Ordinary Differential Equations

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H ANDBOOK OF D IFFERENTIAL E QUATIONS O RDINARY D IFFERENTIAL E QUATIONS VOLUME II

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H ANDBOOK OF D IFFERENTIAL E QUATIONS O RDINARY D IFFERENTIAL E QUATIONS VOLUME II Edited by

A. CAÑADA Department of Mathematical Analysis, Faculty of Sciences, University of Granada, Granada, Spain

P. DRÁBEK Department of Mathematics, Faculty of Applied Sciences, University of West Bohemia, Pilsen, Czech Republic

A. FONDA Department of Mathematical Sciences, Faculty of Sciences, University of Trieste, Trieste, Italy

2005

NORTH HOLLAND

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© 2005 Elsevier B.V. All rights reserved. This work is protected under copyright by Elsevier B.V., and the following terms and conditions apply to its use: Photocopying Single photocopies of single chapters may be made for personal use as allowed by national copyright laws. Permission of the Publisher and payment of a fee is required for all other photocopying, including multiple or systematic copying, copying for advertising or promotional purposes, resale, and all forms of document delivery. Special rates are available for educational institutions that wish to make photocopies for non-profit educational classroom use. Permissions may be sought directly from Elsevier’s Rights Department in Oxford, UK: phone (+44) 1865 843830, fax (+44) 1865 853333, e-mail: [email protected]. Requests may also be completed on-line via the Elsevier homepage (http://www.elsevier.com/locate/permissions). In the USA, users may clear permissions and make payments through the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA; phone: (+1) (978) 7508400, fax: (+1) (978) 7504744, and in the UK through the Copyright Licensing Agency Rapid Clearance Service (CLARCS), 90 Tottenham Court Road, London W1P 0LP, UK; phone: (+44) 20 7631 5555, fax: (+44) 20 7631 5500. Other countries may have a local reprographic rights agency for payments. Derivative Works Tables of contents may be reproduced for internal circulation, but permission of the Publisher is required for external resale or distribution of such material. Permission of the Publisher is required for all other derivative works, including compilations and translations. Electronic Storage or Usage Permission of the Publisher is required to store or use electronically any material contained in this work, including any chapter or part of a chapter. Except as outlined above, no part of this work may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without prior written permission of the Publisher. Address permissions requests to: Elsevier’s Rights Department, at the fax and e-mail addresses noted above. Notice No responsibility is assumed by the Publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made.

First edition 2005 Library of Congress Cataloging in Publication Data: A catalog record is available from the Library of Congress. British Library Cataloguing in Publication Data: A catalogue record is available from the British Library.

ISBN 0 444 52027 9 Set ISBN: 0 444 51742 1 ∞ The paper used in this publication meets the requirements of ANSI/NISO Z39.48-1992 (Permanence of Paper).

Printed in The Netherlands.

Preface This handbook is the second volume in a series devoted to self contained and up-to-date surveys in the theory of ordinary differential equations, written by leading researchers in the area. All contributors have made an additional effort to achieve readability for mathematicians and scientists from other related fields, in order to make the chapters of the volume accessible to a wide audience. These ideas faithfully reflect the spirit of this multivolume and the editors hope that it will become very useful for research, learning and teaching. We express our deepest gratitude to all contributors to this volume for their clearly written and elegant articles. This volume consists of six chapters covering a variety of problems in ordinary differential equations. Both, pure mathematical research and real word applications are reflected pretty well by the contributions to this volume. They are presented in alphabetical order according to the name of the first author. The paper by Barbu and Lefter is dedicated to the discussion of the first order necessary and sufficient conditions of optimality in control problems governed by ordinary differential systems. The authors provide a complete analysis of the Pontriaghin maximum principle and dynamic programming equation. The paper by Bartsch and Szulkin is a survey on the most recent advances in the search of periodic and homoclinic solutions for Hamiltonian systems by the use of variational methods. After developing some basic principles of critical point theory, the authors consider a variety of situations where periodic solutions appear, and they show how to detect homoclinic solutions, including the so-called “multibump” solutions, as well. The contribution of Cârj˘a and Vrabie deals with differential equations on closed sets. After some preliminaries on Brezis–Browder ordering principle and Clarke’s tangent cone, the authors concentrate on problems of viability and problems of invariance. Moreover, the case of Carathéodory solutions and differential inclusions are considered. The paper by Hirsch and Smith is dedicated to the theory of monotone dynamical systems which occur in many biological, chemical, physical and economic models. The authors give a unified presentation and a broad range of the applicability of this theory like differential equations with delay, second order quasilinear parabolic problems, etc. The paper by López-Gómez analyzes the dynamics of the positive solutions of a general class of planar periodic systems, including those of Lotka– Volterra type and a more general class of models simulating symbiotic interactions within global competitive environments. The mathematical analysis is focused on the study of coexistence states and the problem of ascertaining the structure, multiplicity and stability of these coexistence states in purely symbiotic and competitive environments. Finally, the paper by Ntouyas is a survey on nonlocal initial and boundary value problems. Here, some old and new results are established and the author shows how the nonlocal initial or boundv

vi

Preface

ary conditions generalize the classical ones, having many applications in physics and other areas of applied mathematics. We thank again the Editors at Elsevier for efficient collaboration.

List of Contributors Barbu, V., “Al.I. Cuza” University, Ia¸si, Romania, and “Octav Mayer” Institute of Mathematics, Romanian Academy, Ia¸si, Romania (Ch. 1) Bartsch, T., Universität Giessen, Giessen, Germany (Ch. 2) Cârj˘a, O., “Al. I. Cuza” University, Ia¸si, Romania (Ch. 3) Hirsch, M.W., University of California, Berkeley, CA (Ch. 4) Lefter, C., “Al.I. Cuza” University, Ia¸si, Romania, and “Octav Mayer” Institute of Mathematics, Romanian Academy, Ia¸si, Romania (Ch. 1) López-Gómez, J., Universidad Complutense de Madrid, Madrid, Spain (Ch. 5) Ntouyas, S.K., University of Ioannina, Ioannina, Greece (Ch. 6) Smith, H., Arizona State University, Tempe, AZ (Ch. 4) Szulkin, A., Stockholm University, Stockholm, Sweden (Ch. 2) Vrabie, I.I., “Al. I. Cuza” University, Ia¸si, Romania, and “Octav Mayer” Institute of Mathematics, Romanian Academy, Ia¸si, Romania (Ch. 3)

vii


Contents Preface List of Contributors Contents of Volume 1

v vii xi

1. Optimal control of ordinary differential equations V. Barbu and C. Lefter 2. Hamiltonian systems: periodic and homoclinic solutions by variational methods T. Bartsch and A. Szulkin 3. Differential equations on closed sets O. Cârj˘a and I.I. Vrabie 4. Monotone dynamical systems M.W. Hirsch and H. Smith 5. Planar periodic systems of population dynamics J. López-Gómez 6. Nonlocal initial and boundary value problems: a survey S.K. Ntouyas Author index Subject index

1 77 147 239 359 461

559 565

ix


Contents of Volume 1 Preface List of Contributors

v vii

1. A survey of recent results for initial and boundary value problems singular in the dependent variable R.P. Agarwal and D. O’Regan 2. The lower and upper solutions method for boundary value problems C. De Coster and P. Habets 3. Half-linear differential equations O. Došlý 4. Radial solutions of quasilinear elliptic differential equations J. Jacobsen and K. Schmitt 5. Integrability of polynomial differential systems J. Llibre 6. Global results for the forced pendulum equation J. Mawhin 7. Wa˙zewski method and Conley index R. Srzednicki Author Index Subject Index

1 69 161 359 437 533 591

685 693

xi


CHAPTER 1

Optimal Control of Ordinary Differential Equations Viorel Barbu and C˘at˘alin Lefter University “Al.I. Cuza”, Ia¸si, Romania, and Institute of Mathematics “Octav Mayer”, Romanian Academy, Romania

Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1. The calculus of variations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2. General form of optimal control problems . . . . . . . . . . . . . . . . . . . . . . 2. Preliminaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Elements of convex analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Ekeland’s variational principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Elements of differential geometry and exponential representation of flows . . . . 3. The Pontriaghin maximum principle . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. The main theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Proof of the maximum principle . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Convex optimal control problems . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5. Reachable sets and optimal control problems . . . . . . . . . . . . . . . . . . . . 3.6. Geometric form of Pontriaghin maximum principle . . . . . . . . . . . . . . . . 3.7. Free time optimal control problems . . . . . . . . . . . . . . . . . . . . . . . . . 4. The dynamic programming equation . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Optimal feedback controllers and smooth solutions to Hamilton–Jacobi equation 4.2. Linear quadratic control problems . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3. Viscosity solutions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4. On the relation between the two approaches in optimal control theory . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

HANDBOOK OF DIFFERENTIAL EQUATIONS Ordinary Differential Equations, volume 2 Edited by A. Cañada, P. Drábek and A. Fonda © 2005 Elsevier B.V. All rights reserved 1

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3 4 9 10 10 15 16 29 29 32 38 47 55 57 59 62 62 65 68 72 74

Optimal control of ordinary differential equations

3

1. Introduction The theory of control of differential equations has developed in several directions in close relation with the practical applications of the theory. Its evolution has shown that its methods and tools are drawn from a large spectrum of mathematical branches such as ordinary differential equations, real analysis, calculus of variations, mechanics, geometry. Without being exhaustive we just mention, as subbranches of the control theory, the controllability, the stabilizability, the observability, the optimization of differential systems and of stochastic equations or optimal control. For an introduction to these fields, and not only, see [22,33,38], as well as [2,25] and [26] for a geometric point of view. The purpose of this work is to discuss the first order necessary and sufficient conditions of optimality in control problems governed by ordinary differential systems. We do not treat the optimal control of partial differential equations although all basic questions of the finite dimensional theory (existence of optimal control, maximum principle, dynamic programming) remain valid but the treatment requires more sophisticated methods because of the infinite dimensional nature of the problems (see [4,27,38]). In Section 1 we present some aspects and ideas in the classical Calculus of variations that lead later, in the fifties, to the modern theory of optimal control for differential equations. Section 2 presents some preliminary material. It contains elements of convex analysis and the generalized differential calculus for locally Lipschitz functionals, introduced by F.H. Clarke [10]. This will be needed for the proof of the maximum principle of Pontriaghin, under general hypotheses, in Section 3.1. We then discuss the exponential representation of flows, introduced by A. Agrachev and R. Gamkrelidze in order to give a geometric formulation to the maximum principle that we will describe in Sections 3.5, 3.6. Section 3 is concerned with the Pontriaghin maximum principle for general Bolza problems. There are several proofs of this famous classical result and here, following F.H. Clarke’s ideas (see [11]), we have adapted the simplest one relying on Ekeland’s variational principle. Though the maximum principle given here is not in its most general form, it is however sufficiently general to cover most of significant applications. Some examples are treated in detail in Section 3.4. Since geometric control theory became in last years an important branch of mathematics (for an introduction to the theory see [2,26]), it is useful and interesting to give a geometric formulation of optimal control problems and, consequently, a geometric form of the maximum principle. Free time optimal problems are also considered as a special case. In the last section we present the dynamic programming method in optimal control problems based on the partial differential equation of dynamic programming, or Bellman equation (see [7]). The central result of this chapter says that the value function is a viscosity solution to Bellman equation and that, if a classical solution exists, then an optimal control, in feedback form, is obtained. Applications to linear quadratic problems are given. We discuss also the relationship between the maximum principle and the Bellman equation and we will see in fact that the dynamic programming equation is the Hamilton–Jacobi equation for the Hamiltonian system given by the maximum principle.

4

V. Barbu and C. Lefter

1.1. The calculus of variations In this section we point out the fundamental lines of development in the Calculus of variations. We will not impose rigorous assumptions on the functions entering the described problems, they will be as regular as needed. The main purpose is just to emphasize some fundamental ideas that will be reencountered, in a metamorphosed form, in the theory of optimal control for differential equations. For a rigorous presentation of the theory a large literature may be cited, however we restrict for instance to [8,24] and to a very nice survey of extremal problems in mathematics, including the problems of Calculus of variations, in [34]. Let M be an n-dimensional manifold, and M0 , M1 be subsets (usually submanifolds) of M. L : R × T M → R is the Lagrangean function, T M being the tangent bundle of M. The generic problem of the classical Calculus of variations consists in finding a curve, y ∗ , which minimizes a certain integral J (y) =

t1

t0

L t, y(t), y ′ (t) dt

(1.1)

in the space of curves Y = y : [t0 , t1 ] → M; y(tj ) ∈ Mj , j = 1, 2, y continuous and piecewise C 1 .

The motivation for studying such problems comes from both geometry and classical mechanics. E XAMPLES . 1. The brachistocrone. The classical brachistocrone problem proposed by Johann Bernoulli in 1682, asks to find the curve, in a vertical plane, on which a material point, moving without friction under the action of its weight, is reaching the lower end of the curve in minimum time. More precisely, if the curve is joining two points y(t0 ) = y0 , y(t1 ) = y1 , then the time necessary for the material point to reach y1 from y0 is T=

−1/2 2 2g y(t) − y0 1 + y ′ (x) dt.

t1

t0

The curve with this property is a cycloid. 2. The minimal surface of revolution. One is searching for the curve y : [t0 , t1 ] → R, y(t0 ) = y0 , y(t1 ) = y1 , which generates the surface of revolution of least area. The functional to be minimized is t1 2 J (y) = 2π y(x) 1 + y ′ (t) dt. t0

The solution is the catenary. 3. Lagrangean mechanics. A mechanical system with a finite number of degrees of freedom is mathematically modelled by a manifold M and a Lagrangean function


5

L : R × T M → R (see [3]). The manifold M is the configuration space of the mechanical system. The points y ∈ M are generalized coordinates and the y ′ ∈ T M are generalized speeds. The principle of least action of Maupertuis–d’Alembert–Lagrange states that the trajectories of the mechanical system are extremal for the functional J defined in (1.1). Consider the case of a system of N material points in the 3 dimensional space, moving under the action of mutual attraction forces. In this case the configuration space is (R3 )N , while the Lagrangean is L=T −U

(1.2)

where T is the kinetic energy T=

N 1 i=1

2

mi |xi′ |2

and U is the potential energy U (x1 , . . . , xN ) =

N kmi mj , |xi − xj | i=1

k is an universal constant. To make things clear we consider the simplest problem in the Calculus of variations when M = Rn and y0 , y1 are fixed. We consider the space of variations Y = {h : [t0 , t1 ] → Rn ; h(t0 ) = h(t1 ) = 0, h ∈ C 1 }; if y ∗ is a minimum of J in Y , then the first variation d ∗ ∗ = 0. (1.3) δJ (y )h := J (y + sh) ds s=0

A curve that satisfies (1.3) is called extremal and this is only a necessary condition for a curve to realize the infimum of J . One easily computes δJ (y)h =

t1 t0

Ly t, y ∗ (t), (y ∗ )′ (t) · h + Ly ′ t, y ∗ (t), (y ∗ )′ (t) · h′ dt

where Ly , Ly ′ are the gradients of L with respect to y and y ′ , respectively. If y ∗ is C 2 , an integration by parts in the previous formula gives d Ly t, y ∗ (t), (y ∗ )′ (t) − Ly ′ t, y ∗ (t), (y ∗ )′ (t) = 0 dt

(1.4)

which are the Euler–Lagrange equations. It is a system of n differential equations of second order.

6


It may be proved that if the Hessian matrix (Ly ′ y ′ ) > 0, then the regularity of L is inherited by the extremals, for instance if L ∈ C 2 then the extremals are C 2 and thus satisfy the Euler–Lagrange system. The proof of this fact is based on the first of the Weierstrass– Erdmann necessary conditions which state that, along each extremal, Ly ′ and the Hamiltonian defined below in (1.6) are continuous. Another necessary condition for the extremal y ∗ to realize the infimum of J is that (Ly ′ y ′ ) 0 along y ∗ . This is the Legendre necessary condition. Suppose from now on that (Ly ′ y ′ ) is a nondegenerate matrix at any point (t, y, y ′ ). We set p = Ly ′ (t, y, y ′ ).

(1.5)

Since (Ly ′ y ′ ) is nondegenerate, formula (1.5) defines a change of coordinates (t, y, y ′ ) → (t, y, p). From the geometric point of view it maps T M locally onto T ∗ M, the cotangent bundle. In mechanics p is called the generalized momentum of the system and in most applications its significance is of adjoint (or dual) variable. We consider the Hamiltonian H (t, y, p) = (p, y ′ ) − L(t, y, y ′ ).

(1.6)

If, moreover, L is convex in y ′ then H = L∗ , the Legendre transform of L: H (t, y, p) = sup (p, y ′ ) − L(t, y, y ′ ) . y′

For example, if L is given by (1.2) then H = T + U and it is just the total energy of the system. If we compute the differential of H along an extremal, taking into account the Euler–Lagrange equations, we obtain dH = −Lt dt −

d Ly ′ dy + y ′ dp. dt

Thus, through these transformations we obtain the Hamiltonian equations  ∂H ′    y = ∂p (t, y, p),  ′ ∂H  p = − (t, y, p). ∂y

(1.7)

Solutions of the Hamiltonian system are in fact extremals corresponding to the Lagrangean

(y, p), (y ′ , p ′ )) = p · y ′ − H (t, y, p) in T ∗ M. The projections on M are extremals L(t, for J . Roughly speaking, solving the Euler–Lagrange system is equivalent to solving the Hamiltonian system of 2n differential equations of first order. From the mechanics point of view these transforms give rise to the Hamiltonian mechanics which study the mechanical phenomena in the phase space T ∗ M while in mathematics this is the start point for the symplectic geometry (see for example [3,28]).


7

Consider now the more general case of end points lying on two submanifolds M0 , M1 . It may be shown that the first variation of J in y computed in an admissible variation h (assume that also t0 , t1 are free) is δJ (y)h =

t1

t0

where

t Ly (t, y, y ′ ) · h + Ly ′ (t, y, y ′ ) · h′ dt + {pδy − H δt}t1 0

(1.8)

t H δt t1 = H t1 , y(t1 ), p(t1 ) δt1 − H t0 , y(t0 ), p(t0 ) δt0 , 0

t pδy t1 = p(t1 )δy1 − p(t2 )δy0 . 0

It turns out that y ∗ ∈ C 2 is extremal for J if y ∗ satisfies the Euler–Lagrange equations (1.4) and in addition t {pδy − H δt}t1 = 0. 0

(1.9)

These are transversality conditions. In case t0 , t1 are fixed, these become p(t0 ) ⊥ M0 ,

p(t1 ) ⊥ M1 .

Since (Ly ′ y ′ ) is supposed to be nondegenerate, the Euler–Lagrange equations form a second order nondegenerate system of equations and this implies that the family of extremals starting at moment t0 from a given point of y0 ∈ M cover a whole neighborhood V of (t0 , y0 ) (we just vary the value of y ′ (t0 ) in the associated Cauchy problem and use some result on the differentiability of the solution with respect to the initial data, coupled with the inverse function theorem). We consider now the function S : V → R defined by S(t, y) =

t

t0

L s, x(s), x ′ (s) ds

where the integral is computed along the extremal x(s) joining the points (t0 , y0 ) and (t, y). It may be proved that S satisfies the first order nonlinear partial differential equation St + H (t, y, Sy ) = 0.

(1.10)

This is the Hamilton–Jacobi equation. This is strongly related to the Hamiltonian system (1.7) which is the system of characteristics associated to the partial differential equation (1.10) (see [16]). A partial differential equation is usually a more complicated mathematical object than an ordinary differential system. Solving a first order partial differential system reduces to solving the corresponding characteristic system. This is the method of characteristics (see [16]).

8


However, this duality may be successfully used in a series of concrete situations to integrate the Hamiltonian systems appearing in mechanics or in the calculus of variations. This result, belonging to Hamilton and Jacobi, states that if a general solution for the Hamilton–Jacobi equation (1.10) is known, then the Hamiltonian system may be integrated (see [3,16,24]). More precisely, we assume that a general solution of (1.10) is 2S ∂S S = S(t, y1 , . . . , yn , α1 , . . . , αn ) such that the matrix ( ∂y∂i ∂α ) is nondegenerated. Then ∂α j j are prime integrals and a general solution of the Hamiltonian system (1.7) is given by the 2n system of implicit equations: βi =

∂S , ∂αi

pi =

∂S . ∂yi

In fact S is a generating function for the symplectic transform (yi , pi ) → (βi , αi ) and in the new coordinates the system (1.7) has a simple form for which the Hamiltonian function is ≡ 0. A last remark is that a general solution to equation (1.10) may be found if variables of H are separated (see [3,24]). We considered previously first order necessary conditions. Suppose that (Ly ′ y ′ ) > 0. Let us take now the second variation d2 δ 2 J (y)h := 2 J (y + sh) . ds s=0

This is a quadratic form denoted by y

Q (h) =

t1

Ω y (t, h, h′ ) dt

t0

where the new Lagrangean Ω y (t, h, h′ ) = Lyy (t, y, y ′ )h, h + 2 Lyy ′ (t, y, y ′ )h, h′ + Ly ′ y ′ (t, y, y ′ )h′ , h′ .

Here (·, ·) denotes the scalar product in Rn and we assumed that the matrix (Lyy ′ ) is symmetric (for n = 1 this is trivial, in higher dimensions the hypothesis simplifies computations but may be omitted). Clearly, if y ∗ realizes a global minimum of J , then the quadratic form Q(y ∗ ) 0. The positivity of Q is related to the notion of conjugate point. A point t is conjugate to t0 along the extremal y ∗ if there exists a non trivial solution h : [t0 , t] → Rn , h(t0 ) = h(t) = 0 of the second Euler equation: y∗

Ωh −

d y∗ Ω ′ = 0. dt h

The Jacobi necessary condition states that if y ∗ realizes the infimum of J then the open interval (t0 , t1 ) does not contain conjugate points to t0 . If y ∗ is just an extremal and the closed interval [t0 , t1 ] does not contain conjugate points to t0 , then y ∗ is a local weak minimum of J (in C 1 topology).


9

1.2. General form of optimal control problems We consider the controlled differential equation y ′ (t) = f t, y(t), u(t) ,

t ∈ [0, T ].

(1.11)

The input function u : [0, T ] → Rm is called controller or control and y : [0, T ] → Rn is the state of the system. We will assume that u ∈ U where U is the set of measurable, locally integrable functions which satisfy the control constraints: u(t) ∈ U (t) a.e. t ∈ [0, T ]

(1.12)

where U (t) ⊂ Rn are given closed subsets. The differential system (1.11) is called the state system. We also consider a Lagrangean L and the cost functional J (y, u) =

T

0

L t, y(t), u(t) dt + g y(0), y(T ) .

(1.13)

A pair (y, u) is said to be admissible pair if it satisfies (1.11), (1.12) and J (y, u) < +∞. The optimal control problem we consider is min J (y, u); y(0), y(T ) ∈ C, (y, u) verifies (1.11)

(1.14)

Here C ⊂ Rn × Rn is a given closed set. A controller u∗ for which the minimum in (1.14) is attained is called optimal controller. The corresponding states y ∗ are called optimal states while (y ∗ , u∗ ) will be referred as optimal pairs. By solution to (1.11) we mean an absolutely continuous function y : [0, T ] → R (i.e., y ∈ AC([0, T ]; Rn ) which satisfies almost everywhere the system (1.11). In the special case f (t, y, u) ≡ u, problem (1.14) reduces to the classical problem of calculus of variations that was discussed in Section 1.1. For different sets C we obtain different types of control problems. For example, if C contains one element, that is the initial and final states are given, we obtain a Lagrange problem. If the initial state of the system is given and the final one is free, C = {y0 } × R, one obtains a Bolza problem. A Bolza problem with the Lagrangean L ≡ 0 becomes a Mayer problem. An optimal controller u∗ is said to be a bang-bang controller if u∗ ∈ ∂U (t) a.e. t ∈ (0, T ) where ∂U stands for the topological boundary of U . It should be said that the control constraints (1.12) as well as end point constraints (y(0), y(T )) ∈ C can be implicitely incorporated into the cost functional J by redefining L and g as

y, u) = L(t, u) if u ∈ U (t), L(t, +∞ otherwise, g(y ˜ 1 , y2 ) =

g(y1 , y2 ) +∞

if (y1 , y2 ) ∈ C, otherwise.

10


Moreover, integral (isoperimetric) constraints of the form

T

0

0

T

hi t, y(t), u(t) dt αi ,

hi t, y(t), u(t) dt = αi ,

i = 1, . . . , l, i = l + 1, . . . , m

can be implicitly inserted into problem (1.14) by redefining new state variables {z1 . . . , zm } and extending the state system (1.11) to  ′   y (t) = f t, y(t), u(t) , t ∈ (0, T ), z′ (t) = h t, y(t), u(t) ,   z(0) = 0, zi (T ) αi for i = 1, . . . , l, zi (T ) = αi for i = l + 1, . . . , m

where h = {hi }m i=1 . For the new state variable X = (y, z) we have the end point constraints X(0), X(T ) ∈ K,

where

K=

(y0 , 0, . . . , 0), (y1 , z) ∈ Rn+m × Rn+m , (y0 , y1 ) ∈ C, zi αi , i = 1, . . . , l, zi = αi , i = l + 1, . . . , m .

2. Preliminaries 2.1. Elements of convex analysis Here we shall briefly recall some basic results pertaining convex analysis and generalized gradients we are going to use in the formulation and in proof of the maximum principle. Let X be a real Banach space with the norm · and dual X ∗ . Denote by (·, ·) the pairing between X and X ∗ . The function f : X → R = ]−∞, +∞] is said to be convex if f λx + (1 − λ)y λf (x) + (1 − λ)f (y), 0 λ 1, x, y ∈ X. (2.1)

The set D(f ) = {x ∈ X; f (x) < ∞} is called the effective domain of f and E(f ) = (x, λ) ∈ X × R; f (x) λ

(2.2)

is called the epigraph of f . The function f is said to be lower semicontinuous (l.s.c.) if lim inf f (x) f (x0 ). x→x0

The function f is said to be proper if f ≡ +∞.


11

It is easily seen that a convex function is l.s.c. if and only if it is weakly lower semicontinuous. Indeed, f is l.s.c. if and only if every level set {x ∈ X; f (x) λ} is closed. Moreover, the level sets are also convex, by the convexity of f ; the conclusion follows by the coincidence of convex closed sets and weakly closed sets. Note also that, by Weierstrass theorem, if X is a reflexive Banach space and if f is convex, l.s.c. and lim x →∞ f (x) = +∞, then f attains its infimum on X. We note without proof (see, e.g., [9,6]) the following result: P ROPOSITION 2.1. Let f : X → R be a l.s.c. convex function. Then f is bounded from below by an affine function and f is continuous on int D(f ). Given a l.s.c. convex function f : X → R, the mapping ∂f : X → X ∗ defined by ∂f (x) = w ∈ X ∗ ; f (x) f (u) + (w, x − u), ∀u ∈ X

(2.3)

is called the subdifferential of f . An element of ∂f (x) is called subgradient of f at x. The mapping ∂f is generally multivalued. The set D(∂f ) = x; ∂f (x) = φ

is the domain of ∂f . It is easily seen that x0 is a minimum point for f on X if and only if 0 ∈ ∂f (x0 ). We note also, without proof, some fundamental properties of ∂f (see, e.g., [6,9,31]). P ROPOSITION 2.2. Let f : X → R be convex and l.s.c. Then int D(f ) ⊂ D(∂f ). Let C be a closed convex set and let IC (x) be the indicator function of C, i.e., IC (x) =

0, +∞,

x ∈ C, x∈ / C.

Clearly, IC (x) is convex and l.s.c. Moreover, we have D(∂IC (x)) = C and ∂IC (x) = w ∈ X ∗ ; (w, x − u) 0, ∀u ∈ C .

∂IC (x) is precisely the normal cone to C at x, denoted NC (x). If F : X → Y is a given function, X, Y Banach spaces, we set F ′ (x, y) = lim

λ→0

F (x + λy) − F (x) λ

called the directional derivative of F in direction y. By definition F is Gâteaux differentiable in x if ∃DF (x) ∈ L(X, Y ) such that F ′ (x, v) = DF (x)v,

∀v ∈ X.

(2.4)

12


In this case, DF is the Gâteaux derivative (differential) at x. If f : X → R is convex and Gâteaux differentiable in x, then it is subdifferentiable at x and ∂f (x) = ∇f (x). In general, we have P ROPOSITION 2.3. Let f : X → R be convex, l.s.c. and proper. Then, for each x0 ∈ D(∂f ) ∂f (x0 ) = w ∈ X ∗ ; f ′ (x0 , u) (w, u), ∀w ∈ X .

(2.5)

If f is continuous at x0 , then

f ′ (x0 , u) = sup (w, u); w ∈ ∂f (x0 ) ,

∀u ∈ X.

(2.6)

Given f : X → R, the function f ∗ : X ∗ → R

f ∗ (p) = sup (p, x) − f (x); x ∈ X

is called the conjugate of f , or the Legendre transform of f . P ROPOSITION 2.4. Let f : X → R be convex, proper, l.s.c. Then the following conditions are equivalent: 1. x ∗ ∈ ∂f (x), 2. f (x) + f ∗ (x ∗ ) = (x ∗ , x), 3. x ∈ ∂f ∗ (x ∗ ). In particular, ∂f ∗ = (∂f )−1 and f = f ∗∗ . In general, ∂(f + g) ⊃ ∂f + ∂g and the inclusion is strict. We have, however, P ROPOSITION 2.5 (Rockafellar). Let f and g be l.s.c. and convex on D. Assume that D(f ) ∩ int D(g) = φ. Then ∂(f + g) = ∂f + ∂g.

(2.7)

We shall assume now that X = H is a Hilbert space. Let f : H → R be convex, proper and l.s.c. Then ∂f is maximal monotone. In other words, (y1 − y2 , x1 − x2 ) 0,

∀(xi , yi ) ∈ ∂f, i = 1, 2

(2.8)

and R(I + λ∂f ) = H,

∀λ > 0.

(2.9)

R(I + λ∂f ) is the range of I + λ∂f . The mapping (∂f )λ = λ−1 I − (I + λ∂f )−1 ,

λ>0

(2.10)


13

is called the Yosida approximation of f . Denote by fλ : H → R the function |x − y|2 + f (y); y ∈ H , fλ (x) = inf 2λ

λ>0

which is called the regularization of f (see [29]). P ROPOSITION 2.6 (Brezis [9]). Let f : H → R be convex and l.s.c. Then fλ is Fréchet differentiable on H , ∂fλ = {∇fλ } and 2 −1 λ , fλ (x) = ∂fλ (x) + f I + λ∂f (x) 2 lim fλ (x) = f (x),

λ→0

∀x ∈ H.

(2.11) (2.12)

Consider the function Ig : Lp (Ω) → R defined by Ig (y) =

  

Ω

g x, y(x) dx

+∞

if g ·, y(·) ∈ L1 (Ω),

(2.13)

otherwise

where g : Ω × Rm → R is a function satisfying (Ω is a measurable subset of Rn ) 1. g(x, ·) : Rm → R is convex and l.s.c. for a.e. x ∈ ω. 2. g is L × B measurable, i.e. g is measurable with respect to the σ -algebra of subsets of Ω × Rm generated by products of Lebesgue sets in Ω and Borelian sets in Rm . 3. g(x, y) (α(x), y) + β(x), a.e. x ∈ Ω, y ∈ Rm , where α ∈ Lq (Ω),

β ∈ L1 (Ω),

1 1 + = 1. p q

4. ∃y0 ∈ Lp (Ω) such that Ig (y0 ) < +∞. P ROPOSITION 2.7. Let 1 p < ∞. Then Ig is convex, l.s.c. and ≡ +∞. Moreover, ∂Ig (y) = w ∈ Lq (Ω); w(x) ∈ ∂g x, y(x) a.e. x ∈ Ω .

E XAMPLE 2.1. Let

Then

C = y ∈ Lp (Ω); a y(x) b, a.e. x ∈ Ω . g(y) =

0 if a y b, +∞ otherwise

(2.14)

14


and so by (2.14) NC (y) = w ∈ Lq (Ω); w(x) ∈ N[a,b] y(x) a.e. x ∈ Ω = w ∈ Lq (Ω); w(x) = 0 if a < y(x) < b, w(x) 0 if y(x) = a, w(x) 0 if y(x) = b .

(2.15)

The case Ig : L∞ (Ω) → R is more delicate since in this case ∂Ig (y) takes values in a measure space on Ω (see [32]). Generalized gradients Let X be a Banach space of norm · and dual X ∗ . The function f : X → R is said to be locally Lipschitz continuous if for any bounded subset M of X there exists a constant LM such that f (x) − f (y) LM x − y ,

∀x, y ∈ M.

The directional derivative of f in x is defined by f 0 (x, v) = lim sup λ−1 f (y + λv) − f (y) .

(2.16)

y→x λ→0

The function f 0 is finite, positively homogeneous in v and subadditive. Then, by the Hahn– Banach theorem, ∃η ∈ X ∗ such that (η, v) f 0 (x, v),

∀v ∈ X.

By definition, the generalized gradient of f in x, denoted ∂f (x), is the set ∂f (x) = η ∈ X ∗ ; (η, v) f 0 (x, v), ∀v ∈ X .

(2.17)

P ROPOSITION 2.8 (See [10,12]). For each x ∈ X, ∂f (x) is a convex and w ∗ -compact subset of X ∗ . Moreover, f 0 (x, v) = sup (η, v); η ∈ ∂f (x) ,

∀v ∈ X

∗

and the map ∂f : X → 2X is weakly star upper semicontinuous, i.e. if xn → x and ηn → η weakly star in X ∗ , then η ∈ ∂f (x). If f is locally Lipschitz and Gâteaux differentiable, then ∂f = Df . Moreover, if f is convex and locally Lipschitz, then ∂f is precisely the subdifferential of f . Given a closed subset C of X, denote by dC the distance function dC (x) = inf x − y ; y ∈ C ,

∀x ∈ X.


15

We can see that dC is Lipschitzian dC (x) − dC (y) x − y ,

∀x, y ∈ X.

Let x ∈ C. The element v ∈ X is said to be tangent to C in x if dC0 (x, v) = 0. The set of all tangent elements v is denoted TC (x) (the tangent cone to C at x). The normal cone NC (x) to C at x is by definition NC (x) = η ∈ X ∗ ; (η, v) 0, ∀v ∈ TC (x) .

P ROPOSITION 2.9. The vector h ∈ X is tangent to C in x if and only if ∀{xn } ⊂ C convergent to x and each {λn } → 0, there is {hn } → h such that xn + λn hn ∈ C,

∀n.

P ROPOSITION 2.10. If f, g are locally Lipschitzian, then ∂(f + g)(x) ⊂ ∂f (x) + ∂g(x),

∀x ∈ X.

If C is a closed subset of X and if f attains its minimum on C in x, then 0 ∈ ∂f (x) + NC (x). We refer to the book [12] for further properties of generalized gradients.

2.2. Ekeland’s variational principle Here we shall briefly recall, without proof, an important result known in literature as Ekeland variational principle [21]. T HEOREM 2.1. Let X be a complete metric space and F : X → R be a l.s.c. function, ≡ +∞ and bounded from below. Let ε > 0 and x ∈ X be such that F (x) inf F (y); y ∈ X + ε.

(2.18)

Then there exists xε ∈ X such that F (xε ) F (x), √ d(xε , x) ε, F (xε ) < F (y) +

(2.19) (2.20) √

εd(xε , y),

∀y = xε .

(2.21)

16


Roughly speaking, Theorem 2.1 says that xε is a minimum point of the function √ y → F (y) + εd(xε , y). C OROLLARY 2.1. let X be a Banach space and F : X → R be Gâteaux differentiable and bounded from below. Then ∀ε > 0, ∃xε ∈ X such that F (x) inf F (y); y ∈ X + ε, (2.22) √ ∇F (xε ) ε. (2.23)

One may thus construct a minimizing sequence of almost critical points.

2.3. Elements of differential geometry and exponential representation of flows In what follows we present some basic facts concerning the operator calculus introduced by A. Agrachev and R. Gamkrelidze (see [1,2,23]) called exponential representation of flows or chronological calculus. This is a very elegant tool that allows to replace nonlinear objects such as manifolds, tangent vector fields, flows, diffeomorphisms with linear ones which will be functionals and operators on the algebra C ∞ (M) of real infinitely differentiable functions on M. At the end of the section a variation of parameters formula will be given; this formula will show to be very useful in proving the geometric form of Pontriaghin maximum principle. We follow essentially the description in [2]. Differential equations on manifolds In what follows M is a smooth n-dimensional man ifold, T M = y∈M Ty M is the tangent bundle. We consider the Cauchy problem for the nonautonomous ordinary differential equation: ′ y = f t (y) := f (t, y), (2.24) y(0) = y0 where f t is a nonautonomous vector field on M, that is f t (y) ∈ Ty M for any y ∈ M, t ∈ R. In the case M = Rn or a subdomain of Rn we have the following classical theorem of Carathéodory (see [15, Chapter 2, Theorem 1.1]): T HEOREM 2.2. If f is measurable in t for each fixed y and continuous in y for every fixed t and there exists a L1 function m0 such that in a neighborhood of (0, y0 ) f (t, y) m0 (t), then problem (2.24) has a local solution in the extended sense (see Section 1.2). If for any fixed t, fi (t, ·) is C 1 and for any (t, y) there exists an L1 function m1 and neighborhood of (t, y) such that for any (t, y) in this neighborhood ∂fi m1 (t), (t, y) ∂y j


17

then the solution is unique. Moreover, under this assumption the solution is C 1 with respect to the initial data. In order to solve equation (2.24) in the case of a general manifold M, we represent it in local coordinates. Let ϕ : N (y0 ) ⊂ M → N (x0 ) ⊂ Rn , a local chart. In these coordinates the vector field f t is represented as: n ∂ t ϕ∗ f (x) = f˜i (t, x) = f˜t (x). ∂xi i

Here ϕ∗ is the tangent map, or differential of ϕ. Solving problem (2.24) is equivalent to solving the following Cauchy problem in Rn :

x ′ = f˜(t, x), x(0) = x0 .

(2.25)

In order to insure existence and uniqueness of a local solution, we will assume that f˜ satisfies the hypotheses of Theorem 2.2 which are in fact hypothesis on f since they do not depend on the choice of the local chart. Under these hypothesis, by the theorem of Carathéodory, problem (2.25) has a unique local solution x(t, x0 ) which is absolutely continuous with respect to t and C 1 with respect to the initial data x0 and satisfies the equation almost everywhere. The solution of (2.24) is y(t, y0 ) = ϕ −1 (x(t, x0 )) and one may prove that this is independent of the local chart. The solution of the Cauchy problem (2.24) is defined on a maximal interval that we will suppose to be R for all initial data. Such vector fields that determine global flows are called complete. This always happens if the manifold M is compact. If we denote by F t the flow defined by the equation (2.24): F t (y0 ) = y(t, y0 ), then t F ∈ Diff(M) the set of diffeomorphisms of the manifold M and equation (2.24) may be written   d t F (y) = f t ◦ F t (y), y ∈ M, (2.26) dt  0 F = Id . H YPOTHESES . We will suppose from now on that M is a C ∞ manifold and Diff(M) denotes the set of C ∞ diffeomorphisms of M. Moreover, we will suppose that the nonautonomous vector field f t is complete and in any local chart f˜(t, x) is measurable with respect to t for any fixed x and C ∞ with respect to x for every fixed t and there exist locally integrable functions mk (t) such that locally k D f˜(t, x) mk (t). x

These hypotheses insure that the Cauchy problem (2.24) has unique solution depending C ∞ on the initial data.

18


Exponential representation of flows We describe in the sequel how the chronological exponential is defined and we will see that topological and differential structures are translated in the new language into the weak convergence of functionals and operators. Points are represented as algebra homomorphisms from C ∞ (M) to R. If y ∈ M then ˆ = α(y). One may prove that it defines an algebra homomorphism yˆ : C ∞ (M) → R, y(α) for any algebra homomorphism ψ : C ∞ (M) → R, there exists an unique y ∈ M such that ψ = yˆ (see [2]). Diffeomorphisms of the manifold M are represented as automorphisms of the algebra : C ∞ (M) → C ∞ (M) as F (α) = C ∞ (M). More precisely, if F ∈ Diff(M) we define F α ◦ F . More generally, if F : M → N is a smooth map between two manifolds, then : C ∞ (N ) → C ∞ (M) as F (β) = β ◦ F with it defines an algebra homomorphism F ∞ β ∈ C (N ). Observe that if F, G ∈ Diff(M) then F ◦ G = G ◦ F . Tangent vectors. Let f ∈ Ty M. Then, as is well known f may be seen either as tangent vector in y to a curve passing through y or as directional derivative, or Lie derivative, of functions in the point y in the direction f . For the first point of view one considers a smooth curve y(t), y(0) = y, y ′ (0) = v. The second point of view is to consider the Lie derivative Lf α = dtd α(y(t))|t=0 . Through the representation described above, we may construct fˆ : C ∞ (M) → R, fˆ(α) := dtd [y(t)(α)]| ˆ t=0 = Lf α. Obviously, fˆ is a linear functional on ∞ C (M) and satisfies the Leibnitz rule fˆ(αβ) = α(y)fˆ(β) + fˆ(α)β(y).

(2.27)

Any linear functional on C ∞ (M) satisfying (2.27) corresponds in this way to a tangent vector. Vector fields. Let Vec(M) be the set of smooth vector fields on M and let f ∈ Vec(M). Then f defines a linear operator fˆ : C ∞ (M) → C ∞ (M), fˆ(α)(y) = f (y)(α). This operator satisfies the Leibnitz rule fˆ(αβ) = α fˆ(β) + fˆ(α)β.

(2.28)

Any linear functional of C ∞ (M) satisfying (2.28) is called derivation and corresponds to a unique vector field. We study now the behaviour of tangent vectors and vector fields under the action of diffeomorphisms. Let F ∈ Diff(M) and g ∈ Ty M such that g = dtd y(t)|t=0 . Then F∗ g ∈ TF (y) M and is defined as F∗ g = dtd F (y(t))|t=0 . So, if α ∈ C ∞ (M), then

So,

F ∗ g(α) =

d d (α). = g(α ˆ ◦ F ) = gˆ ◦ F = α F y(t) F y(t) (α) dt dt t=0 t=0

. F ∗ g = gˆ ◦ F

(2.29)


19

= yˆ ◦ g, ◦ In the same way, if g ∈ Vec(M), since g(y) ˆ F∗ g(F (y)) = F (y) ◦ F ∗ g = yˆ ◦ F F∗ g. On the other hand F∗ g(F (y)) = F∗ (g(y)) = yˆ ◦ gˆ ◦ F . As y is arbitrary, F ◦ F∗ g = so gˆ ◦ F −1 ◦ gˆ ◦ F = Ad F −1 g. F ˆ ∗g = F

(2.30)

R EMARK 2.1. The notation Ad comes from the theory of Lie groups where it stands for the adjoint representation of the group in the space of linear operators of the associated Lie algebra. In our situation the group of diffeomorphisms of the manifold stands for the Lie group and the associated Lie algebra is the algebra of vector fields. Through the described representation one obtains the group of automorphisms of C ∞ (M) and the associated Lie algebra is the algebra of derivations of C ∞ (M) (see, e.g., [3,28]). The equation (2.24) becomes, through the described representation:   d ˆt y(t) = y(t) ◦ f , dt  y(0) ˆ = yˆ0

so the flow defined by the equation satisfies   d t t ˆt F =F ◦f , dt  0 F = Id .

(2.31)

(2.32)

t is called the right chronological exponential and, in accordance with the linear The flow F case, is denoted by → t = − F exp

0

t

fˆs ds.

(2.33)

In order to simplify notations, we will omit from now on the hat unless confusion is possible and, usually, when we refer to diffeomorphisms and vector fields we mean their representations. We observe however that at this point equations (2.31), (2.32) are not completely rigorous since we have not yet defined a topology in the corresponding spaces of functionals or operators on C ∞ (M). Topology We consider on C ∞ (M) the topology of uniform convergence on compacta of all derivatives. More precisely, if M = Ω ⊂ Rn , for α ∈ C ∞ (M), K ⋐ M and k = (k1 , . . . , kn ), ki 0, we define the seminorms:

α s,K = sup D k α(y); |k| = k1 + · · · + kn s, y ∈ K . This family of seminorms determines a topology on C ∞ (M) which becomes a Fréchet space (locally convex topological linear space with a complete metric topology given by a

20


translation invariant metric). In this topology αm → α iff αm − α s,K → 0 for all s 0 and K ⋐ M. In the case of a general manifold, we choose a locally finite covering of M with charts (Vi , ϕi )i∈I , ϕ : V i → Oi ⊂ Rn diffeomorphisms and let {αi }i∈I be a partition of unity subordinated to this covering. We define the family of seminorms

α s,K = sup D k (αi α) ◦ ϕ −1 (y) |k| s, ϕ −1 (y) ∈ K, i ∈ I .

This family of seminorms depends on the choice of the atlas but the topology defined on C ∞ (M) is independent of this choice. One could also proceed by using the Whitney theorem and considering M as a submanifold of some Euclidean space. Once we have defined the topology on C ∞ (M) we consider the space of linear continuous operators L(C ∞ (M)). The spaces Diff(M) and Vec(M), through the representation are linear subspaces. Indeed, one may easily verify that for f ∈ Vec(M) and F ∈ Diff(M) fˆα C1 α s+1,K , s,K

F α

s,K

C2 α s,K

where the constants C1 = C1 (s, K, f ), C2 = C2 (s, K, F ). We thus define a family of seminorms on Vec(M), respectively Diff(M):

f s,K = sup fˆα s+1,K α s,K = 1 , α α s,K = 1 ,

F s,K = sup F s,K

which define locally convex topologies. On these spaces we also may consider the weak topology induced from C ∞ (M): Fn → F iff Fn α → F α for all α ∈ C ∞ (M) (the same for a sequence of vector fields). Differentiability and integrability of families of functions or operators First of all we define these properties on C ∞ (M) which is a Fréchet space. In general, let X be a Fréchet space whose topology is defined by the family {pk }k∈N of seminorms. The metric on X is defined by d(x, y) =

1 pk (x − y) . 2k 1 + pk (x − y) k∈N

Let h : J ⊂ R → X. The function h is differentiable in t0 if there exists in X the limit lim

t→t0

h(t) − h(t0 ) . t − t0

The function h is Lipschitz continuous if pk ◦ h is Lipschitz for all pk . Differentiability and Lipschitz continuity may also be defined using the metric structure of X. The function h is bounded if pk ◦ h is bounded for all pk .


21

For measurability and integrability we adapt the plan of development for the Bochner integral (see, e.g., [35]). A function h is called a step function if it may be represented as h=

xn χJn

n∈N

where χJn is the characteristic function of a measurable subset Jn ⊂ J . We call such a representation of h a σ -representation and it is obvious that this is not unique. We say that the function h is strongly measurable if h is the limit a.e. of a sequence of step functions. The function h is weakly measurable if x ∗ ◦ h is measurable for all x ∗ ∈ X ∗ . One may prove that if X is separable the two notions of measurability coincide (see Pettis theorem in [35] in the case X is a Banach space). If h is a step function then h is integrable if n

µ(Jn )pk (xn ) ∞

for all the seminorms pk . The integral of h is then defined as h(t) dt = µ(Jn )xn J

n

and it may be shown that it is independent of the order of summation and of the σ -representation of h. If h is a measurable function we say that it is integrable if there exists a sequence of integrable step functions {hn }n∈N such that for all k pk h(t) − hn (t) dt = 0. lim n→+∞ J

In this case one may show that there exists hn (t) dt lim n→+∞ J

and this is independent of the sequence {hn }n∈N with the given properties. The limit is denoted by h(t) dt J

and is the integral of h on J . For a family P t , t ∈ J ⊂ R of linear continuous operators or linear continuous functionals on C ∞ (M) the above notions (continuity, differentiability, boundedness, measurability, integrability) will be considered in the weak sense, that is the function t → P t has one of these properties if P t ◦ α has the corresponding property for all α ∈ C ∞ (M). We will not discuss here the relation between the strong and weak properties.

22


At this point we see that the operator equation (2.32) makes sense and it can be easily proved that it has a unique solution. We point out the Leibnitz rule: d t d t d t t0 t0 t = P ◦Q +P ◦ Q P ◦Q dt dt dt t=t0 t=t0 t=t0

for two functions t → P t , t → Qt differentiable at t0 . Consider now the flow F t defined by (2.24) and Gt = (F t )−1 . If we differentiate the identity F t ◦ Gt = I we obtain F t ◦ f t ◦ Gt + F t ◦

d t G =0 dt

and thus   d t G = −f t ◦ Gt , dt  0 G = Id .

(2.34)

We define thus the left chronological exponential: − exp Gt = ←

t

0

−f t dt.

−1 gˆ for F ∈ Diff(M), Further properties and extensions We have seen that F ∗ g = Ad F d t ) for a flow F t on M such that g ∈ Vec(M). We compute now the differential dt |t=0 Ad(F

We have

  d F t = f ∈ Vec M, dt t=0  F 0 = Id .

d |t=0 Ad F t g = f ◦ g − g ◦ f = [f, g] =: (ad f )g. dt

In the particular case → F =− exp t

t

f s ds

0

we obtain:   d (Ad F t )g = Ad F t ad f t g, dt  Ad F 0 = Id


23

so we may write, formally: t t → → Ad − exp f s ds = − exp ad f s ds . 0

0

Let now F ∈ Diff(M) and g t a nonautonomous vector field. Then t t s −1 − → − → F ◦ exp g ds ◦ F = exp (Ad F g s ) ds. 0

(2.35)

0

Indeed, the both sides of the equality verify the same Cauchy problem for the operator equation   d q t = q t ◦ Ad F g t , dt  0 q = Id and thus, by uniqueness of the solution, they coincide. Now if we take again Gt = (F t )−1 and if we differentiate the identity Gt ◦ F t = Id we obtain that dtd Gt ◦ F t = −Gt ◦ F t ◦ f t and thus d t G = −Gt ◦ Ad F t f t . dt

This gives the relationship between left and right chronological exponentials: t t ← − → Ad F s f s ds. exp exp f s ds = − 0

(2.36)

0

α = If F ∈ Diff(M), as we have seen, it defines an algebra automorphism of C ∞ (M) : F α ◦ F = F ∗ α, where F ∗ is the pull back of C ∞ differential forms defined by F . This suggests the fact that F may be extended, as algebra automorphism to the graded algebra Λ(M) = Λk (M) of differential forms. If ω ∈ Λk (M) then we define ω := F ∗ ω. F

It is well known that F ∗ commutes with exterior differential: F∗ ◦ d = d ◦ F∗ and for ωi ∈ Λki (M), F ∗ (ω1 ∧ ω2 ) = F ∗ (ω1 ) ∧ F ∗ (ω2 ). is an algebra automorphism for Λ(M). We now consider a vector field: So F d t F |t=0 = f, dt

F 0 = Id .

24


The action on Λk (M) is the Lie derivative of differential forms: d t d t ∗ F ω = Lf ω. = F ω dt dt t=0 t=0

We may thus understand the action of a vector field f ∈ Vec(M) as the Lie derivative of differential forms: fˆ = Lf . The chronological exponential may be thus written −→ F t = exp

t

Lf s ds.

0

We point out two fundamental properties of the Lie derivative: t ◦ d = d ◦ F t one obtains that Since F fˆ ◦ d = d ◦ fˆ (equivalently Lf ◦ d = d ◦ Lf ).

Denote by if the interior product of a differential form ω with a vector field f : if ω(f1 , . . . , fk ) = ω(f, f1 , . . . , fk ), for ω ∈ Λk (M), fi ∈ Vec M. Then the classical Cartan’s formula reads: fˆ = d ◦ if + if ◦ d.

(2.37)

Variation of parameters formula Consider the Cauchy problem for the linear differential equation in Rn :

y ′ = Ay + b(t), y(0) = y0 .

The solution of the homogeneous equation (b ≡ 0) is y(t) = eAt y0 . For the nonhomogeneous equation a solution may be found by the variation of constants or variation of parameters method. This consists in searching a solution of the form y(t) = eAt c(t) and an equation for c(t) is obtained: c′ (t) = A(t)b(t). The solution is given by the variation of constants formula y(t) = eAt y0 +

t

eA(t−s) b(s) ds.

0

We consider now the nonlinear differential equation y ′ = f t (y)

(2.38)


→ which generates the flow F t = − exp y ′ = f t (y) + g t (y)

t 0

25

f s ds. We consider also the perturbed equation

→ t f s + g s ds, depending on the perturbation g t . We which generates the flow H t = − exp 0 want to find an expression for this dependence. For this purpose one proceeds as in the linear case and search H t in the form H t = Gt ◦ F t where the flow Gt has to be deduced. Differentiating this equality we find d t H = Gt ◦ F t ◦ f t + g t dt d d d = Gt ◦ F t + Gt ◦ F t = Gt ◦ F t + Gt ◦ F t ◦ f t . dt dt dt So,  −1  d t G = Gt ◦ F t ◦ f t ◦ F t = Gt ◦ Ad F t g t , dt  0 G = Id .

We thus obtained

→ G =− exp t

t

Ad F s g s ds

0

and the first form of variations formula → Ht = − exp

0

t

Ad F s g s ds ◦ F t .

(2.39)

We also obtain −1 −→ t H t = F t ◦ Ad F t exp Ad F s g s ds 0

and by (2.35) → exp H =F ◦− t

→ where Fst = − exp

t

t s

f τ dτ .

t 0

−1 → Ad F t ◦ F s g s ds = F t ◦ − exp

0

t

Fst ∗ g s ds

(2.40)

26


The second form of variations formula may be thus written − → exp

0

t

→ f s + g s ds = − exp

0

t

→ f s ds ◦ − exp

t 0

− → exp

s

ad f τ dτg s ds.

t

In the case when f, g are autonomous vector fields the formula becomes (compare with (2.38)): → et (f +g) = − exp

0

t

→ Ad esf g ds ◦ etf = etf ◦ − exp

t

Ad e(s−t)f g ds.

0

Elements of symplectic geometry. Hamiltonian formalism D EFINITION 2.1. A symplectic structure on a (necessarily odd dimensional) manifold N is a nondegenerate closed differential 2-form. A manifold with a symplectic structure ω is called a symplectic manifold Let M be a manifold and T ∗ M = y∈M Tq∗ M be the cotangent bundle. If (x1 , . . . , xn ) are local coordinates on M then if p ∈ Ty∗ M, p = ni=1 pi dxi , (p1 , . . . , pn , x1 , . . . , xn ) define the canonical local coordinates on T ∗ M. Define ω=

n

dpi ∧ dxi .

i=1

(2.41)

To see that the definition is independent of the local coordinates let π : T ∗ M → M be the canonical projection and the canonical 1-form on T ∗ M: ω1ξ (w) = ξ ◦ π∗ (w), If w ∈ T (T ∗ M) then w=

n

for w ∈ Tξ T ∗ M .

ξi

∂ ∂ + vi . ∂pi ∂xi

= 0 and π∗

i=1

Since π∗

∂ ∂pi

one finds that ω1ξ (w) =

n i=1

pi v i

∂ ∂xi

=

∂ ∂xi


27

so ω1 =

n

pi dxi

i=1

and ω = dω1 . It is easy to see now that ω is a symplectic structure on T ∗ M which becomes a symplectic manifold. Let now (N, ω) be a general symplectic manifold. Functions in C ∞ (N ) are called Hamiltonians. Let H be such a Hamiltonian. Then there exists a unique vector field on − → N denoted H such that − → → ω = ω ·, H = dH. −i− H

− → H is called the Hamiltonian vector field of H and the corresponding flow is the Hamiltonian flow. The Hamiltonian equation is d − → ξ(t) = H ξ(t) dt

(2.42)

and the Hamiltonian flow is t − → −→ t = exp H ds. 0

The Poisson bracket of the Hamiltonians α, β is defined as − → → − − → → {α, β} = L− α β = dβ( α ) = ω α , β = −{β, α}.

− → One may prove that (C ∞ (N ), {·, ·}) is a Lie algebra and the map H → H is a Lie alge∞ bra homomorphism from C (N ) to Vec(N ). Bilinearity and antisymmetry are immediate. −−−→ − → → Jacobi identity as well as the fact that {α, β} = [− α , β ] are easy to prove if in local coordinates ω has the canonic form (2.41). We conclude since, by Darboux theorem (see [3]), there exists indeed a symplectic atlas on N such that ω in local coordinates is in canonical form. In these coordinates n

∂H ∂ − → ∂H ∂ H = − ∂pi ∂xi ∂xi ∂pi i=1

and n ∂α ∂β ∂α ∂β {α, β} = − . ∂pi ∂xi ∂xi ∂pi i=1

28


Moreover, the Hamiltonian system (2.42) is written in the form (1.7). Now, if F ∈ Diff(N ) preserves the symplectic structure, that is F ∗ ω = ω, then − → −−→ Ad F H = F H . Indeed, −−→ ω ·, F H = d(F H ) = d(H ◦ F ) = H∗ ◦ F∗ = dH ◦ F∗ − → − → − → = ω F∗ ·, H = F ∗ ω ·, (F∗ )−1 H = ω ·, Ad F H .

Prime integrals of Hamiltonian systems are those which commute with the Hamiltonian. − → Indeed, consider the equation (2.42). Then α ∈ C ∞ (M) is a prime integral iff et H α = const − → which is equivalent, by differentiation, to H α = 0 or {H, α} = 0. We consider again the case of the symplectic manifold T ∗ M. Given a nonautonomous vector field f t ∈ Vec(M) we consider the Hamiltonian t # f (ξ ) = ξ, f t .

In canonical symplectic coordinates (pi , xi ), if f t = ni=1 fi (t, x) ∂x∂ i then (f t )# (ξ ) = n i=1 pi fi (t, x). Using the canonical coordinates it is easy to see that for f, g ∈ Vec(M)

f # , g # = [f, g]# .

For a nonautonomous vector field f t the Hamiltonian vector field on T ∗ M defined by −−t→# (f ) is named the Hamiltonian lift. It satisfies − −−→ # π∗ f t = f t .

We want to establish now the relation between the flows determined by f t , respectively by −−t→# → t f s ds. Then (F t )∗ ∈ Diff(T ∗ M). Let (f ) . Let Fτt = − exp τ τ d t ∗ F g = dt t=τ τ τ

−−→ P ROPOSITION 2.11. g t = −(f t )# and t ∗ −→ Fτ = exp

t

τ

− → # −− f s ds

(2.43)

P ROOF. First of all, since, in the exponential representation on T ∗ M, (Fτt+ε )∗ = (Ftt+ε )∗ ◦ (Fτt )∗ , it follows by differentiating with respect to ε in 0 that ∗ d t ∗ Fτ = g t ◦ Fτt dt


29

so t ∗ ←− Fτ = exp

t

g s ds.

τ

Since ∗ −1 π ◦ Fτt = Fτt ◦π

it follows by differentiation that π∗ g t = −f t .

(2.44)

On the other hand, the flow (Fτt )∗ preserves the 1-form ω1 and thus the symplectic form ω. By Cartan’s formula (2.3) 0 = Lg t ω1 = ig t ω + dω1 g t

which implies that

−→ −−− g t = ω1 g t

which means that the field g t is Hamiltonian. By (2.44) and observing that g t is linear homogeneous on the tangent space to the fibers, the first conclusion follows. Equality (2.43) is now immediate taking into account the relationship between the left and right chronological exponential.

3. The Pontriaghin maximum principle The Pontriaghin maximum principle, developed by L. Pontriaghin and his collaborators (see [30]), is a set of first order necessary conditions of optimality in optimal control problems. This is expressed in terms of the dual linearized state system and reduces the problem to solving a two point boundary problem for a differential system, which is in fact a Hamiltonian system, composed of the state equation and the dual equation.

3.1. The main theorem Throughout this section the following conditions will be assumed on the optimal control problem (1.14): (i) The functions L : [0, T ] × Rn × Rm → R;

f : [0, T ] × Rn × Rm → Rn

30


and Ly , fy are measurable in t, continuous in (y, u) and fy (t, y, u) + Ly (t, y, u) α(t, u),

∀t ∈ [0, T ], ∀u ∈ U (t).

(ii) For each t ∈ [0, T ], U (t) ⊂ Rm is closed and for each closed set D ⊂ Rm the set {t; D ∩ U (t) = ∅} is measurable. (iii) g ∈ C 1 (Rn × Rn ) and C is a closed convex subset of Rn × Rn . Here we have denoted by the same symbol · the norm in L(Rn , Rn ) and in Rn . Theorem 3.1 below is the celebrated Pontryagin’s maximum principle for problem (1.14). T HEOREM 3.1. Let (y ∗ , u∗ ) be an optimal pair in problem (1.14) such that α(t, u∗ ) ∈ L1 (0, T ). Then there exists p ∈ AC([0, T ]; Rn ) and a constant λ which is equal to 0 or 1 such that

and

p(t) + |λ| = 0,

∀t ∈ [0, T ]

p ′ = −fy∗ (t, y ∗ , u∗ )p + λLy (t, y ∗ , u∗ ), a.e. t ∈ [0, T ], p(0), −p(T ) ∈ λ∇g y ∗ (0), y ∗ (T ) + NC y ∗ (0), y ∗ (T ) , p(t), f t, y ∗ (t), u∗ (t) − λL t, y ∗ (t), u∗ (t) a.e. t ∈ [0, T ]. = max p(t), f t, y ∗ (t), u − λL t, y ∗ (t), u u∈U (t)

(3.1) (3.2)

(3.3)

If λ = 1, the problem is called normal otherwise it is abnormal. If C = {y0 } × Rn and g(y1 , y2 ) ≡ g1 (y2 ) this is the Bolza problem with initial condition y(0) = y0 and (3.2) reduces to p(T ) = −λ∇g1 y(T ) .

(3.4)

If C = {(y1 , y2 ); y1 = y2 } and g ≡ 0, this is the periodic optimal control problem and (3.2) has the form p(0) = p(T ).

(3.5)

The end point boundary conditions (3.2) are also called transversality conditions. An elementary approach to the maximum principle In order to understand better how the optimality system (3.1)–(3.3) appears, as well as the proof we give in the next section, we discuss first the special case where L(t, ·, ·), f (t, ·, ·) are smooth (of class C 1 for instance), g(y1 , y2 ) = g2 (y2 ) ∈ C 1 , C = {y0 } × Rn and U (t) ≡ U is a closed convex subset of Rm . We shall assume also fy (t, y ∗ , u∗ ) ∈ L∞ (0, T , R2n ), fu (t, y ∗ , u∗ ) ∈ L∞ (0, T , R2n ), where


31

(y ∗ , u∗ ) is an optimal pair. By optimality we have for λ ∈ (0, 1) and ∀v ∈ L2 (0, T ; Rm ), u∗ (t) + λv(t) ∈ U a.e. t ∈ (0, T )

T

0

L(t, y ∗ , u∗ ) dt + g2 y ∗ (T )

T

0

∗ ∗ L t, y u +λv , u∗ + λv dt + g2 y u +λv (T ) .

Here y v is the solution of the Cauchy problem y ′ = f (t, y, v), y(0) = y0 . Noticing that 1 u∗ +λv y (t) − y ∗ (t) λ→0 λ

z(t) = lim

is the solution to the system in variations

z′ = fy (t, y ∗ , u∗ )z + fu (t, y ∗ , u∗ )v, z(0) = 0,

t ∈ (0, T ),

(3.6)

we find that

0

T

Ly (t, y ∗ , u∗ ), z(t) + Lu (t, y ∗ , u∗ ), v(t) dt + ∇g2 y ∗ (T ) , z(T ) 0.

(3.7)

Next we define p the solution to the Cauchy problem

p ′ = −fy∗ (t, y ∗ , u∗ )p + Ly (t, y ∗ , u∗ ), p(T ) = −∇g2 y ∗ (T ) .

a.e. t ∈ (0, T ),

Multiplying the latter by z and integrating on (0, T ) we find by (3.6), (3.7) that

0

T

Lu (t, y ∗ , u∗ ) − fu (t, y ∗ , u∗ ), v(t) dt 0.

Equivalently,

0

T

Lu (t, y ∗ , u∗ ) − fu (t, y ∗ , u∗ ), w(t) − u∗ (t) dt 0

for all w ∈ L2 (0, T ; Rm ), w(t) ∈ U a.e. t ∈ (0, T ). This means (see (2.4)) that fu t, y ∗ (t), u∗ (t) − Lu t, y ∗ (t), u∗ (t) ∈ NU u∗ (t)

a.e. t ∈ (0, T ).

If f is linear in u and u → L(t, y, u) is convex the latter is equivalent with (3.3).

32


3.2. Proof of the maximum principle The main idea of proof given here is essentially due to F. Clarke [11]. We may assume that f (t, y ∗ , u) + Ly (t, y, u) + fy (t, y, u) β(t)

(3.8)

for a.e. t ∈ [0, T ] and all (y, u) ∈ Rn × U (t) where β ∈ L1 [0, T ]. This clearly implies that f (t, x, u) − f (t, y, u) β(t) x − y , f (t, y, u) β(t) y − y ∗ + 1

(3.9)

and so (standard existence theory) the state system (1.11) has a unique absolutely continuous solution y ∈ AC([0, T ]; Rn ) for each function u(t) ∈ U (t), ∀t ∈ (0, T ). This can be achieved by replacing U (t) by Un (t) = u ∈ U (t); f (t, y ∗ , u) − f (t, y ∗ , u∗ ) n, fy (t, y, u) − fy (t, y, u∗ ) n ∀y ∈ Rn .

Indeed, if (y ∗ , u∗ ) is optimal then clearly it is optimal in problem (1.14) with control constraints u(t) ∈ Un (t) a.e. t ∈ (0, T ) and so if the maximum principle (3.1)–(3.3) is true in this case, there are {pn , λn } satisfying the conditions of Theorem 3.1 where U is replaced by Un (t). By (3.1) and by assumption (ii) we see that ′ p (t) α0 t, u∗ (t) , n

a.e. t ∈ (0, T ).

If {|pn (0)|} is bounded this implies that {pn } is compact in C([0, T ]; Rn ) and so on a subsequence pn → p

in C [0, T ]; Rn

where p satisfies Eqs. (3.1)–(3.3). Otherwise, we set qn = pn (t)/ pn (0) and conclude as above that pn → p

in C [0, T ]; Rn

where p satisfies Eqs. (3.1)–(3.3) with λ = 0. Now we come back to the proof of the maximum principle. We set X = u : [0, T ] → Rm measurable; u(t) ∈ U (t), a.e. t ∈ [0, T ] .

(3.10)

It is easily seen that this is a complete metric space with the Ekeland distance d(u, v) = m t ∈ [0, T ]; u(t) = v(t) .

(3.11)


33

Let Y = X × Rn endowed with the standard product metric and consider the function ϕ : Y → R,

ϕ(u, y0 ) =

0

T

L t, y u (t), u(t) dt + g y0 , y u (T )

(3.12)

where

(y u )′ = f (t, y u , u) y u (0) = y0 .

a.e. in (0, T ),

We define the function ϕε (u, y0 ) =

1/2 + 2 + dC2 y0 , y u (T ) ϕ(u, y0 ) − ϕ u∗ , y ∗ (0) + ε

(3.13)

for all (u, y0 ) ∈ Y . Here dC is the distance to C. By Ekeland’s principle, Theorem 2.1, for each ε > 0 there exists (uε , y0ε ) ∈ Y such that ϕε (uε , y0ε ) ε,

and

√ d(uε , u∗ ) + y0ε − y ∗ (0) ε ϕε (uε , y0ε ) ϕε (u, y0 ) + ρ

√ ε d(uε , u) + y0ε − y0 ,

(3.14)

∀(u, y0 ) ∈ Y.

(3.15)

We take y0 = y0ε + ρz0 and set yε = y uε , yε (0) = y0ε with z0 = 1. In (3.15) we take the “spike” admissible control uρ (t) =

u(t), uε (t),

t ∈ [t0 − ρ, t0 ], t ∈ [0, T ] \ (t0 − ρ, t0 )

where t0 ∈ [0, T ] is arbitrary but fixed and u ∈ X. Then we have yρ (t) = y uρ (t) = yε (t) + ρzε (t) + o(ρ) where zε ∈ BV ([0, T ]; Rn ) is the solution to the equation in variations

 ′  zε = fy (t, yε , uε )zε a.e. t ∈ (0, t0 ) ∪ (t0 , T ), zε (0) = z0 ,  + zε (t0 ) − zε− (t0 ) = f t0 , yε (t0 ), u(t0 ) − f t0 , yε (t0 ), uε (t0 ) .

(Here BV ([0, T ]; Rn ) is the space of functions of bounded variation on [0, T ].) By (3.15) we have ρ √ ϕε (uρ , y0 ) − ϕε (uε , y0ε ) −2 ε ρ

(3.16)

34


ρ ((ϕ(uρ , y0 ) − ϕ(u∗ , y ∗ (0)) + ε)+ )2 1 = ρ ρ ϕε (uρ , y0 ) + ϕε (uε , y0ε ) ((ϕ(uε , y0ε ) − ϕ(u∗ , y ∗ (0)) + ε)+ )2 ρ ρ d 2 (y , yρ (T )) − dC2 (y0ε , yε (T )) + C 0 . ρ −

Letting ρ tend to zero, we obtain after some calculation that T ρ √ (ϕ(uε , y0 ) − ϕε (u∗ , y ∗ (0)) + ε)+ −2 ε Ly (t, yε , uε )zε dt ϕε (uε , y0ε ) 0 + ∇g y0ε , yε (T ) , z0 , zε (T ) + L t0 , yε (t0 ), u(t0 ) − L t0 , yε (t0 ), uε (t0 ) +

(∇dC (y0ε , yε (T )), (z0 , zε (T ))) ε dC y0 , yε (T ) . ε ϕε (uε , y0 )

Here t0 is a Lebesgue point for L(t, yε (t), uε (t)) and L(t, yε (t), u(t)). We remind that s is a Lebesgue point for a function v : I ⊂ R → R if 1 lim t→s t − s

s

v(τ ) − v(s) dτ = 0

t

(3.17)

and if v ∈ L1loc then almost all points s ∈ I are Lebesgue points of v. We have

We set

∇dC y ε , yε (T ) = 1 if (y0ε , yε (T )) ∈ / C, 0 ε ε ε dC y0 , yε (T ) ∇dC y0 , yε (T ) = 0 if (y0 , yε (T )) ∈ C.  (ϕ(uε , y0ε ) − ϕ(u∗ , y ∗ (0)) + ε)+   λ = ,  ε  ϕε (uε , y0ε )  dC (y0ε , yε (T ))   ∇dC y0ε , yε (T ) .  µε = ε ϕε (uε , y0 )

This yields

λε

0

T

Ly (t, yε , uε )zε dt + ∇g y0ε , yε (T ) , z0 , zε (T ) + L t0 , yε (t0 ), u(t0 )

√ − L t0 , yε (t0 ), uε (t0 ) + µε , z0 , zε (T ) −2 ε,

(3.18)


35

where λε > 0 and λ2ε + µε 2 = 1,

∀ε > 0.

(3.19)

Let pε ∈ AC([0, T ]; Rn ) be the solution to the backward differential system

pε′ (t) = −fy∗ (t, yε , uε )pε + λε Ly (t, yε , uε ), pε (T ) = −P λε ∇g y0ε , yε (T ) + µε

t ∈ [0, T ],

(3.20)

where P is the projection P (y1 , y2 ) = y2 . Substituting into (3.18), we get (via (3.16)) λε

T

Ly (t, yε , uε )zε dt

0

=−

0

T

pε (t), zε′ (t) − fy (t, yε , uε )zε dt

− pε (t0 ), f t0 , yε (t0 ), u(t0 ) − f t0 , yε (t0 ), uε (t0 ) − pε (0), z0 − P λε ∇g y0ε , yε (T ) + µε , zε (T ) .

Substituting into (3.18) we obtain

√ −2 ε λε L t0 , yε (t0 ), u(t0 ) − L t0 , yε (t0 ), uε (t0 ) − pε (t0 ), f t0 , yε (t0 ), u(t0 ) − f t0 , yε (t0 ), uε (t0 ) + λε ∇g y0ε , yε (T ) , z0 , zε (T ) + µε , z0 , zε (T ) − pε (0), z0 − P λε ∇g y0ε , yε (T ) + µε , zε (T )

(3.21)

for all z0 ∈ Rn and u(t0 ) ∈ U (T0 ). This yields

√ −2 ε λε L t0 , yε (t0 ), u(t0 ) − L t0 , yε (t0 ), uε (t0 ) − pε (t0 ), f t0 , yε (t0 ), u(t0 ) − f t0 , yε (t0 ), uε (t0 ) − pε (0), −(I − P ) λε ∇g y0ε , yε (T ) + µε , z0 , zε (T ) .

For z0 = 0 we get

√ 2 ε − λε L t0 , yε (t0 ), uε (t0 ) + f t0 , yε (t0 ), uε (t0 ) , pε (t0 ) max −λε L t0 , yε (t0 ), u + f t0 , yε (t0 ), u , pε (t0 ) u∈U (t0 )

(3.22)

and for u = uε we see by (3.21) that

pε (0), −pε (T ) = λε ∇g yε (0), yε (T ) + µε + ηε

(3.23)

36


√ where ηε 2 ε. Then, on a subsequence, again denoted ε, we have λε → λ, µε → µ, pε → p

in C [0, T ]; Rn (by Arzela theorem), y0ε → y ∗ (0) in C [0, T ]; Rn , m t ∈ [0, T ]; uε (t) = u∗ (t) → 0.

(3.24)

Recalling that by (3.9) f (t, yε , uε ) β(t) yε − y ∗ + 1

we infer that {yε } is compact in C([0, T ]; Rn ) and {yε′ } is weakly compact in L1 (0, T ; Rn ). We have t f s, yε (s), uε (s) ds (3.25) yε (t) = yε (0) + 0

and

f t, yε (t), uε (t) − f t, y ∗ (t), u∗ (t) f t, yε (t), uε (t) − f t, y ∗ (t), uε (t) + f t, y ∗ (t), uε (t) − f t, y ∗ (t), u∗ (t) β(t)yε (t) − y ∗ (t) + f t, y ∗ (t), uε (t) − f t, y ∗ (t), u∗ (t) .

(3.26)

On the other hand, since f is continuous in (y, u) we have ∗ f t, y (t), uε (t) − f t, y ∗ (t), u∗ (t) → 0 a.e. in (0, T ).

Since

∗ f t, y (t), uε (t) β(t)

a.e. t ∈ [0, T ]

we infer by (3.26) and the Lebesgue dominated convergence theorem that f (t, yε , uε ) → f (t, y ∗ , u∗ )

in L1 (0, T ).

Thus, by (3.25) we conclude that yε → y ∗ in C [0, T ]; Rn .

By (3.23) we see that p(0), −p(T ) = λ∇g y ∗ (0), y ∗ (T ) + µ

(3.27)


37

where µ ∈ NC (y ∗ (0), y ∗ (T )). Indeed, since C is convex, dC2 is convex and we have that µε , yε (0), yε (T ) − w 2 dC2 yε (0), yε (T ) − dC2 (w) ,

∀w ∈ C

and passing to the limit we obtain

Since

∗ µ, y (0), y ∗ (T ) − w 0,

∀w ∈ C.

fy∗ t, yε (t), uε (t) → fy∗ t, y ∗ (t), u∗ (t) Ly t, yε (t), uε (t) → Ly t, y ∗ (t), u∗ (t)

a.e. t ∈ (0, T ),

a.e. t ∈ (0, T )

by (3.8) and (3.20) it follows that

p ′ = −fy∗ (t, y ∗ , u∗ )p + λLy (t, y ∗ , u∗ )

a.e. t ∈ (0, T )

(3.28)

and by (3.22) −λL t0 , y ∗ (t0 ), u∗ (t0 ) + f t0 , y ∗ (t0 ), u∗ (t0 ) , p(t0 ) = max −λL t0 , y ∗ (t0 ), u + f t0 , y ∗ (t0 ), u , p(t0 ) u∈U (t0 )

a.e. t0 ∈ [0, T ]. (3.29)

Recall also that λ 0 and |λ| + µ = 1.

(3.30)

If λ > 0, then replacing p by p/λ we get (3.1)–(3.3) with λ = 1. If λ = 0, then by (3.30) we see that µ = 0 and so p(0) + p(T ) = 0.

Clearly, this implies that

p(t) = 0 ∀t ∈ [0, T ].

The proof of the theorem is complete. R EMARK 3.1. The problem (1.14) with state constraints y(t) ∈ K ⊂ Rm

∀t ∈ [0, T ]

(3.31)

38


where K is a closed convex subset of Rn can be treated similarly. In this case we take ϕε (u, y0 ) =

+ 2 + dC2 y0 , y u (T ) ϕ(u, y0 ) − ϕ u∗ , y ∗ (0) + ε +

T

0

2 dK y(t) dt

1/2

.

We propose to the reader to obtain a optimality theorem of the type of Theorem 3.1 in the present situation. R EMARK 3.2. In Theorem 3.1 the condition that C is convex can be removed. (See [4] for a proof in this general case.)

3.3. Convex optimal control problems We shall study here the problem (P): min

0

T

L t, y(t), u(t) dt + g y(0), y(T ) ; y(0), y(T ) ∈ C

(3.32)

subject to y ′ (t) = A(t)y(t) + B(t)u(t) + f0 (t), u(t) ∈ U (t)

a.e. t ∈ [0, T ]

u ∈ L1 0, T ; Rm

where L is convex in (y, u), measurable in t, g ∈ C 1 (Rn × Rn ) is convex, C is closed and convex, A(t) ∈ L(Rn × Rn ), B(t) ∈ L(Rm , Rn ), A(·), B(·), f0 (·) are integrable and U (t) ⊂ Rm is closed and convex. We have by Theorem 3.1 the following sharpening of the maximum principle in this case: C OROLLARY 3.1. If (y ∗ , u∗ ) is optimal and u∗ ∈ L1 (0, T ), then there exists p ∈ AC([0, T ]; Rn ), λ ∈ {0, 1} such that λ + |p(t)| = 0 and

p ′ = −A∗ (t)p + λLy t, y ∗ (t), u∗ (t) a.e. t ∈ (0, T ), p(0), −p(T ) − λ∇g y ∗ (0), y ∗ (T ) ∈ NC y ∗ (0), y ∗ (T ) ,

B ∗ p(t) ∈ λLu t, y ∗ (t), u∗ (t) + NU (t) u∗ (t)

where ∂L = (∂y L, ∂u L) is the subdifferential of L.

a.e. t ∈ (0, T )

(3.33)

(3.34)


39

In fact, (3.34) comes from the maximum principle λL t, y ∗ (t), u∗ (t) − f t, y ∗ (t), u∗ (t) , p(t) = max λL t, y ∗ (t), u − f t, y ∗ (t), u , p(t) u∈U (t)

(3.35)

where f (t, y, u) ≡ A(t)y + B(t)u + f0 (t) and, because λL(t, y ∗ , ·) is convex, the maximum in (3.35) is attained for u∗ satisfying (3.34). C OROLLARY 3.2. Assume that C = C1 × C2 and there exists (y, u) admissible such that y(T ) ∈ int C2 or y(0) ∈ int C1 . Then the problem is normal. P ROOF. Assume that λ = 0 and y(T ) ∈ int C2 . Then |p(t)| = 0 and

We have

p ′ = −A∗ (t)p a.e. t ∈ [0, T ], p(0) ∈ NC1 y ∗ (0) , −p(T ) ∈ NC2 y ∗ (T ) ,

B ∗ (t)p(t) ∈ NU (t) u∗ (t) ,

a.e. t ∈ [0, T ].

y ′ = A(t)y + B(t) + f0 (t)u y(T ) ∈ int C2 .

a.e. t ∈ [0, T ],

(3.36) (3.37)

(3.38)

This yields (y ∗ − y)′ = A(t)(y − y ∗ ) + B(t)(u − u∗ )

a.e. t ∈ [0, T ]

and − p(T ), y ∗ (T ) − ρw − y(T ) 0,

∀|w| = 1.

Then using (3.37) we get

ρ p(T ) = − p(T ), y ∗ (T ) − y(T ) ∗ = − p(0), y (0) − y0 +

0

T

u − u∗ , B ∗ (t)p(t) dt 0

(because p(0) ∈ NC1 (y ∗ (0))). Hence p(T ) = 0, contradiction. The corollary is proved. The case y(0) ∈ int C1 can be treated similarly. C OROLLARY 3.3. Under assumption of Corollary 3.2, the system (3.33)–(3.34) is also sufficient for optimality.

40


P ROOF. As seen earlier, λ = 1. Let (y, u) be an arbitrary pair such that y ′ = A(t)y + B(t)u + f0 (t) y(0), y(t) ∈ C1 × C2 .

a.e. t ∈ [0, T ], u(t) ∈ U (t),

We have (by convexity of C)

L(t, y ∗ , u∗ ) L(t, y, u) + Ly (t, y ∗ , u∗ ), y ∗ − y + Lu (t, y ∗ , u∗ ), u∗ − u , g y ∗ (0), y ∗ (T ) g y(0), y(T ) + y ∗ (0) − y(0), y ∗ (T ) − y(T ) × ∇g y ∗ (0), y ∗ (T ) .

Integrating on [0, T ] and using (3.33) and (3.34), we see that

0

as claimed.

T

L(t, y ∗ , u∗ ) dt + g y ∗ (0), y ∗ (T )

0

T

L(t, y, u) dt + g y(0), y(T )

We shall prove now a maximum principle for the convex control problem of Bolza under more general conditions on L. We shall assume that 1. L(t, ·, ·) : Rn × Rn → R is convex, continuous and the Hamiltonian function H (t, x, p) = sup (p, u) − L(t, x, u): u ∈ U (t) is finite and summable in t for each (x, p) ∈ Rn × Rm . U (t) ⊂ Rm is closed and convex for each t. Moreover, assumption (ii) in Section 3.1 holds. 2. g ∈ C(Rn × Rn ) is convex and C = C1 × C2 where C1 , C2 are convex and closed. 3. f (t, y, u) = A(t)y + B(t)u + f0 (t) where A(t) ∈ L1 (0, T ; Rn × Rn ), B(t) ∈ L1 (0, T ; Rm × Rn ), f0 ∈ L1 (0, T ). 4. There is (y, u) admissible such that either y(0) ∈ int C1 or y(T ) ∈ int C2 .

T HEOREM 3.2. Assume that (y ∗ , u∗ ) ∈ C([0, T ]; Rn ) × L2 ([0, T ]; Rn ) is optimal. Then there exists p ∈ AC([0, T ]; Rn ) such that p ′ + A∗ (t)p ∈ ∂u L t, y ∗ (t), u∗ (t) a.e. t ∈ (0, T ), (3.39) ∗ ∗ ∗ ∗ (3.40) p(0), −p(T ) ∈ ∂g y (0), y (T ) + NC y (0), y (T ) , B ∗ p ∈ ∂u L t, y ∗ (t), u∗ (t) + NU (t) u∗ (t) a.e. t ∈ (0, T ). (3.41)

Moreover, conditions (3.39)–(3.41) are also sufficient for optimality. P ROOF. For λ > 0 consider the problem min

T 0

1 Lλ (t, y, u) dt + gλ y(0), yλ (T ) + 2

0

u(t) − u∗ (t)2 dt

T


41

2 1 1 2 dC1 yλ (0) + dC2 2 yλ (T ) , u(t) ∈ U (t) (Pλ ) + y(0) − y ∗ (0) + 2 2λ

subject to

y ′ = A(t)y + B(t)u + f0 (t)

a.e. t ∈ (0, T ).

Problem (Pλ ) has a unique solution (yλ , uλ ). L EMMA 3.1. For λ → 0 we have yλ → y ∗ in C [0, T ]; Rn , uλ → u∗ in L2 [0, T ]; Rn .

(3.42) (3.43)

P ROOF. Recall that (see Section 2.1)

|y − z|2 |u − v|2 + + L(t, z, v) , Lλ (t, y, u) = inf (z,v) 2λ 2λ |y1 − z1 |2 |y2 − z2 |2 + + g(z1 , z2 ) gλ (y1 , y2 ) = inf (z1 ,z2 ) 2λ 2λ

and dC1 (dC2 ) is the distance to C1 (and C2 respectively). We have

1 T uλ (t) − u∗ (t)2 dt Lλ t, yλ (t), uλ (t) dt + gλ yλ (0), yλ (T ) + 2 0 0 2 1 2 1 dC1 yλ (0) + dC2 2 yλ (T ) + yλ (0) − y ∗ (0) + 2 2λ T ∗ L t, y (t), u∗ (t) dt + g y ∗ (0), y ∗ (T ) (3.44) T

0

because Lλ L, gλ g. Let for λ → 0,

weakly in L2 0, T ; Rm , strongly in C 0, T ; Rn .

uλ → u¯ yλ → y¯

Then by the Fatou lemma lim inf λ→0

0

T

Lλ t, yλ (t), uλ (t) dt

0

T

L t, y(t), ¯ u(t) ¯ dt

and by the lower semicontinuity of g lim inf gλ λ (0), yλ (T ) g y(0), ¯ u(T ¯ ) . λ→0

42


Then by (3.44) we deduce that yλ (0) → y ∗ (0),

uλ → u∗

in L2 0, T ; Rm .

Now the maximum principle in (Pλ ) yields ((Pλ ) is smooth and so Corollary 3.2 applies)  ′ pλ + A∗ (t)pλ = ∇y Lλ (t, yλ , uλ ) a.e. t ∈ (0, T ),     ∗    pλ (0), −pλ (T ) = ∇gλ yλ (0), yλ (T ) + yλ (0) − y (0), 0 1   + ∇dC2 1 yλ (0) , ∇dC2 2 yλ (T ) ,   λ    ∗ B pλ = ∂u Lλ (yλ , uλ ) + uλ − u∗ + NU (t) uλ (t) a.e. t ∈ (0, T ).

(3.45)

We shall prove now that {pλ (t)} is bounded in Rn . We shall use the same argument as in the proof of Corollary 3.2. Indeed, we have

because

Hence

pλ (T ), yλ (T ) − y(0) − ρw ∇2 gλ yλ (0), yλ (T ) , yλ (T ) − y(0) M 1 2 1 ∇d (y) = I − (I + λ∂IC2 )−1 (y). 2 C2 λ ρ pλ (T ) pλ (T ), yλ (T ) − y(0) .

On the other hand, by (3.45), we have

− pλ (0), yλ (0) − y(0) + pλ (T ), yλ (T ) − y(T ) T T = B(uλ − u), pλ dt ∇y Lλ (t, yλ , uλ ), yλ − y dt + 0

0

where y ′ = Ay + Bu + f0 . Then again by (3.45) we see that pλ (T ), yλ (T ) − y(T )

1 2 dC1 yλ (0) − dC2 2 y(0) . pλ (0), yλ (0) − y(0) + 2λ

Substituting the latter in the previous inequalities we see that {pλ (T )} is bounded in Rn .


43

On the other hand, the Hamiltonian function H (t, y, p) is concave in y and convex in p. By assumption 1, it follows that for each y0 ∈ Rn there is a neighborhood V(y0 ) of y0 and α ∈ L1 (0, T ) such that −H (t, y, 0) α(t),

∀y ∈ V(y0 ), t ∈ (0, T ).

Indeed, we may choose V(y0 ) a simplex generated by {y1 , . . . , yN +1 }. Then −H (t, y, 0) −

i

λi H (t, yi , 0) =: α(t).

By the inequality H (t, y, 0) − H (t, y, ρw) ρ(v, w),

∀v ∈ ∂p H (t, y, 0)

it follows that sup v ; v ∈ ∂p H (t, y, 0) β(t),

a.e. t ∈ (0, T )

(3.46)

where β ∈ L1 (0, T ). We have

Lλ t, y ∗ (t) + ρw, v0 (t) L t, y ∗ (t) + ρw, v0 (t) α(t)

for all |w| = 1 and v0 (t) ∈ ∂p H (t, y ∗ (t) + ρw, 0). Because

and

L(t, y, v0 ) = sup (v0 , p) − H (t, y, p) L(t, y, v0 ) + H (t, y, 0) = 0.

We have, by (3.45) and the convexity of Lλ (t, y, ·), that ′ pλ + A∗ pλ , yλ − y ∗ − ρw + B ∗ pλ + uλ − u∗ , uλ − v0 Lλ (t, yλ , uλ ) − Lλ (t, y ∗ + ρw, v0 )

a.e. t ∈ (0, T ).

Hence ρ pλ′ + A∗ pλ α(t) − Lλ (t, yλ , uλ ) + pλ′ + A∗ pλ , yλ − y + B ∗ pλ , uλ − v0 + (uλ − u∗ , uλ − v0 ).

This yields (Lλ is bounded from below by an affine function)

(3.47)

44


ρ

0

p ′ + A∗ pλ dt C + pλ (T ), yλ (T ) − y ∗ (T ) λ

T

− pλ (0), yλ (0) − y ∗ (0) + C pλ (t)uλ (t) − v0 (t) + |uλ − u∗ |2 + |uλ − u∗ ||uλ − v0 |

Since

T 0

a.e. t ∈ (0, T ).

|uλ |2 dt and |pλ (0)|, |pλ (T )| are bounded it follows by Gronwall’s lemma that |pλ (t)| C, ∀t ∈ [0, T ], T ′ p (t) + A∗ pλ (t) dt C. λ 0

As a matter of fact, by (3.47) we see that {pλ′ } is weakly compact in L1 (0, T ; Rn ) (the Dunford–Pettis theorem). Then on a subsequence, again denoted λ, we have pλ (t) → p(t)

pλ′

→ p′

uniformly on [0, T ], weakly in L1 0, T ; Rn .

(3.48)

Moreover, letting λ → 0 into (see the second equation in (3.45)) pλ (T ), yλ (0) − ξ − pλ (T ), yλ (T ) − η

1 gλ yλ (0), yλ (T ) − gλ (ξ, η) + dC2 1 yλ (0) + dC2 2 yλ (T ) λ + yλ (0) − y ∗ (0), yλ (0) − ξ , ∀(ξ, η) ∈ C

we see that

p(0), yλ (0) − ξ − p(T ), y ∗ (T ) − η g y ∗ (0), y ∗ (T ) − g(ξ, η), ∀(ξ, η) ∈ C.

Then letting λ → 0 we see that the transversality condition (3.40) holds. Next, we let λ → 0 into the inequality (see (3.45))

0

T

pλ′

∗

+ A pλ , yλ − y dt +

T

1 Lλ t, yλ , uλ dt + 2 0 T 1 − |u − u∗ |2 dt. 2 0

0

0

T

T

B ∗ pλ , uλ − u dt ∗ 2

|uλ − u | dt −

0

T

Lλ (t, y, u) dt


45

By weak lower semicontinuity of the convex integrand we know that (see Lemma 3.1) lim inf λ→0

T

Lλ (t, yλ , uλ ) dt

0

T

L(t, y ∗ , u∗ ) dt.

0

Hence

0

T

p ′ + A∗ p, y ∗ − y dt +

0

T

L(t, y ∗ , u∗ ) dt −

T

0

T

B ∗ p, u∗ − u dt

L(t, y, u) dt,

0

∀(y, u) ∈ L∞ 0, T ; Rn × L2 0, T ; Rm .

The latter implies that

p ′ (t) + A∗ (t)p(t) ∈ ∂p L t, y ∗ (t), u∗ (t) B ∗ (t)p(t) ∈ ∂u L t, y ∗ (t), u∗ (t) + NU (t) u∗ (t)

a.e. t ∈ (0, T ), a.e. t ∈ (0, T )

as claimed. The sufficiency of conditions (3.39)–(3.41) for optimality is immediate. It relies on the obvious inequalities L(t, y ∗ , u∗ ) L(t, y, u) + Ly (t, y ∗ , u∗ ), y ∗ − y + Lu (t, y ∗ , u∗ ) + η, u∗ − u a.e. t ∈ (0, T ), η ∈ NU (t) u∗ (t)

where (y, u) is any pair of functions such that u(t) ∈ U (t). If we take (y, u) such that y(0) ∈ C1 and y(T ) ∈ C2 y ′ = A(t)y + B(t)u + f0 (t) and we integrate on (0, T ) we get by (3.40)–(3.41)

0

T

∗

∗

L(t, y , u ) dt

0

T

L(t, y, u) dt + p(T ), y ∗ (T ) − y(T )

− p(0), y ∗ (0) − y(0) T L(t, y, u) dt − g y ∗ (0), y ∗ (T ) + g y(0), y(T ) . 0

Hence (y ∗ , u∗ ) is optimal in problem (Pλ ).

46


The dual problem Define the functions M(t, q, w) = sup (q, v) + (w, y) − L(t, y, v); v ∈ U (t) , m(p1 , p2 ) = sup (p1 , x1 ) − (p2 , x2 ) − g(x1 , x2 ); x1 ∈ C1 , x2 ∈ C2 .

(3.49)

The problem

min

T 0

M t, B ∗ (t)p, w(t) dt +

0

T

f0 (t), p(t) dt

+ m p(0), p(T ) ; p ′ + A∗ (t)p = w a.e. in (0, T )

(P∗ )

is called the dual of (P). We have T HEOREM 3.3. Under assumptions of Theorem 3.2 the pair (y ∗ , u∗ ) is optimal in problem (P) if and only if (P∗ ) has a solution (p ∗ , w ∗ ). We have inf P + inf P∗ = 0.

(3.50)

The proof is immediate. It relies on the conjugacy relationship between L and M. It turns out that in certain situations the dual problem (P∗ ) is simpler than the primal problem (P). In particular, control constraints u(t) ∈ U (t) disappear in the dual problem. Let us illustrate this on the following simple example: T 1 min

y(t) 2 dt; y ′ (t) = A(t)y(t) + u(t), y(0) = y0 , 2 0 y(T ) 1, u(t) ρ a.e. t ∈ (0, T )

where · is the Euclidean norm. In this case

1 M(t, q, w) = w 2 + ρ q ∀(q, w) ∈ Rn × Rn , 2 m(p1 , p2 ) = (p1 , y0 ) − p2 ∀(p1 , p2 ) ∈ Rn × Rn and so the dual control problem (P∗ ) is min

T

1 2 ρ p(t) + w(t) dt + p(0), y0 + p(T ); 2 0 p ′ + A∗ (t)p = w a.e. in (0, T ) .


47

Comments The results presented above are essentially due to R.T. Rockafellar (see [32]). In infinite dimensional spaces such results were established in [6]. 3.4. Examples 3.4.1. The optimal control of the prey–predator system We shall treat here some specific problems from different areas of interest. Consider the Volterra prey–predator system  ′   x (t) = x(t)λ1 − µ1 u(t)y(t) , t ∈ [0, T ], (3.51) y ′ (t) = y(t) −λ2 + µ2 u(t)x(t) , t ∈ [0, T ],   x(0) = x0 , y(0) = y0 , x0 , y0 > 0 where x is the prey, y the predator and 0 u(t) 1 is the segregation rate; λi , µi are positive constants. Consider the optimal control problem (see [4,37]): min − x(T ) + y(T ) ; 0 u 1 . (3.52) This is a Bolza optimal control problem where L ≡ 0,

g(x, y) = −(x + y),

U = {u ∈ R; 0 u 1}, x(λ1 − µ1 uy) f (x, y, u) = . y(−λ2 + µ2 ux) The maximum principle (see Theorem 3.1) yields   p1′ = −(λ1 − µ1 u∗ y ∗ )p1 − µ2 u∗ y ∗ p2 , t ∈ [0, T ], (3.53) p ′ = µ1 u∗ x ∗ p1 − (−λ2 + µ2 u∗ x ∗ )p2 , t ∈ [0, T ],  2 p1 (T ) = 1, p2 (T ) = 1, u∗ (t) = argmax x ∗ (t) λ1 − µ1 uy ∗ (t) p1 (t) + y ∗ (t) −λ2 + µ2 ux ∗ (t) p2 (t) u∈U

a.e. t ∈ [0, T ].

(3.54)

Equivalently ∗

u (t) =

0 if µ2 p2 (t) − µ1 p1 (t) < 0, 1 if µ2 p2 (t) − µ1 p1 (t) > 0.

(3.55)

(Since x0 , y0 > 0, we have x ∗ (t) > 0, y ∗ (t) > 0.) We shall discuss the form of the optimal control according to the sign of µ2 − µ1 . We note first that always u∗ is a bang–bang controller because the set of zeros of the function µ2 p2 − µ1 p1 consists of a finite number of points.

48


1. µ2 − µ1 < 0. In this case (µ2 p2 − µ1 p1 )(T ) = µ2 − µ1 < 0.

(3.56)

Hence µ 2 p2 − µ 1 p1 < 0 in a maximal interval [T − δ, T ]. On this interval we have by (3.56) that u∗ (t) = 0 and so  ′  p1 = −λ1 p, t ∈ (T − δ, T ), p ′ = λ2 p2 , t ∈ (T − δ, T ),  2 p1 (T ) = p2 (T ) = 1.

Hence

p1 (t) = eλ1 (T −t) ,

p2 (t) = eλ2 (t−T )

on [T − δ, T ].

Since the function µ2 eλ2 (t−T ) − µ1 e−λ1 (T −t) is increasing, it follows that (T − δ, T ) = (0, T ). In other words, in this case u∗ (t) = 0, ∀t ∈ (0, T ). 2. µ2 − µ1 > 0. Then µ2 p2 (t) − µ1 p1 (t) > 0 for t ∈ [T − ε, T ] and u∗ (t) = 0 for t ∈ [T − ε, T ]. (We may assume that t ∈ [T − ε, T ] is maximal with this property.) Let us prove that t1 = T − ε is a switching point for u∗ , i.e., µ2 p2 (t) − µ1 p1 (t) < 0 for 0 t T − ε. We have on (T − ε, T )

p1′ = −p1 (λ1 − µ1 y ∗ ) − µ2 y ∗ p2 , p2′ = −p2 (µ2 x ∗ − λ2 ) + µ1 x ∗ p1

t ∈ (T − ε, T ),

p1′ = −λ1 p1 + y ∗ (µ1 p1 − µ2 p2 ), p2′ = λ2 p2 + x ∗ (µ1 p1 − µ2 p2 ),

t ∈ (t1 , T ), t ∈ (t1 , T ).

i.e.,

(3.57)


49

Hence p1 (t) eλ1 (T −t) 1,

p1 (t1 ) =

µ2 µ2 p2 (t1 ) > 0. µ1 µ1

Note that µ1 p1 (t) − µ2 p2 (t) = ϕ(t) satisfies the equation ϕ ′ (t) = u∗ ϕ(t)(µ2 x ∗ − µ1 y ∗ ) − λ2 µ2 p2 − λ1 µ1 p1 ,

t ∈ (0, t1 ).

Hence t1

ϕ(t) = Ce t +

t

u∗ (µ2 x ∗ −µ1 y ∗ ) ds

t1 s

e

t

u∗ (µ2 x ∗ −µ1 y ∗ ) dr

(λ2 µ2 p2 + λ1 µ1 p1 ) ds

for t ∈ (0, t1 ).

Since ϕ(t1 ) = 0 we see that C = 0 and λ2 µ2 p2 (t1 ) + λ1 µ1 p1 (t1 ) λ2 µ2 + λ1 µ1 > 0 we conclude that ϕ(t) > 0 in a left neighborhood of t1 . Hence u∗ (t) = 0

for t ∈ (t1 − ε, t1 ) = (t2 , t1 ).

But as seen above, µ2 p2 − µ1 p1 is increasing on (t2 , t1 ) and so µ2 p2 (t) − µ1 p1 (t) < 0 for all t < t1 . Hence t1 = 0 and so ∗

u (t) =

1 for t1 < t T , 0 for 0 t < t1

(3.58)

where the switching point t1 can be computed from the equation µ2 p2 (t) − µ1 p1 (t) = 0. 3. µ2 − µ1 = 0. In this case it follows that u∗ (t) = 0 for all t ∈ (0, T ). 3.4.2. Periodic solutions to Hamiltonian systems

y ′ (t) = ∂p H y(t), p(t) + f1 (t), p ′ (t) = −∂y H y(t), p(t) + f2 (t),

Consider the Hamiltonian system t ∈ (0, T ),

t ∈ (0, T )

(3.59)

50


with periodic conditions y(0) = y(T ),

p(0) = p(T ).

(3.60)

Assumptions: 1. H : Rn × Rn → R is convex, of class C 1 and γ1 |y|2 + γ2 |p|2 + C1 H (y, p)
0. 2. f1 , f2 ∈ L2 (0, T ; Rn ). A special case of (3.59) is f1 = 0, H (y, p) = g(y) + 12 |p|2 . In this case, (3.59) reduces y ′ = p,

p ′ = −g ′ (y) + f2 (t)

i.e., y ′′ + g ′ (y) = f2 (t),

y(0) = y(t),

y ′ (0) = y ′ (T ).

Following Clarke and Ekeland [13], we may reduce problem (3.59), (3.60) to the optimal control problem min

0

subject to

T

G v(t) − f2 (t), u(t) − f1 (t) − y(t), v(t) dt

y ′ (t) = u(t), y(0) = y(T ),

z′ (t) = −v(t) a.e. t ∈ (0, T ), z(0) = z(T )

(3.61)

(3.62)

where G = H ∗ is the conjugate of H , i.e., G(q1 , q2 ) = sup (y, p1 ) + (p, q2 ) − H (y, p) . (y,p)

If (y ∗ , z∗ , u∗ , v ∗ ) is optimal the maximum principle yields (see Theorem 3.1)  ′ ∗  q1 (t) = −λv (t) ′ q (t) = 0  2 q1 (0) = q1 (T ),

a.e. t ∈ (0, T ), a.e. t ∈ (0, T ),

u∗ (t), v ∗ (t) = argmax u, q1 (t) − v, q2 (t) {u,v}

− λG v − f2 (t), u − f1 (t) + λ y ∗ (t), v .

(3.63)

(3.64)


51

Clearly, λ = 1 because otherwise (i.e. if λ = 0), q1 ≡ q2 ≡ 0 which contradicts (3.64). By (3.62)–(3.64) we have q2 ≡ C2 , q1 − z∗ ≡ C1 and by (3.64) we see that ∗ y (t) − q2 (t), q1 (t) ∈ ∂G v ∗ (t) − f2 (t), u∗ (t) − f1 (t) a.e. t ∈ [0, T ]. Since (∂G)−1 = ∂H we get (see Proposition 2.4) ∗ v (t) − f2 (t), u∗ (t) − f1 (t) ∈ ∂H y ∗ (t) − C2 , z∗ (t) + C1 . We set

y¯ = y ∗ (t) − C2 ,

p = z∗ (t) + C1 .

(3.65)

We have (see (3.63))  ′ ¯ p) + f1 (t) a.e. t ∈ (0, T ),  y¯ ∈ ∂p H (y, ′ p ∈ −∂y H (y, ¯ p) + f2 (t) a.e. t ∈ (0, T ),  y(0) ¯ = y(T ¯ ), p(0) = p(T )

i.e., (y, ¯ p) is a solution of (3.59). We note also that, by assumption 1, we have G(q1 , q2 ) sup (y, p1 ) + (p, q2 ) − γ1 |y|2 − γ2 |p|2 − C1 < ∞, {y,p}

∀(q1 , q2 ) ∈ Rn × Rn

i.e., G is continuous on Rn × Rn . To conclude the proof, it remains to show that problem (3.61) has at least one solution. Let {yn , zn , un , vn } be such that yn′ = un , zn′ = −vn , yn (0) = yn (T ), z(0) = zn (T ), T T 1 d G(vn − f2 , un − f1 ) dt − (yn , vn ) dt d + . n 0 0

(3.66)

where d is the infimum in (3.61). By definition of G and by assumption 1, we have G(vn − f2 , un − f1 ) − (yn , un )

(y, vn − f2 ) + (p, un − f1 ) − (yn , vn ) − ω |y|2 + |p|2 ∀(y, p) ∈ Rn × Rn

where ω
0] > 0,

y ′′ + uy = 0, y ′ (0) = y ′ (1) = 0 has at least one nontrivial solution}.

T HEOREM 3.5. Assume that B > π 2 . Then every optimal pair (y ∗ , u∗ ) satisfies ∗

u (t) =

B, 0 t t1 , 0, t1 < t < t2 , B, t2 t < 1.

(3.70)

P ROOF. The state system is y ′ = z,

z′ = −uy,

z(0) = z(1) = 0.

By the maximum principle, Theorem 3.1, there exists λ = 0, 1 and (p1 , p2 ) such that p1′ = up2 ,

p2′ (0) = 0,

p2′ = −p1

p2′ (1) = 0,

a.e. t ∈ [0, 1],

u∗ (t) = argmax −uy ∗ (t)p2 (t) − λu a.e. t ∈ [0, T ]. u∈U

(3.71) (3.72)

54


We note that p2 = p is the solution to ′′ p + u∗ p = 0 a.e. t ∈ [0, T ], p(0) = p(1) = 0. Hence p and y ∗ are both solutions to y ′′ + u∗ y = 0 and therefore p = Cy ∗ on (0, 1). If λ = 0, by (3.72) we see that 2 u∗ (t) = argmax −C y ∗ (t) u . u∈U

Hence, u∗ (t) = 0 if C > 0 and u∗ (t) = B if C < 0. However u∗ = 0 and u∗ (t) = B because we know that u = π 2 is admissible in our problem and B > π 2 . Hence λ = 0 and so λ = 1. Then by (3.72) it follows that − y ∗ (t)p(t) + 1 ∈ NU u∗ (t) ⊂ N[0,B] u∗ (t) a.e. t ∈ [0, 1]. Hence (see (2.15)) 0 u∗ (t) = B

if y ∗ (t)p(t) + 1 > 0, if y ∗ (t)p(t) + 1 < 0.

Equivalently u∗ (t) =

0 B

if C(y ∗ (t))2 + 1 > 0, if C(y ∗ (t))2 + 1 < 0.

(3.73)

(This follows by an elementary argument as in [36].) On the other hand, if u∗ is optimal, then |(y ∗ )′ (t)| = 0, ∀t ∈ (0, 1). One can compute exactly (t1 , t2 ) and find v=

T

u∗ (t) dt.

0

From here, we may conclude that for any u ∈ L∞ (0, T ) with 0 u B, if

T

u(t) dt < v,

0

then the equation y ′′ + uy = 0,

y ′ (0) = y ′ (1) = 0

has only the trivial solution y = 0. This result is relevant in the theory of nonlinear resonant problems of the form y ′′ + f (y) = 0,

y ′ (0) = y ′ (1) = 0.


55

3.5. Reachable sets and optimal control problems In what follows we consider the controlled equation (1.11) supposed for simplicity to be autonomous: y ′ = f u (y) := f (y, u) with the initial data y(0) = y0 . The hypotheses on f and the controller set U are such that for any u ∈ U the nonautonomous vector field f u(t) satisfies the hypotheses in Section 2.3. For example we will suppose that the controller set U = {u : [0, T ] → U : u ∈ L∞ (0, T )} and U ⊂ Rm is closed.The vector field f is assumed to be C ∞ in y for any fixed u ∈ U and f , ∂f ∂y are continuous in (y, u). The reachable set (or attainable set) at moment t is defined as follows: t −→ Ry0 (t) = y0 ◦ exp f u(τ ) dτ u ∈ U . 0

−→ t f u(τ ) dτ and the flow corresponding to the equation F t = We denote by y u (t) = exp s 0 − → t f u(τ ) dτ . exp s We prove in this section that optimal control problems reduce to the study of reachable sets. T HEOREM 3.6. If y u ∗ y u (s) ∈ ∂Ry0 (s).

∗ (T )

∈ ∂Ry0 (T ), the boundary of Ry0 (T ), then, for all 0 < s < T ,

P ROOF. It is clear that FsT (Ry0 (s)) ⊂ Ry0 (T ) and, since FsT is a diffeomorphism, FsT (int Ry0 (s)) ⊂ int Ry0 (T ) and the conclusion is immediate. We will still call such trajectories optimal and the corresponding controller optimal control. Optimal control problems We consider the following controlled equation

y ′ = f u (y), y(0) = y0 .

(3.74)

The optimal control problem is to find the admissible strategy u : [0, T ] → U such that the pair (u, y u ) minimizes a cost functional J . Depending on the form of the cost functional J we distinguished in Section 1.2 three types of optimal control problems: Lagrange, Mayer and Bolza.

56


We consider first of all the case of the Lagrange problem with fixed end points y0 , y1 and T cost functional J (y, u) = 0 L(y(t), u(t)) dt, with the Lagrangean L satisfying similar hypotheses with f . We introduce the new variable j and consider the new system:

j ′ = L(t, y, u), y ′ = f u (y)

(3.75)

with initial data y(0) = y0 ,

j (0) = 0.

We consider the set of controllers u ∈ U such that y u (T ) = y1 . Then it is clear that, if ∗ (u∗ , y u ) is an optimal pair then ∗ j (T ), y u (T ) ∈ ∂R(0,y0 ) (T )

where R(0,y0 ) refers to the reachable set for system (3.75). This reduction has some inconvenient in the sense that it does not distinguish between trajectories realizing the minimum of J and those realizing the maximum. That is why one considers the extended set of

= {(u, v) | u ∈ U, v ∈ [0, +∞)} and the problem controllers U   j ′ = L(t, y, u) + v, y ′ = f u (y),  y(0) = q0 , j (0) = 0.

(3.76)

˜ 0) is optimal in It is now clear that if u∗ is optimal for the Lagrange problem then (u, (3.76). Since Mayer problem is just a particular case of a Bolza problem, we describe the reduction for the latter. In this case the cost functional is J (y, u) = g(y(T )) + T 0 L(t, y(t), u(t)) dt and the functions g, L satisfy similar hypotheses to f . We intro and consider the new system: duce the new variable j , the extended set of controllers U  n  ∂l   (y)fi (y, u) + v,  j ′ = L(t, y, u) + ∂yi i=1   y ′ = f u (y),   q(0) = q0 , j (0) = 0.

(3.77)

As in the case of the Lagrange problem, if u∗ is optimal for the Bolza problem, then (u∗ , 0) is optimal in (3.77). We have thus seen that the study of optimal control problems reduces to the study of reachable sets, more precisely to the study of those trajectories whose final points belong to the boundary of the reachable set at that moment.


57

3.6. Geometric form of Pontriaghin maximum principle In this section we present a coordinate free version of the maximum principle (see also Section 3.1). The proof we give here follows the ideas in [2]. For u ∈ U we consider the Hamiltonian H u := (f u )# . ∗

T HEOREM 3.7. Suppose that for the admissible control u∗ (t), t ∈ [0, T ], y u (T ) ∈ ∂Ry0 (T ). Then there exists a non-zero Lipschitz curve in the cotangent bundle ξ(t) ∈ Ty∗u∗ (t) M solution of the Hamiltonian equation d − →u∗ (t) ξ(t) ξ(t) = H dt

and the following maximality condition is satisfied − →u(t) − →u∗ (t) ξ(t) . H ξ(t) = max H u∈U

P ROOF. The idea of the proof is to consider as curve ξ(t) a curve of covectors “orthogonal” at each point to the boundary of the reachable set: ∂Ry0 (t). Step 1. Let T : RN → Rn be Lipschitz continuous, T(0) = 0 and differentiable at 0. Denote by T0 = DT(0) and by N RN + = (x1 , . . . , xN ) ∈ R | xi 0 . n N We prove that if T0 (RN + ) = R , then for any neighborhood V of 0 in R , 0 ∈ int T(V ∩ N R+ ). N By the convexity of RN + it turns out that T0 |int RN is surjective and let y ∈ int R+ with +

T0 (y) = 0 and δ > 0 such that y + Bδ ⊂ int RN +. It is clear that one may find an n-dimensional linear subspace X ⊂ RN such that T0 (X) = Rn so T0 |X is invertible. Denote by D = Bδ ∩ X and for ε > 0 the continuous functions Tε : D → Rn : 1 Tε (v) = T ε(y + v) . ε

One may easily check that Tε → T0 uniformly on D and since 0 ∈ int T0 (D) it turns out, using an usual argument based on degree theory, that 0 ∈ int Tε (D) for ε > 0 small enough or, equivalently, 0 ∈ int T(ε(y + Bδ )) which concludes the Step 1. Step 2. We consider an admissible control u(t) and compute the end point of the trajectory using the second form of variations of parameters formula (2.40): → y (T ) = y0 ◦ − exp u

u∗

T

fu

∗ (t)

0

→ = y (T ) ◦ − exp

0

T

∗ + f u(t) − f u (t) dt

FtT

u(t) ∗ f − f u (t) dt. ∗

(3.78)

58


Denote by ∗ g t,u = FtT ∗ f u − f u (t)

and let L be the set of Lebesgue points of u∗ (see (3.17)). We suppose that the convex cone ∗ W generated by {g t,u (y u (T )) | t ∈ L, u ∈ U } is the whole tangent space Ty u∗ (T ) M. We ∗ prove that, in this case, necessarily y1 := y u (T ) ∈ int Ry0 (T ). Indeed, one may find a finite set of points 0 < t1 < · · · < tN < T and u1 , . . . , uN ∈ U such that W is generated by the finite set {g ti ,ui | i = 1, . . . , N}. For x = (x1 , . . . , xN ) ∈ RN + we consider the strategy:

ux (t) =

 ui ,  

∗   u (t),

t ∈ [ti , ti + xi ], N ! t ∈ [0, T ] [ti , ti + xi ]. i=1

Variation of parameters formula (3.78) gives: x → y u (T ) = y0 ◦ − exp

T

fu

0

u∗

→ exp = y (T ) ◦ −

x (t)

dt

t1 +x1

t1

g

t,u1

→ dt ◦ · · · ◦ − exp

tN +xN

g t,un dt.

(3.79)

tN

If one considers the map: x

T(x1 , . . . , xN ) = y u (T ),

x1 , . . . , xN ∈ R

then it is easy to verify that T is Lipschitz continuous, T(0) = y1 and ∂T = g ti ,ui (y1 ). ∂xi (0,...,0) The hypotheses of Step 1 are verified and, consequently, y1 ∈ int T V ∩ RN +

for any neighborhood V of 0 in RN and, since ux is an admissible strategy we find that y1 ∈ int Ry0 (T ). ∗

Step 3. Suppose now that y u (T ) ∈ ∂Ry0 (T ). Since 0 ∈ ∂W, there exists a support hyperplane defined by ξ(T ) ∈ Ty∗u∗ (T ) M,ξ(T ) = 0 such that ∗ ξ(T ) g T ,u y u (T ) 0 a.e. t ∈ [0, T ], u ∈ U.


59

This means exactly that ∗ ∗ ∗ T ∗ Ft ξ(T ) f u y u (t) FtT ξ(T ) f u y u (t) .

Denote by

∗ ξ(t) = FtT ξ(T ).

The maximality condition is satisfied and, by (2.43) d − →u∗ (t) ξ(t) ξ(t) = H dt

which concludes the proof.

It is now easy to recover the maximum principle for optimal control problems, as is expressed in Section 3.1 by using the transformation described in Section 3.5 and the geometric form of maximum principle, Theorem 3.7.

3.7. Free time optimal control problems The free time optimal control problem min

(u,T )

T

0

L t, y(t), u(t) dt + g y(0), y(T ) ; y(0), y(T ) ∈ C

(3.80)

subject to y ′ = f (y, u)

a.e. t ∈ (0, T )

can be reduced to a fixed time optimal control problem of the form (1.14) by substitution

s

w 2 (τ ) dτ, z(s) = y t (s) ,

t=

0

This yields

min

(v,w)

0

1

0 s 1, v(s) = u t (s) .

L t (s), z(s), v(s) w 2 (s) ds + g z(0), z(1) ; z(0), z(1) ∈ C

subject to z′ (s) = f z(s), v(s) w 2 (s)

a.e. s ∈ (0, 1).

60


In this case, by Theorem 3.1 we find that the maximum principle has the form p ′ (t) = −fy (y ∗ , u∗ )p + λLy (y ∗ , u∗ ), p(0), −p(T ) ∈ λ∇g y ∗ (0), y ∗ (T ) + NC y ∗ (0), y ∗ (T ) , p(t), f t, y ∗ (t), u∗ (t) − λL t, y ∗ (t), u∗ (t) = max p(t), f y ∗ (t), u∗ − λL y ∗ (t), u , (u∈U (t) p(t), f t, y ∗ (t), u∗ (t) − λL t, y ∗ (t), u∗ (t) = 0 a.e. t ∈ [0, T ]

(3.81)

where λ = 0, 1 and p(t) + λ = 0, ∀t ∈ [0, T ]. In the special case, L ≡ 1, g ≡ 0, (3.80) reduces to the optimal time problem min T ; y(0), y(T ) ∈ C, u ∈ U (t), a.e. t ∈ (0, T ) .

(T ,u)

(3.82)

We leave to the reader to deduce the maximum principle (from (3.81)) in this case. We note, however, that if g = 0, C = {y0 } × {y1 }, then it reads as p ′ (t) = −fy (t, y ∗ , u∗ )p a.e. in (0, T ), ∗ ∗ p(t), f t, y (t), u (t) − λ = 0 a.e. t ∈ (0, T ), p(t), f t, y ∗ (t), u∗ (t) = max p(t), f t, y ∗ (t), u u∈U (t)

where λ ∈ {0, 1} and |p(t)| + λ = 0, ∀t ∈ [0, T ]. Hence |p(t)| = 0, ∀t ∈ [0, T ]. From the geometric point of view, in the case of Lagrange or Bolza problems considered in Section 3.5, if the final time T is free the conclusion is that for the equivalent ∗ problems (3.75), respectively (3.77), the optimal pair ((u∗ , 0), (j ∗ , y u ) satisfy, for ε > 0 small enough ∗ ∗ j (T ), y u (T ) ∈ ∂

!

|T −t| x and Φ is SOP then there exist neighborhoods U of x and V of ΦT (x) and t0 > 0 such that Φt0 (U ) Φt0 (V ). It follows that Φt0 (x) Φt0 +T +ǫ (x) for all ǫ sufficiently small. The previous assertion implies ω(x) = p ∈ E. 1.2. Nonordering of omega limit sets The next result is the first of several describing the order geometry of limit sets. P ROPOSITION 1.5 (Nonordering of Periodic Orbits). A periodic orbit of a monotone semiflow is unordered. P ROOF. Let x have minimal period s > 0 under a monotone semiflow Φ. Suppose x z ∈ O(x). By compactness of O(x) there is a maximal y ∈ O(x) such that y z x. By periodicity and monotonicity y = Φt (x) Φt (y), t > 0, hence y = Φt (y) by maximality. Therefore t is an integer multiple of s, so x = Φt (x) = y, implying x = z. The following result, which implies (1.5), is a broad generalization of the obvious fact that for ODEs in R, nonconstant solutions are everywhere increasing or everywhere decreasing. Let J ⊂ R be an interval and f : J → X a map. A compact subinterval [a, b] ⊂ J is rising for f provided f (a) < f (b), and falling if f (b) < f (a). T HEOREM 1.6. A trajectory of a monotone semiflow cannot have both a rising interval and a falling interval. This originated in Hirsch [67], with improvements in Smith [194], Smith and Waltman [203]. An analog for maps is given in Theorem 5.4. P ROOF. Let Φ be a monotone semiflow in X and fix a trajectory f : [0, ∞) → X, f (t) := Φt (x). Call an interval [d, d ′ ] weakly falling if f (d) f (d ′ ). Monotonicity shows that when this holds, the right translates of [d, d ′ ]—the intervals [d + u, d ′ + u] with u 0— are also weakly falling. Proceeding by contradiction, we assume f has a falling interval [a, a + r] and a rising interval [c, c + q]. To fix ideas we assume a c, the case c a being similar. Define b := sup t ∈ [c, c + q]: f (t) f (c), s := c + q − b .

Then [b, b + s] is a rising interval in [c, c + q], and b s, and (ii) [b − (l − s), b] is weakly falling. To see (i), observe that f (b + l) f (b) because

250

M.W. Hirsch and H. Smith

[b, b + l] is a right translate of [b − l, b]; hence l s would entail b < b + l b + s, contradicting (1.1) with t = b + l. To prove (ii), note that right translation of [b − l, b] shows that [b − l + s, b + s] is weakly falling, implying f (b − (l − s)) f (b + s) > f (b); hence [b − (l − s), b] is falling. Repetition of this argument with l replaced by l − s, l − 2s, . . . leads by induction on n to the absurdity that l − ns > s for all n ∈ N. Claim 2: r > s. For f (b + r) f (b) because [b, b + r] is falling, as it is a right translate of [a, a + r]. Therefore r > s, for otherwise b < b + r b + s and (1.1) leads to a contradiction. As b + s a + r, we can translate [a, a + r] to the right by (b + s) − (a + r), obtaining the weakly falling interval [b + s − r, b + s]. Note that b + s − r < b by Claim 2. From f (b + s − r) f (b + s) > f (b)] we conclude that [b − (r − s), b] is falling. But this contradicts Claim 1 with l = r − s. L EMMA 1.7. An omega limit set for a monotone semiflow Φ cannot contain distinct points x, y having respective neighborhoods U, V such that Φr U Φr V for some r 0. P ROOF. We proceed by contradiction. Suppose there exist distinct points x, y ∈ ω(z) having respective neighborhoods U , V such that Φr U Φr V for some r 0. Then ω(z) is not a periodic orbit, for otherwise from Φr (x) Φr (y) we infer x y and hence x < y, violating Nonordering of Periodic Orbits. There exist real numbers a < b < c be such that Φa (z) ∈ U , Φb (z) ∈ V , Φc (z) ∈ U . Therefore the properties of r, U and V imply Φa+r (z) Φb+r (z),

Φb+r (z) Φc+r (z).

As ω(z) is not periodic, the semiflow is injective on the orbit of z; hence the order relations above are strict. But this contradicts Theorem 1.6. It seems to be unknown whether omega limit sets of monotone semiflows must be unordered. This holds for SOP semiflows by the following theorem due to Smith and Thieme [197, Proposition 2.2]; the strongly monotone case goes back to Hirsch [66]. This result is fundamental to the theory of monotone semiflows: T HEOREM 1.8 (Nonordering of Omega Limit Sets). Let ω(z) be an omega limit set for a monotone semiflow Φ. (i) No points of ω(z) are related by ≪. (ii) If ω(z) is a periodic orbit or Φ is SOP, no points of ω(z) are related by 0 such that Φt0 (U ) Φt0 (V ). Let δ > 0 be so small that {Φs (x): 0 s δ} ⊂ U and {Φs (y): 0 s δ} ⊂ V . Then Φs (x) Φr (y) whenever t0 r, s t0 + δ. Therefore, Φtk −t0 Φs (x) Φtk −t0 Φt0 (y) = Φtk (y)

for all s ∈ [t0 , t0 + δ] and all large k. As

Φtk −t0 Φs (x) = Φs−t0 Φtk (x) = Φr Φtk (x) ,

(1.2)

Monotone dynamical systems

253

where r = s − t0 ∈ [0, δ] if s ∈ [t0 , t0 + δ], we have Φr Φtk (x) Φtk (y)

for large k and r ∈ [0, δ]. Passing to the limit as k → ∞ we find that Φr (p) p for 0 r δ. If, in (1.2), we replace Φs (x) by Φt0 (x) and replace Φt0 (y) by Φs (y), and argue as above then we find that p Φr (p) for 0 r δ. Evidently, Φr (p) = p, 0 r δ and therefore for all r 0, so p ∈ E.

T HEOREM 1.12 (Intersection Principle). If x < y then ω(x) ∩ ω(y) ⊂ E. If p ∈ ω(x) ∩ ω(y) and tk → ∞, then Φtk (x) → p if and only if Φtk (y) → p. P ROOF. If p ∈ ω(x) ∩ ω(y) then there exists a sequence tk → ∞ such that Φtk (x) → p and Φtk (y) → q ∈ ω(y), and p q by monotonicity. If p < q then we contradict the Nonordering of Limit Sets since p, q ∈ ω(y). Hence p = q. The Colimiting Principle then implies p ∈ E. The proof of the next result has been substantially simplified over previous versions. L EMMA 1.13. Assume x < y, tk → ∞, Φtk (x) → a, and Φtk (y) → b as k → ∞. If a < b then O(a) < b and O(b) > a. P ROOF. The set W := {t 0: Φt (a) b} contains 0 and is closed. We prove W = [0, ∞) by showing that W is also open. Observe first that if t ∈ W , then Φt (a) < b. For equality implies b ∈ ω(x) ∩ ω(y) ⊂ E, and then the Intersection Principle entails Φtk (x) → b, giving the contradiction a = b. Suppose t¯ ∈ W is positive. By SOP there are open sets U, V with Φt¯(a) ∈ U , b ∈ V and t1 0 such that Φt (U ) Φt (V ) for t t1 . There exists δ ∈ (0, t¯/2) such that Φs (a) ∈ U for |s − t¯| δ, so we can find an integer κ > 0 such that Φs (Φtk (x)) ∈ U for k κ. Choose k0 κ such that Φtk0 (y) ∈ V . Then we have Φt+s+tk0 (x) Φt+tk0 (y) for t t1 . Setting t = tk − tk0 for large k in this last inequality yields Φtk +s (x) Φtk (y) for large k. Taking the limit as k → ∞ we get Φs (a) b for |s − t¯| δ. A similar argument in the case t¯ = 0 considering only s ∈ [0, δ] gives the previous inequality for such s. Therefore, W is both open and closed so W = [0, ∞). This proves O(a) < b, and O(b) > a is proved dually. L EMMA 1.14 (Absorption Principle). Let u, v ∈ X. If there exists x ∈ ω(u) such that x < ω(v), then ω(u) < ω(v). Similarly, if there exists x ∈ ω(u) such that ω(v) < x, then ω(v) < ω(u). P ROOF. Apply Lemma 1.3 to obtain open neighborhoods U of x and V of ω(v) and t0 > 0 such that r t0

)⇒ Φr (U ) Φr (V ),

hence Φr (U ) ω(v) since ω(v) is invariant. As x ∈ ω(u), there exists t1 > 0 such that Φt1 (u) ∈ U . Hence for Φt0 +t1 (u) ω(v), and monotonicity implies that Φs+t0 +t1 (u)

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ω(v) for all s 0. This implies that ω(u) ω(v). If z ∈ ω(u) ∩ ω(v) then z = sup ω(u) = inf ω(v), whence {z} = ω(u) = ω(v) by Corollary 1.9(ii). But this is impossible since x < ω(v) and x ∈ ω(u), so we conclude that ω(u) < ω(v). L EMMA 1.15 (Limit Set Separation Principle). Assume x < y, a < b and there is a sequence tk → ∞ such that Φtk (x) → a, Φtk (y) → b. Then ω(x) < ω(y). P ROOF. By Lemma 1.13, O(a) < b, and therefore ω(a) b. If b ∈ ω(a) then Corollary 1.9 implies that ω(a) = b ∈ E. Applying the Absorption Principle with u = x, v = a, x = a, we have a ∈ ω(x), a < ω(a) = b which implies that ω(x) < ω(a). This is impossible as ω(a) ⊂ ω(x). Consequently, ω(a) < b. By the Absorption Principle again (with u = a, v = y), we have ω(a) < ω(y). Since ω(a) ⊂ ω(x), the Absorption Principle gives ω(x) < ω(y). We now prove the fundamental tool in the theory of monotone dynamics, stated for strongly monotone semiflows in Hirsch [66,68]. T HEOREM 1.16 (Limit Set Dichotomy). If x < y then either (a) ω(x) < ω(y), or (b) ω(x) = ω(y) ⊂ E. If case (b) holds and tk → ∞ then Φtk (x) → p if and only if Φtk (y) → p. P ROOF. If ω(x) = ω(y) then ω(x) ⊂ E by the Intersection Principle, Theorem 1.12, which also establishes the final assertion. If ω(x) = ω(y) then we may assume that there exists q ∈ ω(y) \ ω(x), the other case being similar. There exists tk → ∞ such that Φtk (y) → q. By passing to a subsequence if necessary, we can assume that Φtk (x) → p ∈ ω(x). Monotonicity implies p q and, in fact, p < q since q ∈ / ω(x). By the Limit Set Separation Principle, ω(x) < ω(y). Among the many consequences of the Convergence Criterion is that a monotone semiflow in a strongly ordered Banach space cannot have a periodic orbit γ that is attracting, meaning that γ attracts all points in some neighborhood of itself (Hadeler [55], Hirsch [69]). The following consequence of the Limit Set Dichotomy implies the same conclusion for periodic orbits of SOP semiflows: T HEOREM 1.17. Let γ be a nontrivial periodic orbit, some point of which is accessible from above or below. Then γ is not attracting. The accessibility hypothesis is used to ensure that there are points near p that are orderrelated to p but different from p. Some such hypothesis is required, as otherwise we could simply take X = γ , and then γ is attracting! P ROOF. Suppose γ ⊂ W attracts an open set W . By hypothesis there exists p ∈ γ and x ∈ W such that x > p or x < p and ω(x) = γ . To fix ideas we assume x > p. Then


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p ∈ ω(x), so the Limit Set Dichotomy implies p ∈ E. Hence the contradiction that γ contains an equilibrium. It turns out that the periodic orbits γ considered above are not only not attracting; they enjoy the strong form of instability expressed in the next theorem. A set K ⊂ X is minimal if it is nonempty, invariant, and every orbit it contains is dense in K. T HEOREM 1.18. Let K be a compact minimal set that is not an equilibrium, some point of which is accessible from below or above. Then there exists δ > 0 with the following property: Every neighborhood of K contains a point x comparable to some point of K, such that dist(Φt (x), K) > δ for all sufficiently large t. P ROOF. We may assume there exists a sequence xñ → p ∈ K with xñ > p. Suppose there is no such δ. Then there exist a subsequence {xn } and points yn ∈ ω(xn ) such that yn → q ∈ K. Minimality of K implies ω(p) = ω(q) = K. Since xn > p, the Limit Set Dichotomy implies ω(xn ) ω(p); therefore yn K, so q K. It follows that q = sup K, and Corollary 1.9 implies the contradiction that K is a singleton. A stronger form of instability for periodic orbits is given in Theorem 2.6.

1.5. Q is plentiful One of our main goals is to find conditions that make quasiconvergent points generic in various senses. The first such results are due to Hirsch [66,73]; the result below is an adaptation of Smith and Thieme [199, Theorem 3.5]. We continue to assume Φ is an SOP semiflow with compact orbit closures. A totally ordered arc is the homeomorphic image of a nontrivial interval I ⊂ R under a map f : I → X satisfying f (s) < f (t) whenever s, t ∈ I and s < t. T HEOREM 1.19. If J ⊂ X is a totally ordered arc, J \ Q is at most countable. Stronger conclusions are obtained in Theorems 2.8 and 2.24. The following global convergence theorem is adapted from Hirsch [73, Theorem 10.3]. C OROLLARY 1.20. Let Y be an ordered Banach space. Assume X ⊂ Y is an open set, a closed order interval, or a subcone of Y+ . If E = {p}, every trajectory converges to p. P ROOF. If X is open in Y , there exists a totally ordered line segment J ⊂ X and quasiconvergent points u, v ∈ J with u < x < v, by Theorem 1.19. Therefore Φt (u) → p and Φt (v) → p, so monotonicity and closedness of the order relation imply Φt (x) → p. If X = [a, b], the trajectories of a and b converge to p by the Convergence Criterion 1.4, and the previous argument shows all trajectories converge to p. Similarly if X is a subcone of Y+ .

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P ROOF OF T HEOREM 1.19. Let W = Φ([0, ∞) × J ). Continuity of Φ implies that W is a separable metric space which is positively invariant under Φ. Therefore we may as well assume that X is a separable metric space. We show that if x ∈ J and inf dist ω(x), ω(y) : y ∈ J, y = x = 0,

then x ∈ Q. Choose a sequence xn ∈ J , xn = x such that dist(ω(x), ω(xn )) → 0. We may assume that xn < x for all n. Taking a subsequence, we conclude from the Limit Set Dichotomy: Either some ω(xn ) = ω(x), or every ω(xn ) < ω(x). In the first case, x ∈ Q. In the second case, choose yn ∈ ω(xn ), zn ∈ ω(x) such that d(yn , zn ) → 0. After passing to subsequences, we assume yn , zn → z ∈ ω(x). Because yn ω(x), we conclude that z ω(x). As z ∈ ω(x), Corollary 1.9 implies ω(x) = {z}. Hence x ∈ Q in this case as well. It follows that for every x ∈ J \ Q, there exists an open set Ux containing ω(x) such that Ux ∩ ω(y) = ∅ for every y ∈ J \ {x}. By the axiom of choice we get an injective mapping J \ Q → X,

x → px ∈ ω(x) ⊂ Ux .

The separable metric space X has a countable base B. A second application of the axiom of choice gives a map J \ Q → B,

x → Vx ⊂ Ux ,

px ∈ Vx .

This map is injective. For if x, y are distinct points of J \ Q, then Vx = Vy because Vx , being contained in Ux , does not meet ω(y); but py ∈ Vy ∩ ω(y). This proves J \ Q is countable. Let Y be an ordered Banach space and assume X ⊂ Y is an ordered subspace (not necessarily linear). When Y is finite-dimensional, Theorem 1.19 implies X \ Q has Lebesgue measure zero, hence almost every point is quasiconvergent. For infinite-dimensional Y there is an analogous result for Gaussian measures (Hirsch [73, Lemma 7.7]). The next result shows that in this case Q is also plentiful in the sense of category. A subset of a topological space S is residual if it contains the intersection of countably many dense open subsets of S. When S is a complete metric space every residual set is dense by the Baire category theorem. The assumption on X in the following result holds for many subsets of an ordered Banach space, including all convex sets and all sets with dense interior. T HEOREM 1.21. Assume X is a subset of an ordered Banach space Y , and a dense open subset X0 ⊂ X is covered by totally ordered line segments. Then Q is residual in X. P ROOF. It suffices to show that the set Q1 := Q ∪ (Y \ X0 ) is residual in Y . Note that Y \ Q1 = X0 \ Q. Let L ⊂ Y be the 1-dimensional space spanned by some positive vector. Every translate y + L meets Y \ Q1 in a finite or countably infinite set by Theorem 1.19,


257

hence (y + L) ∩ Q1 is residual in the line y + L. By the Hahn–Banach theorem there is a closed linear subspace M ⊂ Y and a continuous linear isomorphism F : Y ≈ M × L such that F (x + L) = {x} × L for each x ∈ M. Therefore F (Q1 ) ∩ ({x} × L) is residual in {x} × L for all x ∈ X0 , whence F (Q1 ) is residual in M × L by the Kuratowski–Ulam Theorem (Oxtoby [154]). This implies Q1 is residual in Y . Additional hypotheses seem to be necessary in order to prove density of Q in general ordered spaces. The next theorem obtains the stronger conclusion that Q has dense interior. A different approach will be explored in Section 2. A point x is doubly accessible from below (respectively, above) if in every neighborhood of x there exist f , g with f < g < x (respectively, x < f < g). Consider the following condition on a semiflow satisfying (H): (L) Either every omega limit set has an infimum in X and the set of points that are doubly accessible from below has dense interior, or every omega limit set has a supremum in X and the set of points that are doubly accessible from above has dense interior. This holds when X is the Banach space of continuous functions on a compact set with the usual ordering, for then every compact set has a supremum and infimum, and every point is doubly accessible from above and below. T HEOREM 1.22. If (L) holds, then X \ Q ⊂ Int C, and Int Q is dense. The proof is basedon the following result. For p ∈ E define C(p) := {z ∈ X: ω(z) = {p}}. Note that C = p∈E C(p).

L EMMA 1.23. Suppose x ∈ X \ Q and a = inf ω(x). Then ω(a) = {p} with p < ω(x), and x ∈ Int C(p) provided x is doubly accessible from below. P ROOF. Fix an arbitrary neighborhood M of x. Note that a < ω(x) because ω(x) is unordered (Theorem 1.8). By invariance of ω(x) we have Φt a ω(x), hence Φt a a. Therefore the Convergence Criterion Theorem 1.4 implies ω(a) is an equilibrium p a. Because p < ω(x), SOP yields a neighborhood N of ω(x) and s 0 such that p Φt N for all t s. Choose r 0 with Φt x ∈ N for t r. Then p Φt x if t r + s. The set V := (Φr+s )−1 (N ) ∩ M is a neighborhood of x in M with the property that p Φt V for all t r + 2s. Hence: u∈V

)⇒ p ω(u).

(1.3)

Now assume x doubly accessible from below and fix y1 , y ∈ V with y1 < y < x. By the Limit Set Dichotomy ω(y) < ω(x), because ω(x) ⊂ E. By SOP we fix a neighborhood U ⊂ V of y1 and t0 > 0 such that Φt0 u Φt0 y for all u ∈ U . The Limit Set Dichotomy implies ω(u) = ω(y) or ω(u) < ω(y); as ω(y) < ω(x), we therefore have: u∈U

)⇒ ω(u) < ω(x).

(1.4)

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For all u ∈ U , (1.4) implies ω(u) ω(a) = {p}, while (1.3) entails p ω(u). Hence U ⊂ C(p) ∩ M, and the conclusion follows. P ROOF OF T HEOREM 1.22. To fix ideas we assume the first alternative in (L), the other case being similar. Let X0 denote a dense open set of points doubly accessible from below. Lemma 1.23 implies X0 ⊂ Q ∪ Int C ⊂ Q ∪ Int Q, hence the open set X0 \ Int Q lies in Q. This prove X0 \ Int Q ⊂ Int Q, so X0 \ Int Q = ∅. Therefore Int Q ⊃ X0 , hence Int Q ⊃ X0 = X. E XAMPLE 1.24. An example in Hirsch [73] shows that generic quasiconvergence and the Limit Set Dichotomy need not hold for a monotone semiflow that does not satisfy SOP. Let X denote the ordered Banach space R3 whose ordering is defined by the “ice-cream” cone

X+ = {x ∈ R3 : x3 x12 + x22 }. The linear system x1′ = −x2 , x2′ = x1 , x3′ = 0 generates a flow Φ with global period 2π which merely rotates points about the x3 -axis. Evidently X+ is invariant, so linearity of Φ implies monotonicity. On the other hand, Φ is not strongly order preserving: If a = (1, 0, 1) (or any other point on ∂Y+ except the origin 0), SOP would require Φt (a) ≫ 0 for t > 0 because Φt is a homeomorphism, but this fails for all t > 0. The Limit Set Dichotomy fails to hold: For a = (1, 0, 1) and b = (2, 0, 2) it is easy to see that a < b (for the ordering defined by X+ ) and ω(a) ∩ ω(b) = ∅, but ω(a) < ω(b). As E = C = Q = {x: x1 = x2 = 0} and most points belonging to periodic orbits of minimal period 2π , quasiconvergence is rare. In fact, the set of nonquasiconvergent points—the complement of the x3 -axis—is open and dense. It is not known whether there is a similar example with a polyhedral cone.

1.6. Stability in normally ordered spaces We continue to assume the semiflow Φ is SOP with compact orbit closures. The diameter of a set Z is diam Z := supx,y∈Z d(x, y). We now introduce some familiar stability notions. A point x ∈ X is stable (relative to R ⊂ X) if for every ǫ > 0 there exists a neighborhood U of x such that diam Φt (U ∩ R) < ǫ for all t 0. The set of stable points is denoted by S. Suppose x0 is stable. Then omega limit sets of nearby points are close to ω(x0 ), and if all orbit closures are compact, the map x → ω(x) is continuous at x0 for the Hausdorff metric on the space of compact sets. x is stable from above (respectively, from below) if x is stable relative to the set of points x (resp., x). The set of points stable from above (resp., below is denoted by S+ (resp., S− ). The basin of x in R is the union of all subsets of R of the form V ∩ R where V ⊂ X is an open neighborhood of x such that lim diam Φt (V ∩ R) = 0.

t→∞

Notice that ω(x) = ω(y) for all y in the basin.


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If the basin of x in R is nonempty, we say x is asymptotically stable relative to R. This implies x is stable relative to R. If x is asymptotically stable relative to X we say x is asymptotically stable. The set of asymptotically stable points is an open set denoted by A. x is asymptotically stable from above (respectively, below) if it is asymptotically stable relative to the set of points x (resp., x). The basin of x relative to this set is called the upper (resp., lower) basin of x. The set of such x is denoted by A+ (resp., A− ). Note that continuity of Φ shows that asymptotic stability relative to R implies stability relative to R. In particular, A ⊂ S, A+ ⊂ S+ and A− ⊂ S− . These stability notions for x depend only on the topology of X, and not on the metric, provided the orbit of x has compact closure. The metric space X is normally ordered if there exists a normality constant κ > 0 such that d(x, y) κd(u, v) whenever u, v ∈ X and x, y ∈ [u, v]. In a normally ordered space order intervals are bounded and the diameter of [u, v] goes to zero with d(u, v). Many common function spaces, including Lp spaces and the Banach space of continuous functions with the uniform norm, are normally ordered by the cone of nonnegative functions. But spaces whose norms involve derivatives are not normally ordered. Normality is required in order to wring the most out of the Sequential Limit Set Trichotomy. The propositions that follow record useful stability properties of SOP dynamics in normally ordered spaces. P ROPOSITION 1.25. Assume X is normally ordered. (a) x ∈ S+ (respectively, S− ) provided there exists a sequence yn → x such that yn > x (resp., yn < x) and limn→∞ supt>0 d(Φt (x), Φt (yn )) = 0. (b) x ∈ S provided x ∈ S+ ∩ S− and x is accessible from above and below. (c) x ∈ A provided x ∈ A+ ∩ A− and x is accessible from above and below. (d) Suppose a < b and ω(a) = ω(b). Then a ∈ A+ and b ∈ A− . If a < x < b then x ∈ A and the basin of x includes [a, b] \ {a, b}. In particular, (d) shows that an equilibrium e is in A+ if x > e and Φt (x) → e (provided X is normally ordered); and dually for A− . P ROOF. We prove (a) for the case yn > x. Given ǫ > 0, choose m and t0 so that t > t0 )⇒ d Φt (x), Φt (ym ) < ǫ.

By SOP there exists a neighborhood W of x and t1 > t0 such that t > t1 , v ∈ W

)⇒ Φt (v) < Φt (ym ).

Fixing t1 , we shrink W to a neighborhood Wǫ of x so that 0 < t t1 , v ∈ Wǫ )⇒ d Φt (x), Φt (v) < κǫ,

where κ > 0 is the normality constant. If x < v ∈ Wǫ and t > t1 then Φt (x) Φt (v) Φt (ym ), and therefore t > t1 , x < v ∈ Wǫ )⇒ d Φt (x), Φt (v) κd Φt (x), Φt (ym ) κǫ.

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Hence we have proved )⇒ d Φt (x), Φt (v) < κǫ.

0 < t < ∞, v ∈ Wǫ

As ǫ is arbitrary, this proves x ∈ S+ . To prove (b), let un , vn → x with un < x < vn . Because x ∈ S+ ∩ S− , for any ǫ > 0 there exists δ > 0 such that if d(y, x) < δ and y < x or y > x, then supt>0 d(Φt (y), Φt (x)) < ǫ. Choose k such that d(uk , x) < δ and d(vk , x) < δ. By SOP there is a neighborhood Wǫ of x such that Φt (uk ) Φt (Wǫ ) Φt (vk ) for sufficiently large t. Normality implies that for such t, κ −1 diam Φt (We ) d Φt (uk ), Φt (vk ) d Φt (uk ), Φt (x) + d Φt (x), Φt (vk ) < 2ǫ.

As κ is constant and ǫ is arbitrary, this proves x is stable. The proofs of (c) and (d) are similar.

P ROPOSITION 1.26. Assume X is normally ordered, p ∈ E, and {Kn } is a sequence of nonempty compact invariant sets such that Kn < p and dist(Kn , p) → 0. Then: (a) p is stable from below. (b) If z is such that ω(z) = p, then z is stable from below. In particular, if p is the limit of a sequence of equilibria < p then p is stable from below. P ROOF. (a) Given ǫ > 0, fix m such that dist(Km , p) < ǫ. By Lemma 1.3 there is a neighborhood W of p and t0 > 0 such that t > t0 )⇒ Φt (W ) Km , and therefore t > t0 , v ∈ W, p > v

)⇒ d Φt (p), Φt (v) κd Φt (p), Φt (Km ) κǫ.

Pick a neighborhood Wǫ ⊂ W of p so small that 0 t t0 , v ∈ W ǫ Then

)⇒ d Φt (p), Φt (v) < κǫ.

0 t < ∞, v ∈ Wǫ , v < p

)⇒ d Φt (p), Φt (v) < κǫ.

This proves p ∈ S− , because ǫ is arbitrary. (b) Choose a neighborhood U of z and t1 0 such that Φt1 (U ) ⊂ W . Assume y ∈ U , y < z. If t t1 + t0 , then Km Φt (y) Φt (z), and therefore by normality, d(Φt (y), Φt (z)) κ dist(Km , Φt (z)). As Φt (z) → p, there exists t2 t1 + t0 such that t t2

)⇒

d Φt (y), Φt (z) κ dist(Km , p) < κǫ.


Fix this t2 . By continuity of Φ there is a neighborhood U1 ⊂ U of z so small that 0 t t2 )⇒ d Φt (y), Φt (z) κǫ. As ǫ is arbitrary, this implies z ∈ S− .

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1.7. Stable equilibria in strongly ordered Banach spaces In spaces that are not normally ordered we cannot directly use the results of the previous subsection to characterize stable equilibria. For strongly monotone semiflows in strongly ordered Banach spaces we work around this by introducing a weaker norm that makes the order normal, and for which the semiflows are continuous and SOP. This permits use of the earlier results. Let Y be a strongly ordered Banach space. The order topology on Y is the topology is generated by open order intervals. An order norm on the topological vector space Y defined by fixing u ≫ 0 and assigning to x the smallest ǫ such that x ∈ [−ǫu, ǫu]. It is normally ordered by the order norm, with normality constant 1. is easy to see that Y contains [p − ǫu, p + ǫu] for all sufficiently small Every order neighborhood of p in Y numbers ǫ > 0. For example, Y = C 1 ([0, 1]) with the usual C 1 -norm and with Y+ the cone of nonnegative functions is strongly ordered but not normally ordered; putting u := 1, the order norm becomes the usual supremum. The induced topology on any subset Z ⊂ Y is also referred to as the order topology, A neighborhood in Z is an order and the resulting topological space is denoted by Z. neighborhood. is open in Z, i.e., the identity map of Z is continuous from Z Every open subset of Z to Z. Therefore Z = Z as topological spaces when Z is compact. As shown below, if Ψ is denoted by Ψ . Evidently a monotone local semiflow in Z, it is also a local semiflow in Z, Ψ and Ψ have the same orbits and the same invariant sets. L EMMA 1.27. Let Ψ be a monotone local semiflow in a subset X of a strongly ordered Banach space Y , that extends to a monotone local semiflow in an open subset of Y . Then: is a monotone local semiflow. (a) Ψ is SOP. (b) If Ψ is a strongly monotone, then Ψ

P ROOF. It suffices to prove (a) and (b) when X is open in Y , which condition is henceforth assumed. is monotone because Ψ is monotone. To prove continuity of Ψ , let N = [[a, b]]Y ∩ X Ψ −1 and (t0 , x0 ) ∈ Ψ (N ). As the latter is open in R+ × X, there exists ǫ > 0 and U , an open neighborhood of x0 in X, such that −1 (N ). (t0 − ǫ, t0 + ǫ) ∩ R+ × U ⊂ Ψ We may choose u, v ∈ U such that x ∈ [[u, v]]Y . If z ∈ [[u, v]]Y ∩ X and |t − t0 | < ǫ then t (u) Ψ t (z) Ψ t (v) ≪ b. Thus, by monotonicity and u, v ∈ U we have a ≪ Ψ −1 (N ), (t0 − ǫ, t0 + ǫ) ∩ R+ × [[u, v]]Y ∩ X ⊂ Ψ

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. proving the continuity of Ψ Assume x, y ∈ X, x < y and let t0 > 0 be given. By strong monotonicity of Ψ there are respective open neighborhoods U, V ⊂ X of x, y such that Ψt0 (U ) Ψt0 (V ) (see Proposition 1.2). Choose w, u, v, z ∈ X such that u, w ∈ U , v, z ∈ V and w ≪ x ≪ u,

v≪y≪z

so that [[w, u]]Y ∩ X and [[v, z]]Y ∩ X are order neighborhoods in X of x, y respectively. Monotonicity of Ψ implies Ψt0 [[w, u]]Y ∩ X Ψt0 [[v, z]]Y ∩ X .

An equilibrium p for Ψ : R+ × X → X is order stable (respectively, asymptotically . order stable if p is stable (respectively, asymptotically stable) for Ψ

P ROPOSITION 1.28. Let Ψ be a monotone local semiflow in a subset X of a strongly ordered Banach space Y , that extends to a monotone local semiflow in some open subset of Y . Assume p is an equilibrium having a neighborhood W that is attracted to a compact set K ⊂ X. If p is order stable (respectively, asymptotically order stable), it is stable (respectively, asymptotically stable). = K, there is P ROOF. Suppose p is order stable and let U be a neighborhood of p. As K a closed order neighborhood N0 of p such that N0 ∩ K ⊂ U ∩ K. By order stability there exists an order neighborhood N1 of p such that O(N1 ) ⊂ N0 . Compactness of N0 ∩ K implies there is an open set V ⊃ K there is an open set V ⊃ K such that N0 ∩ V ⊂ U . Because K attracts W , there is a neighborhood U2 ⊂ W of p and r 0 such that t r

)⇒ Ψt (U2 ) ⊂ V .

By continuity of Ψr at p = Ψr (p) there is a neighborhood U3 ⊂ U2 of p such that 0t r

)⇒ Ψt (U3 ) ⊂ V .

and thus O(U3 ) ⊂ V . Therefore N1 ∩ U3 is a neighborhood of p such that O(N1 ∩ U3 ) ⊂ O(N1 ) ∩ O(U3 ) ⊂ N0 ∩ V ⊂ U. This shows p is stable. Assume p is asymptotically order stable and choose an order neighborhood M ⊂ X of . We show that M ∩ W is in the basin of p for Ψ . Consider p that is attracted to p by Ψ arbitrary sequences {xk } in M ∩ W and tk → ∞ in [0, ∞). Fix u ≫ 0. By the choice of M there are positive numbers ǫk → 0 such that p − ǫk u ≪ Ψtk (xk ) ≪ p + ǫk u. This implies Ψtk (xk ) → p in X, because the order relation on X is closed and {Ψtk (xk )} is precompact in X by the choice of W and compactness of K.


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1.8. The search for stable equilibria The following results illustrate the usefulness of a dense set of quasiconvergent points. Φ denotes a strongly order preserving semiflow in X; Hypothesis (H) of Section 1.4 is still in force. P ROPOSITION 1.29. Assume Q is dense. Let p, q ∈ E be such that p < q, p is accessible from above, and q is accessible from below. Then there exists z ∈ X satisfying one of the following conditions: (a) p < z < q, and Φt (z) → p or Φt (z) → q; (b) p < z < q and z ∈ E; (c) z > p and p ∈ O(z), or z < q and q ∈ O(z). P ROOF. By SOP there are open neighborhoods U, V of p, q respectively and t0 0 such that Φt U Φt V for t t0 . Choose sequences xn → p in U and yn → q in V with p < xn , / O(xn ) and q ∈ / O(yn )), as otherwise (c) is satisfied. Then yn < q. We assume p ∈ t t0

)⇒ p < Φt (xn ) Φt (yn ) < q.

Choose open neighborhoods U1 , W, V1 of p, Φt0 (y1 ), q respectively such that for some t1 t0 : t t1

)⇒ Φt (U1 ) Φt (W ) Φt (V1 ).

Choose w ∈ Q ∩ W and a sequence sk → ∞, sk t1 such that Φsk (w) → e ∈ E. Fix m so large that xm ∈ U1 , ym ∈ V1 . Then for sufficiently large k, p < Φsk (xm ) Φsk (w) Φsk (ym ) < q. It follows that p e q. If e = p or q then ω(Φsk (w)) = p or q by the Convergence Criterion 1.4, giving (a) with z = Φsk (w). Therefore if (a) does not hold, (b) holds with z = e. The assumption in Proposition 1.29 that Q is dense can be considerably weakened, for example, to p (or q) being interior to Q: Assume y1 ∈ Int Q and set w = Φsk (w0 ), w0 ∈ (Int Q) ∩ Φsk −1 (W ), etc. In fact, density of Q can be replaced with the assumption that p or q lies in the interior of the set Q# of points x such that there is a sequence xi → x with limi→∞ dist(ω(xi ), E) = 0. Clearly Q# is closed and contains Q, so density of Q implies Q# = X. T HEOREM 1.30. Suppose X is normally ordered and the following three conditions hold: (a) Q is dense; (b) if e ∈ E and e is not accessible from above (below) then e = sup X (e = inf X); (c) there is a maximal totally ordered subset R ⊂ E that is nonempty and compact. Then R contains a stable equilibrium, an asymptotically stable equilibrium if R is finite.

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P ROOF. By Lemma 1.1, sup R (inf R) exists and is a maximal (minimal) element of E. We first prove that every maximal equilibrium q is in A+ . This holds vacuously when q = sup X. Suppose q = sup X. If q is in the orbit of some point > q then q ∈ A+ by Proposition 1.25(d). Hence we can assume: t 0, y > q

)⇒

Φt (y) > q.

By hypothesis we can choose y > q. By SOP there is an open neighborhood U of q and s > 0 such that Φs (y) Φs (U ). By hypothesis we can choose z ∈ U such that Φs (y) = Φs (z) and z > q. Set x2 = Φs (y), x1 = Φs z. Then x2 > x1 > q, By SOP and the assumption above there is a neighborhood V2 of x2 and t0 0 such that t > t0

)⇒ q < Φt (x1 ) Φt (V2 ).

Choose v ∈ V2 ∩ Q. Then q < Φt (v) for t t0 , hence q ω(v) = ω(Φt0 (v)) ⊂ E. Therefore Φt (v) → q by maximality of q, so and Proposition 1.25(d) implies q ∈ A+ , as required. The dual argument shows that every minimal equilibria is in A− . Assumption (c) and previous arguments establish that q = sup R and p = inf R satisfy p q and q ∈ A+ , p ∈ A− . Suppose p = q; in this case we prove q ∈ A. As q is both maximal and minimal in E, we have q ∈ A+ ∩ A− . If q is accessible from above and below then q ∈ A by Proposition 1.25(b). If q is not accessible from above then by hypothesis q = sup X, in which case the fact that q ∈ A− implies q ∈ A. Similarly, q ∈ A if q is not accessible from below. Henceforth we assume p < q. As R is compact and R ∩ S− = ∅ because p ∈ R, it follows that R contains the equilibrium r := sup(R ∩ S− ). Note that r ∈ S− , because this holds by definition of r if r is isolated in {r ′ ∈ R: r ′ r}, and otherwise r ∈ S− by Proposition 1.26(a). If r = q a modification of the preceding paragraph proves q ∈ S. Henceforth we assume r < q; therefore r is accessible from above. If r is not accessible from below then r = p = inf X so r ∈ S and we are done; so we may as well assume r is accessible from below as well as from above. If r is the limit of a sequence of equilibria > r then r ∈ S+ by the dual of Proposition 1.26, hence r ∈ S by Proposition 1.25(b). Therefore we can assume R contains a smallest equilibrium / S− by maximality of r. We apply Proposition 1.29 to r, r1 : among r1 > r. Note that r1 ∈ its conclusions, the only one possible here is that z > r and Φt (z) → r (and perhaps r ∈ O(z)). Therefore r ∈ S+ by Proposition 1.25(a), whence r ∈ S by 1.25(b). When R is finite, a modification of the preceding arguments proves max(R ∩ A− ) ⊂ A. Assumption (b) in the Theorem 1.30 holds for many subsets X of an ordered Banach space Y , including open sets, subcones of Y+ , closed order intervals, and so forth. This result is similar to Theorem 10.2 of Hirsch [73], which establishes equilibria that are merely order stable, but does not require normality. Assumption (c) holds when E is compact, and also in the following situation: X ⊂ Y where Y is an Lp space, 1 p < ∞, and E is a nonempty, closed, and order bounded subset of X; then every order bounded increasing or decreasing sequence converges. If (c) holds and some Φt is real analytic with spatial derivatives that are compact and


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strongly positive operators, then R is finite. This follows from the statements and proofs of Lemma 3.3 and Theorem 2 in Jiang and Yu [90]. For related results on stable equilibria see Jiang [86], Mierczyński [138,139], and Hirsch [69]. T HEOREM 1.31. Let Φ be a semiflow in a subset X of a strongly ordered Banach space Y , that extends to a strongly monotone local semiflow in some open subset of Y . Assume hypotheses (a), (b), (c) of Theorem 1.30 hold, and every equilibrium has a neighborhood attracted to a compact set. Let R ⊂ E be as in 1.30(c). Then R contains a stable equilibrium, and an asymptotically stable equilibrium when R is finite. (see Section 1.7). in X P ROOF. Our strategy is to apply Theorem 1.30 to the semiflow Φ Give X the metric coming from an order norm on Y ; this makes X is normally ordered. is SOP. Therefore R contains an equilibrium p that is stable Lemma 1.27 shows that Φ for Φ, by Theorem 1.30. This means p is order stable for Φ, whence Proposition 1.28 shows that p is stable for Φ. The final assertion follows similarly. Stable equilibria are found under various assumptions in Theorems 2.9, 2.10, 2.11, 2.26, 3.14, 4.12.

2. Generic convergence and stability 2.1. The sequential limit set trichotomy Throughout Section 2 we assume Hypothesis (H) of Section 1.4: Φ is a strongly order preserving semiflow in an ordered space X, with all orbit closures compact. The main result is that the typical orbit of an SOP semiflow is stable and approaches the set E of equilibria. Existence of stable equilibria is established under additional compactness assumptions. The index n runs through the positive integers. A point x is strongly accessible from below (respectively, above) if there exists a sequence {yn } converging to x such that yn < yn+1 < x (resp., yn > yn+1 > x). In this case we say {yn } strongly approximates x from below (resp., from above). The sequence {xn } is omega compact if n ω(xn ) is compact. Define sets BC, AC ⊂ X as follows: x ∈ BC ⇐⇒ x is strongly accessible from below by an omega compact sequence, x ∈ AC ⇐⇒ x is strongly accessible from above by an omega compact sequence.

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In this notation “B” stands for “below,” “A” for above, and “C” for “compact.” We will also use the following condition on a set W ⊂ X: (C) Every sequence {wn } in W that strongly approximates a point of W from below or above is omega compact. This does not assert that any point is strongly accessible from below or above. But if every point of W is accessible from above and W satisfies (C), then W ⊂ AC; and similarly for BC. The next two propositions imply properties stronger than (C). Recall that a map f : X → X is completely continuous provided f (B) is compact for every bounded set B ⊂ X; and f conditionally completely continuous provided f (B) is compact whenever B and f (B) are bounded subsets of X. The orbit of any set B ⊂ X is O(B) = t Φt (B). P ROPOSITION 2.1. Assume the following two conditions: (a) every compact set has a bounded orbit, and (b) Φs is conditionally completely continuous for some s > 0. If L ⊂ X is compact, then x∈L ω(x) is compact and this implies X has property (C).

P ROOF. O(L) is a bounded set by (a), and positively invariant, so (b) implies compactness of Φs (O(L)). As the latter set contains ω(x) for all x ∈ L, the first assertion is proved. The second assertion follows from precompactness of {xn }. P ROPOSITION 2.2. Assume W ⊂ X has the following property: For every x ∈ W there is a neighborhood Ux ⊂ X and a compact set Mx that attracts every point in Ux . Then O(x) is compact for every x ∈ W , and y∈Ux ω(y) is compact. If zn → x ∈ W then n ω(zn ) is compact, therefore W has property (C).

P ROOF. It is easy to see that O(x) is compact and y∈Ux ω(y) is compact because it lies in Mx . Fix k 0 such that zn ∈ Ux for all n k. Then ! n

ω(zn ) =

!

1nk

ω(zn ) ∪ Mx ,

which is the union of finitely many compact sets, hence compact. Condition (C) follows trivially. The key to stronger results on generic quasiconvergence and stability is the following result of Smith and Thieme [197]: T HEOREM 2.3 (Sequential Limit Set Trichotomy). Let {xñ } be an omega compact sequence strongly approximating z ∈ BC from below. Then there is a subsequence {xn } such that exactly one of the following three conditions holds:


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(a) There exists u0 ∈ E such that ω(xn ) < ω(xn+1 ) < ω(z) = {u0 } and lim dist ω(xn ), u0 = 0.

n→∞

In this case z ∈ C. (b) There exists u1 = sup{u ∈ E: u < ω(z)} and ω(xn ) = {u1 } < ω(z). In this case z ∈ Int C. Moreover z has a neighborhood W such that if w ∈ W , w < z then Φt (w) → u1 and Φt (w) > u1 for sufficiently large t. (c) ω(xn ) = ω(z) ⊂ E. In this case z ∈ Int Q. Moreover ω(w) = ω(z) ⊂ E for every w < z sufficiently near z. Note that z is convergent in (a), and strongly accessible from below by convergent points in (b). In (c), z is quasiconvergent and strongly accessible from below by quasiconvergent points. If z ∈ AC there is an analogous dual result, obtained by reversing the order relation in X. Although we do not state it formally, we will use it below. If z ∈ AC ∩ BC then both results apply. See Proposition 3.6 in Smith and Thieme [197]. P ROOF OF T HEOREM 2.3. By the Limit Set Dichotomy 1.16, either there exists a positive integer j such that ω(xñ ) = ω(x˜m ) for all m, n j , or else there exists a subsequence {xñi } such that ω(xñi ) < ω(xñi+1 ) for all i. Therefore there is a subsequence {xn } such that ω(xn ) < ω(xn+1 ) for all n, or ω(xn ) = ω(xn+1 ) for all n. Case I: ω(xn ) < ω(xn+1 ). We will see that (a) holds. The Limit Set Dichotomy 1.16 implies ω(xn ) ω(z). In fact, that ω(xn ) < ω(z). Otherwise ω(xk ) ∩ ω(z) = ∅ for some k, and the Limit Set Dichotomy implies the contradiction ω(xk ) = ω(z) ω(xk+1 ) > ω(xk ). Define K = ω(xn ), a nonempty compact invariant set. Consider the set 2 Λ = y: y = lim yn , yn ∈ ω(xn ) ⊂ K. n→∞

Clearly Λ is invariant and closed, and compactness of K implies Λ is compact and nonempty. We show that Λ is a single equilibrium. Suppose y, v ∈ Λ, so that yn → y, vn → v with yn , vn ∈ ω(xn ). Since yn < vn+1 and vn < yn+1 , we have y v and v y, so v = y. Thus we can set Λ = {u0 }, and invariance implies u0 ∈ E. The definition of Λ and compactness of K imply limn→∞ dist(ω(xn ), u0 ) = 0. From ω(xn ) < ω(xn+1 ) < ω(z) we infer ω(xn ) < u0 ω(z).

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If u0 ∈ ω(z) then ω(z) = {u0 } by Corollary 1.9, yielding (a). We show that u0 < ω(z) gives a contradiction. Choose a neighborhood W of ω(z) and t0 0 such that u0 Φt (W ) for all t t0 (by Lemma 1.3). There exists t1 > 0 such that Φt1 (z) ∈ W , and by continuity of Φt1 there exists m such that Φt1 (xm ) ∈ W . It follows that u0 Φt (xm ) for t t0 + t1 . As u0 ∈ E, we have u0 ω(xm ). But this contradicts ω(xm ) < u0 . Thus (a) holds in Case I. Case II: ω(xn ) = ω(xn+1 ) ⊂ E. Since xn < z, the Limit Set Dichotomy implies that either ω(xn ) = ω(z), which gives (c), or else ω(xn ) < ω(z), which we now assume. Choose an equilibrium u1 ∈ ω(x1 ). By Lemma 1.3 there exists an open set W containing ω(z) and t0 0 such that u1 Φt (W ) for all t t0 . Arguing as in Case I, we obtain u1 Φt (xm ) for some m and all large t. Since u1 ∈ ω(xm ), it follows that ω(xm ) = u1 by Corollary 1.9, and therefore ω(xn ) = {u1 } as asserted in case (b). Finally, if u ∈ E and u < ω(z), we argue as above that ω(xm ) u for some m, which implies u1 u. To prove z ∈ Int Q, use SOP to obtain a neighborhood Un of xn such that Φt (xn−1 ) Φt (Un ) Φt (xn+1 ) for all large t, implying Un ⊂ Q. A similar argument proves the analogous assertion in (b). The following addendum to the Sequential Limit Set Trichotomy provides important stability information. In essence, it associates various kinds of stable points to arbitrary elements z ∈ BC: P ROPOSITION 2.4. Assume X is normally ordered. In cases (a), (b) and (c) of the Sequential Limit Set Trichotomy, the following statements are valid respectively: (a) z and u0 are stable from below; (b) z is not stable from below, ω(z) is unstable from below, and u1 is asymptotically stable from above; (c) z is asymptotically stable from below, and z ∈ A. P ROOF. (a) follows from Proposition 1.26(a) and (b). (b) The first two assertions are trivial. To prove u1 ∈ A+ , take w = xn for some large n in the last assertion of (b) and apply 1.25(d) with a = u1 . (c) follows from 1.25(d), taking b = z. We expect in real world systems that observable motions are stable trajectories. Our next result implies stable trajectories approach equilibria. P ROPOSITION 2.5. S ∩ (BC ∪ AC) ⊂ Q. P ROOF. When z ∈ S ∩ (BC ∪ AC), only (a) and (c) of the Sequential Limit Set Trichotomy are possible, owing to continuity at z of the function x → ω(x). In both cases z ∈ Q. The inclusion S ⊂ Q suggests trajectories issuing from nonquasiconvergent points are unlikely to be observed; the next result implies that their limit sets are, not surprisingly, unstable. There are as many concepts of instability as there are of stability, but for our purposes the following very strong property suffices: A set M ⊂ X is unstable from above


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provided there is an equilibrium u > M such that ω(x) = {u} if u > x > y, y ∈ M. Such an equilibrium u is unique, and SOP implies it attracts all points < u in some neighborhood of u. Unstable from below is defined dually. T HEOREM 2.6. Assume z ∈ BC \ Q (respectively, z ∈ AC \ Q). Then ω(z) is unstable from below (resp., above). P ROOF. To fix ideas we assume z ∈ BC \ Q. Then there exists a sequence xn → z and an equilibrium u1 as in conclusion (b) of the Sequential Limit Set Trichotomy. Suppose u1 < x < y, y ∈ ω(z). SOP implies there exist open sets Wx and Wy containing x and y, respectively, and t0 0, such that Φt (Wx ) Φt (Wy ) for all t t0 . As Φs (z) ∈ Wy for some large s, by continuity Φs (xn ) ∈ Wy for some large n. Thus u1 Φt (x) Φt+s (xn ) for all t t0 . Letting t → ∞ and using the fact that ω(xn ) = {u1 }, we find that ω(x) = {u1 }. A set is minimal if it is nonempty, closed and invariant, and no proper subset has these three properties. Every positively invariant nonempty compact set contains a minimal set (by Zorn’s Lemma). A minimal set containing more than one point is called nontrivial. C OROLLARY 2.7. A compact, nontrivial minimal set M that meets BC (respectively, AC) is unstable from below (resp., above). P ROOF. Suppose z ∈ M ∩ BC. The assumptions on M imply M = ω(z) and M ∩ E = ∅. Therefore z ∈ BC \ Q, and instability follows from Theorem 2.6. When X is a convex subset of a vector space, an alternative formulation of Theorem 2.6 is that ω(z) belongs to the upper boundary of the basin of attraction of the equilibrium u1 . Corollary 2.7 implies that periodic orbits are unstable. Theorem 2.6 is motivated by Theorem 1.6 in Hirsch [79]. The following sharpening of Theorem 1.19, due to Smith and Thieme [199], is an immediate corollary of the Sequential Limit Set Trichotomy. T HEOREM 2.8. If J ⊂ X is a totally ordered arc having property (C), then J \ Q is a discrete, relatively closed subset of J ; hence it is countable, and finite when J is compact. P ROOF. Every limit point z of J \ Q is strongly accessible from above or below by a sequence {xñ } in J \ Q. As Property (C) implies J ⊂ BC ∪ AC, there is a sequence {xn } satisfying (a), (b) or (c) of Theorem 2.3 (or its dual result), all of which imply xn ∈ Q. Thus J \ Q contains none of its limit points, which implies the conclusion. The following result sharpens Theorems 1.30 and 2.8: P ROPOSITION 2.9. Assume X is normally ordered and every point is accessible from above and below. Let J ⊂ X be a totally ordered compact arc having property (C), with

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endpoints a < b such that ω(a) is an equilibrium stable from below and ω(b) is an equilibrium stable from above. Then J contains a point whose trajectory converges to a stable equilibrium. P ROOF. Denote by Cs (respectively: C+ , C− ) the set of convergent points whose omega limits belong to S (resp.: to S+ , S− ). Then C+ ∩ C− = Cs by Proposition 1.25(b). Set sup(J ∩ C− ) = z ∈ J . Case 1: z ∈ / C− . Then z > a. Choose a sequence x1 < x2 < · · · < z in J ∩ C− such that xn → z. By the Sequential Limit Set Trichotomy 2.3 it suffices to consider the following three cases: (a) There exists u0 ∈ E such that ω(xn ) < ω(xn+1 ) < ω(z) = {u0 }. This is not possible, because u0 ∈ S− by Proposition 2.4(a), yielding the contradiction z ∈ C− . (b) There exists u1 = sup{u ∈ E: u < ω(z)}, and for all n we have ω(xn ) = {u1 } < ω(z). Now 2.4(b) has u1 ∈ S+ , hence xn ∈ C+ . Therefore xn ∈ C+ ∩ C− = Cs , as required. (c) ω(xn ) = ω(z). This is not possible because xn ∈ C− and ω(z) = ω(xn ) implies the contradiction z ∈ C− . Thus (b) holds, validating the conclusion when z ∈ / C− . Case 2: z ∈ C− . If z = b then z ∈ C+ ∩ C− = Cs and there is nothing more to prove. Henceforth we assume z < b. The closed subinterval K ⊂ J with endpoints z, b satisfies the hypotheses of the theo/ C+ rem. Set inf(K ∩ C+ ) = w ∈ K. The dual of the reasoning above shows that if w ∈ then the conclusion of the theorem is true. From now on we assume w ∈ C+ . If w = z there is nothing more to prove, so we also assume w > z. Let L ⊂ K be the closed subinterval with endpoints w and z. Let {x¯n } be a sequence in L converging to w from below. One of the conclusions (a), (b) or (c) of 2.3 holds. Referring to the corresponding parts of 2.4, we see in case (a) that ω(w) is an equilibrium u¯ 0 that is stable from below; but w > z, so this contradicts the definition of z. If (b) holds, ω(x¯n ) is an equilibrium u¯ 1 stable from above. But x¯n < w, so this contradicts the definition of w. In case (c) we have for all n that ω(x¯n ) = ω(w), which is an equilibrium stable from above. But x¯n < w for n > 1, again contradicting the definition of w. In the following result the assumption on equilibria holds when Φ has a global compact attractor. P ROPOSITION 2.10. Assume X is an open subset of a strongly ordered Banach space, Φ is strongly monotone, and every equilibrium has a neighborhood attracted to a compact set. Let J ⊂ X be a totally ordered compact arc, with endpoints a < b such that ω(a) is


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an equilibrium stable from below and ω(b) is an equilibrium stable from above. Then J contains a point whose trajectory converges to a stable equilibrium. in the normally ordered P ROOF. Apply Proposition 2.9 to the to the SOP semiflow Φ (see Section 1.7), to obtain an equilibrium p that is stable for Φ. This means p is space X order stable for Φ, hence stable for Φ by Proposition 1.28. C OROLLARY 2.11. Let X be a p-convex open set in an ordered Banach space Y . Assume Φ has a compact global attractor. Suppose that either Y is normally ordered, or Y is strongly ordered and Φ is strongly monotone. Then: (i) There is a stable equilibrium. (ii) Let u, v ∈ X be such that u < v and there exist real numbers r, s > 0 such that u < Φr (u), Φs (v) < v. Then there is a stable equilibrium in [u, v]. In case (ii) with Y normally ordered, the hypothesis of a global attractor can be replaced the assumption that the line segment joining u to v from satisfies condition (C). P ROOF. We first prove (ii). Monotonicity shows that ω(x) ⊂ [u, v] for all x ∈ [u, v]. The Convergence Criterion implies Φt (u) → a ∈ E ∩ [u, v],

Φt (v) → b ∈ E ∩ [u, v].

We claim that a ∈ S− and b ∈ S+ , and a ∈ S is stable if a = b. When Y is normal this follows from Propositions 1.25(b) and (d), and it is easy to prove directly when Φ is strongly monotone. Suppose a < b. By p-convexity and Theorems 2.9 and 2.10, the line segment from a to b lies in [u, v] ∩ X and contains a point whose x such that ω(x) is a stable equilibrium z. As noted above, z ∈ [u, v]. We prove (i) by finding u and v as in (ii). By Theorem 2.8 and compactness of the global attractor, there is a minimal equilibrium p and a maximal equilibrium q > p. As X is open, it contains a totally ordered line segment J < p. By Theorem 1.19 J contains a quasiconvergent point u < p. As ω(u) p, minimality of p implies Φt (u) → p. Similarly there exist v > q with Φt (v) → q. It follows from SOP that u < Φr (u), Φs (v) < v for some r, s > 0. For strongly monotone semiflows, the existence of order stable equilibria in attractors was treated in Hirsch [68,69,73].

2.2. Generic quasiconvergence and stability The following result adapted from Smith and Thieme [197] refines Theorems 1.22 and 1.21: T HEOREM 2.12. (i) AC ∪ BC ⊂ Int Q ∪ C. Therefore if AC ∪ BC is dense, so is Q. (ii) (Int AC) ∪ (Int BC) ⊂ Int Q. Therefore if (Int AC) ∪ (Int BC) is dense, so is Int Q.

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P ROOF. Every z ∈ BC is the limit of an omega compact sequence x1 < x2 < · · · such that (a), (b) or (c) of the Sequential Limit Set Trichotomy Theorem 2.3 holds, and z ∈ Int Q ∪ C in each case; the proof for AC is similar. To prove (ii), assume z ∈ Int BC. If (a) holds for every point of a neighborhood W of z, then W ⊂ C, whence z ∈ Int Q. If there is no such W , every neighborhood of z contains a point for which (b) or (c) holds, hence z ∈ Int Q. Similarly for z ∈ Int AC. The next result extends Theorems 8.10 and 9.6 of Hirsch [73] and Theorem 3.9 of Smith and Thieme [197]: T HEOREM 2.13. Assume X is normally ordered and Int(BC ∪ AC) is dense. Then A ∪ Int C is dense. P ROOF. We argue by contradiction. If A ∪ Int C is not dense, there exists an open set U such that U ∩ A = ∅ = U ∩ Int C. Suppose z ∈ U ∩ BC, and let {xn } be a sequence in U strongly approximating z from below. Conclusion (b) of the Sequential Limit Set Trichotomy 2.3 is not possible because / A (see Proposition 2.4(c)). Therefore z∈ / Int C, and conclusion (c) is ruled out because z ∈ conclusion (a) holds, which makes z convergent; likewise when z ∈ U ∩ AC. Thus we have C ⊃ U ∩ (BC ∪ AC), so Int C ⊃ U ∩ Int(BC ∪ AC). But the latter set is nonempty by the density hypothesis, yielding the contradiction U ∩ Int C = ∅. The following theorem concludes that generic trajectories are not only quasiconvergent, but also stable. Its full force will come into play in the next subsection, under assumptions entailing a dense open set of convergent points. T HEOREM 2.14. If X is normally ordered and Int(BC ∩ AC) is dense, then Int(Q ∩ S) is dense. P ROOF. Int Q is dense by Theorem 2.12. To prove density of Int S, it suffices to prove that if z ∈ Int(BC ∩ AC), then every open neighborhood U of z meets Int S. We can assume z∈ / A because A ⊂ Int S. Let {xn } be an omega compact sequence strongly approximating z from below. Suppose (b) or (c) of the Sequential Limit Set Trichotomy 2.3 holds. Then xm ∈ U for m m0 . Fix m m0 . It follows from Proposition 1.25(d) (with a = xm , x = xm+1 , b = xm+2 ) that xm+1 ∈ A, hence z ∈ A; this is proved similarly when {xn } strongly approximates z from above. Henceforth we can assume z belongs to the open set W = Int(BC ∩ AC) \ A, and consequently that there are omega compact sequences {xn }, {yn } strongly approximating z from below and above respectively, for which Theorem 2.3(a) and its dual hold respectively. Then Proposition 1.26 implies z ∈ S+ ∩ S− , whence z ∈ S by Proposition 1.25(b). Thus the open set W is contained in Int S, and we have proved Int S is dense. It follows that Int S ∩ Int Q is dense.


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2.3. Improving the limit set dichotomy for smooth systems The aim now is to strengthen the Limit Set Dichotomy with additional hypotheses, especially smoothness, in order to obtain the following property: (ILSD) A semiflow satisfies the Improved Limit Set Dichotomy if x1 < x2 implies that either (a) ω(x1 ) < ω(x2 ), or (b) ω(x1 ) = ω(x2 ) = e ∈ E. We begin with some definitions. Let X be a subset of the Banach space Y . A map f : X → Y is said to be locally C 1 at p ∈ X if there exists a neighborhood U of p in X and a continuous quasiderivative map f ′ : U → L(Y ), where L(Y ) is the Banach space of bounded operators on Y , such that f (x) − f (x0 ) = f ′ (x0 )(x − x0 ) + φ(x, x0 )|x − x0 |,

x, x0 ∈ U

with φ(x, x0 ) → 0 as x → x0 . The following result gives a setting where the quasiderivative is uniquely determined by f . We denote the open ball in Y of center p and radius r by BY (p, r) := {y ∈ Y : |y − p| < r}. L EMMA 2.15. Let p ∈ X ⊂ Y where Y is a strongly ordered Banach space. Assume f : X → Y is locally C 1 at p, and suppose that either BY (p, r) ∩ Y+ ⊂ X or BY (p, r) ∩ (−Y+ ) ⊂ X for some r > 0. Then f ′ (p) is uniquely defined. P ROOF. Suppose BY (p, r) ∩ Y+ ⊂ X, the other case being similar. Fix w ≫ 0 and let y ∈ Y . As w + y/n := kn 0 for large n, y = n(kn − w) so Y = Y+ − Y+ . Assume f (x) − f (p) = A(x − p) + φ(x, p)|x − p| = B(x − p) + ψ(x, p)|x − p|, where A, B ∈ L(Y ) and φ, ψ → 0 as x → p in X. It suffices to show that Av = Bv for all v 0. The segment x = p + sv ∈ X for all small s 0. Inserting it in the formula above, dividing by s, and letting s → 0 yields the desired result. Let Φ be a monotone semiflow on the subset X of the strongly ordered Banach space Y . Concerning X and the set of equilibria E, we assume the following condition on the pair (Y, X): (OC) Either X is an order convex subset of Y or E ⊂ Int X. For each e ∈ E there exists r > 0 such that either BY (e, r) ∩ Y+ ⊂ X or BY (e, r) ∩ (−Y+ ) ⊂ X. This relatively minor restriction is automatically satisfied if X is an open set, an order interval, or the cone Y+ . The second assertion of (OC) trivially holds if E ⊂ Int X.

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We will also assume the following two conditions hold for some τ > 0. A compact, strongly positive linear operator is called a Krein–Rutman operator. (M) x1 < x2 )⇒ Φτ (x1 ) ≪ Φτ (x2 ) (D*) Φτ is locally C 1 at each e ∈ E, with Φτ′ (e) a Krein–Rutman operator. As motivation for (D*), consider the case that X is an open set in Y and Φτ is C 1 . If x ∈ X, y ∈ Y+ , h > 0, and x +hy ∈ X, then (Φτ (x +hy)−Φτ (x))/ h 0 by monotonicity; on taking the limit as h → 0, we get Φτ′ (x)y 0. Consequently, Φτ′ (x)Y+ ⊂ Y+ , and hence the assumption that Φτ′ (x) is strongly positive is not such a severe one. Typically, one usually must verify it anyway to prove that Φτ is strongly monotone. Observe that (M) implies that Φ is strongly order preserving on X. T HEOREM 2.16 (Improved Limit Set Dichotomy). Let Φ be a monotone semiflow on a subset X of the strongly ordered Banach space Y for which (OC), (M), and (D*) are satisfied. Then (ILSD) holds. In particular, (ILSD) holds if X is open, the semiflow Φ continuously differentiable and strongly monotone, and the derivative Φt′ (e) is a Krein–Rutman operator at each e ∈ E. Before giving the proof, we explore the spectral and dynamical implications of (D*). 2.3.1. The Krein–Rutman theorem The spectrum of a linear operator A : Y → Y is denoted by Spec(A). When A is compact (i.e., completely continuous), Spec(A) consists of a countable set of eigenvalues and perhaps 0, and the eigenvalues have no accumulation point except possibly 0. Let ρ(A) be the spectral radius of A, that is, ρ(A) = max{|λ|: λ ∈ Spec(A)}. Denote the null space of A by N (A) and the range by Im(A). The set KR(Y ) of Krein–Rutman operators on Y is given the metric induced by the uniform norm. T HEOREM 2.17 (Krein–Rutman). Let A ∈ KR(Y ) and set r = ρ(A). Then Y decomposes into a direct sum of two closed invariant subspaces Y1 and Y2 such that Y1 = N (A − rI ) is spanned by z ≫ 0 and Y2 ∩ Y+ = {0}. Moreover, the spectrum of A|Y2 is contained in the closed ball of radius ν < r in the complex plane. See Krein and Rutman [104], Takáˇc [214] or Zeidler [244] for proofs. It follows that each A ∈ KR(Y ) has a unique unit eigenvector z(A) ∈ Y+ , and z(A) ∈ Int Y+ , Az(A) = ρ(A)z(A). L EMMA 2.18. ρ(A) and z(A) are continuous functions of A ∈ KR(Y ). P ROOF. The upper semicontinuity of the spectral radius follows from the upper semicontinuity of the spectrum as a function of the operator (Kato [92]). The lower semicontinuity follows from the lower semicontinuity of isolated parts of the spectrum (Kato [92, Chapter IV, Theorem 3.1, Remark 3.3, Theorem 3.16]). Let PA be the projection


275

onto N (A) − ρ(A)I ) along Im(A − ρ(A)I ). Continuity of A → PA is proved in [92, Chapter IV, Theorem 3.16]. Let An → A in KR(Y ) and set zn = z(An ), z = z(A). Then (I − PA ))zn = (PAn − PA )zn → 0 as n → ∞, and {PA zn } is precompact, so {zn } is precompact. If zni → u for some subsequence, then PA u = lim Ani zni = lim ρ(Ani )zni = ρ(A)u. Uniqueness of the positive eigenvector for A (Theorem 2.17) implies u = z and zn → z. For technical reasons it is useful to employ a norm that is more compatible with the partial order. If w ∈ Int Y+ is fixed, then the set U = {y ∈ Y : −w ≪ y ≪ w} is an open neighborhood of the origin. Consequently, if y ∈ Y , then there exists t0 > 0 such that t0−1 y ∈ U , hence, −t0 w ≪ y ≪ t0 w. Define the w-norm by

y w = inf{t > 0: −tw y tw}. y ∈ Y+ . Since w ∈ Int Y+ , there exists δ > 0 such that for all y ∈ Y \ {0} we have w ± δ |y| Thus

y w δ −1 |y| holds for all y ∈ Y , implying that the w-norm is weaker than the original norm. In fact, the two norms are equivalent if Y+ is normal, but we will have no need for this result. See Amann [6] and Hirsch [73] for more results in this direction. It will be useful to renormalize the positive eigenvector z(A) for A ∈ KR(Y ). The next result says this can be done continuously. Continuity always refers to the original norm topology on Y unless the contrary is explicitly stated. L EMMA 2.19. Let Z(A) = z(A)/ z(A) w and β(A) = sup{β > 0: Z(A) βw}. Then β(A) > 0, Z(A) β(A)w, and the maps A → Z(A) and A → β(A) are continuous on KR(Y ). P ROOF. Since the w-norm is weaker than the original norm, the map A → z(A) w is continuous. This implies that Z(A) is continuous in A. It is easy to see that β(A) > 0. Let ǫ > 0 satisfy 2ǫ < β(A) and let An → A in KR(Y ). Then −ǫw Z(A) − Z(An ) ǫw for all large n by continuity of Z and because the w-norm is weaker than the original norm. Therefore, Z(An ) = Z(An ) − Z(A) + Z(A) (β(A) − ǫ)w, so β(An ) β(A) − ǫ for all large n. Similarly, Z(A) = Z(A) − Z(An ) + Z(An ) (β(An ) − ǫ)w for all large n, so β(A) β(An ) − ǫ for all large n. Thus, β(A) − ǫ β(An ) β(A) + ǫ holds for all large n, completing the proof. The key to improving the Limit Set Dichotomy is to show that the omega limit set of a point x that is quasiconvergent but not convergent, is uniformly unstable in the linear approximation. The direction of greatest instability at e ∈ ω(x) is the positive direction z(e) := z(Φτ′ (e)). The number ρ(e) := ρ(Φτ′ (e)) gives a measure of the instability.

276


Nonordering of Limit Sets means that positive directions are, in some rough sense, “transverse” to the limit set. Thus our next result means that the limit set is uniformly unstable in a transverse direction. L EMMA 2.20. Assume (D*). Let x be quasiconvergent but not convergent. Then ρ(e) > 1 for all e ∈ ω(x). P ROOF. Fix e ∈ ω(x). Since ω(x) is connected, e is the limit of a sequence {en } in ω(x) ∩ U \ {e0 }, where U is the neighborhood of e in the definition of Φτ is locally C 1 at e. Then e0 − en = Φτ (e) − Φτ (en ) = Φτ′ (e)(e − en ) + o |e − en | ,

where o(|e − en |)/|e − en | → 0 as n → ∞. Put vn = (e − en )/|e − en |. Then vn = Φτ′ (e)vn + rn ,

rn → 0,

n → ∞.

The compactness of Φτ′ (e) implies that vn has a convergent subsequence vni ; passing to the limit along this subsequence leads to v = Φτ′ (e)v for some unit vector v. Thus ρ(e) 1. If ρ(e) = 1, then the Krein–Rutman Theorem implies v = rz(e) where r = ±1. Consequently, (e − eni )/|e − eni | → rz(e) as i → ∞. It follows that e ≪ eni or e ≫ eni for all large i, contradicting the Nonordering of Limit Sets. P ROOF OF T HEOREM 2.16. By the Limit Set Dichotomy (Theorem 1.16), it suffices to prove: If x1 < x2 and ω(x1 ) = ω(x2 ) = K ⊂ E, then K is a singleton. K is compact and connected, unordered by the Nonordering of Limit Sets, and consists of fixed points of Φτ . Arguing by contradiction, we assume K is not a singleton. Set vn = Φnτ (x1 ), un = Φnτ (x2 ). Then dist(K, un ) → 0 and dist(K, vn ) → 0 as n → ∞. Moreover (M) and the final assertion of the Limit Set Dichotomy imply un − vn ≫ 0,

un − vn → 0.

Fix w ≫ 0 and define real numbers αn = sup{α ∈ R: α 0, αw un − vn }. Then αn > 0 and αn → 0. To simplify notation, define S : X → X by S(x) := Φτ (x). Choose en ∈ K such that vn − en → 0 as n → ∞. By Lemma 2.20, local smoothness of Φτ and compactness of K, there exists r > 1 such that ρ(e) > r for all e ∈ K. Let zn = Z(en ) be the normalized positive eigenvector for S ′ (en ) = Φτ′ (en ) so zn w = 1 and zn w. By Lemma 2.19, there exists ǫ > 0 such that β(en ) ǫ for all n. In particular, w zn ǫw for all n.


277

Fix a positive integer l such that r l ǫ > 1. For each e ∈ K, by (D*) we can choose an open neighborhood We of e in X and a continuous map S ′ : We → L(Y ) such that for x, x0 ∈ We we have Sx − Sx0 = S ′ (x0 )(x − x0 ) + φ(x, x0 )|x − x0 |,

lim φ(x, x0 ) = 0.

x→x0

Putting x0 = e and estimating norms, one easily sees that there exists a convex open neighborhood Ue ⊂ We of e such that S i (Ue ) ⊂ We for 1 i l. Furthermore, a simple induction argument implies that S l is locally C 1 at e with quasiderivative l ′ S : Ue → L(Y ),

l ′ S (x) = S ′ S l−1 x ◦ S ′ S l−2 x ◦ · · · ◦ S ′ (x).

By compactness of K there is a finite subset {e1 , . . . , eν } ⊂ K such that the sets Uej cover K. Set Uj = Uej , Wj = Wej . Then K⊂

ν !

Uj ,

j =1

S i (Uj ) ⊂ Wj

(1 i l),

and for z, z0 ∈ Uj ′ S l (z) − S l (z0 ) = S l (z0 )(z − z0 ) + φl,j (z, z0 )|z − z0 |,

lim φl,j (z, z0 ) = 0,

z→z0

and the usual chain rule expresses (S l )′ in terms of S ′ . By (OC), either X is order convex in Y or E ⊂ Int X. In the order convex case, from vn ≪ vn + αn w un we infer that vn + sαn w ∈ X for all s ∈ [0, 1]. Since vn − en → 0, vn − un → 0, and αn → 0, for sufficiently large n there exists j (n) ∈ {1, . . . , ν} such that Uj (n) contains the points vn , un , en , and vn + sαn w for all s ∈ [0, 1]. When E ⊂ Int X the same conclusion holds, and we can take Uj , Vj to be open in Y . Lemma 2.15 justifies the application of the fundamental theorem of calculus to the map [0, 1] → X, s → S l (vn + sαn w), leading to

and

′ S l (vn + αn w) − S l (vn ) = S l (en )(αn w) + αn δn

δn =

0

1

′ ′ S l (vn + ηαn w) − S l (en ) w dη.

Using that vn + αn w − en → 0, K is compact, and (S l )′ is continuous, it is easy to show that ′ ′ lim max S l (vn + ηαn w) − S l (en ) w = 0.

n→∞ 0η1

278


It follows that dn := δn w → 0 as n → ∞. Because w zn ǫw ≫ 0 and δn −dn w, for sufficiently large n we have: ′ S l (vn + αn w) − S l (vn ) S l (en ) αn w − αn dn w l S ′ (en ) αn w − αn dn w r l αn zn − αn dn w

(r l ǫ − dn )αn w αn w, and therefore

un+l = S l (un ) S l (vn + αn w) S l vn + αn w = vn+l + αn w. Thus αn w un+l − vn+l , so the definition of αn+l implies αn+l αn > 0 for all sufficiently large n. Therefore the sequence {αi }i∈N+ , which converges to 0, contains a nondecreasing positive subsequence {αn+kl }k∈N+ . This contradiction implies K is a singleton. A drawback of the Improved Limit Set Dichotomy, Theorem 2.16, is that the topology on X comes from a strongly ordered Banach space Y ⊃ X, severely limiting its application to infinite-dimensional systems. The following extension permits use of (ILSD) in more general spaces: P ROPOSITION 2.21. Let X 1 , X 0 be ordered spaces such that X 1 ⊂ X 0 and the inclusion map j : X 1 ֒→ X 0 is continuous and order preserving. For k = 0, 1 let Φ k be a monotone semiflow on X k with compact orbit closures. Assume for all t > 0 that Φt0 maps X 0 continuously into X 1 , and Φt0 |X 1 = Φt1 . If (ILSD) holds for Φ 1 , it also holds for Φ 0 . P ROOF. Denote the closure in X k of any S ⊂ X k by Ck S. For k ∈ {0, 1} and x ∈ X k , let Ok (x) and ωk (x) respectively denote the orbit and omega limit set of x. The hypotheses imply that the compact set C0 O0 (x), which is positively invariant for Φ 0 , is mapped homeomorphically by Φ10 onto C1 O1 (y) ⊂ X 1 , which is positively invariant for Φ 1 . As Φ 0 and Φ 1 coincide in X 1 , we see that ω0 (x) = ω1 (y) as compact sets. Hence Φ 0 and Φ 1 have the same collection of omega limit sets, which implies the conclusion. T HEOREM 2.22 (Improved Sequential Limit Set Trichotomy). Assume (ILSD). Let {xñ } be a sequence approximating z ∈ BC from below, with n ω(xñ ) compact. Then there is a subsequence {xn } such that exactly one of the following three conditions holds for all n: (a) There exists u0 ∈ E such that ω(xn ) < ω(xn+1 ) < ω(z) = {u0 } and lim dist ω(xn ), u0 = 0.

n→∞


279

(b) There exists u1 = sup{u ∈ E: u < ω(z)}, and ω(xn ) = {u1 } < ω(z). In this case z ∈ Int C. Moreover z has a neighborhood W such that if w ∈ W , w < z then Φt (w) → u1 and Φt (w) > u1 for sufficiently large t. (c′ ) There exists u2 ∈ E such that ω(xn ) = ω(x0 ) = u2 . Note that z is convergent in (a), strongly accessible from below by convergent points in (b), and convergent in (c′ ). P ROOF. Conclusions (a) and (b) are the same as in the Sequential Limit Set Trichotomy, Theorem 2.3. If 2.3(c) holds, then (c′ ) follows from (ILSD). P ROPOSITION 2.23. Assume (ILSD). If x ∈ BC \ C then ω(x) is unstable from below. If x ∈ AC \ C then ω(x) is unstable from above. P ROOF. This is just Theorem 2.6 if x ∈ / Q. If x ∈ BC ∩ (Q \ C), we must have conclusion (b) of Theorem 2.22. This provides u1 ∈ E such that ω(xn ) = {u1 } for all n, and the remainder of the proof mimics that of Theorem 2.6. A consequence of Proposition 2.23 is that if x ∈ BC ∩ AC is nonconvergent, then ω(x) lies in both the upper boundary of the basin of attraction of an equilibrium u0 and the lower boundary of the basin of attraction of an equilibrium v0 , where u0 < L < v0 . Thus ω(x) forms part of a separatrix separating the basins of attraction of u0 and v0 .

2.4. Generic convergence and stability The following result concludes that the set C of convergent points is dense and open in totally ordered arcs: T HEOREM 2.24. Assume (ILSD) and let J ⊂ X be a totally ordered arc having property (C). Then J \ C is a discrete, relatively closed subset of J ; hence it is countable, and finite when J is compact. P ROOF. The proof is like that of Theorem 2.8, using the Improved Limit Set Trichotomy 2.22 instead of the Sequential Limit Set Trichotomy 2.3. We can now prove the following generic convergence and stability results: T HEOREM 2.25. Assume (ILSD). (a) AC ∪ BC ⊂ Int C ∪ C. In particular, if AC ∪ BC is dense, so is Int C is dense. (b) If Int(BC ∩ AC) is dense and X is normally ordered, then Int(C ∩ S) is dense.

280


P ROOF. The proof of (a) is similar to that of Theorem 2.12: take p ∈ X \ Int C and use the Improved Limit Set Trichotomy (Theorem 2.22), instead of the Limit Set Trichotomy, to show that p ∈ Int C ∪ C. Conclusion (b) follows from (a) and Theorem 2.14. T HEOREM 2.26. Assume X is a subset of a strongly ordered Banach space Y , and a dense open subset of X is covered by totally ordered line segments. Let (M) and (D*) hold. Then: (a) The set of convergent points has dense interior. (b) Suppose Y is normally ordered. Then the set of stable points has dense interior. (c) Assume Y is normally ordered; X is open or order convex or a subcone of Y+ ; and every closed totally ordered subset of E is compact. Then there is a stable equilibrium, and an asymptotically stable equilibrium when E is finite. P ROOF. The assumption in (a) implies BC ∩ AC has dense interior and condition (OC) holds. Therefore the Improved Limit Set Dichotomy (ILSD) holds by Theorem 2.16, so (a) and (b) follow from Theorem 2.25(a). Conclusion (c) is a consequence of (a) and Theorem 1.30. As most orbits with compact closure converge to an equilibrium, it is natural to investigate the nature of the convergence. It might be expected that most trajectories converging to a stable equilibrium are eventually increasing or decreasing. We quote a theorem of Mierczyński that demonstrates this under quite general conditions for smooth strongly monotone dynamical systems, including cases when the equilibrium is not asymptotically stable in the linear approximation. Mierczyński assumes the following hypothesis: (M1 ) X is an open set in a strongly ordered Banach space Y . Φ is C 1 on (0, ∞) × X and strongly monotone, Φt′ (x) is strongly positive for all t > 0, x ∈ X, and Φ1′ (x) is compact. The following local trichotomy due to Mierczyński [138] builds on earlier work of Poláˇcik [161]: T HEOREM 2.27. Assume (M1 ). Then each equilibrium e satisfying ρ(Φ1′ (e)) 1 belongs to a locally invariant submanifold Σe of codimension one that is smooth and unordered and has the following property. If limt→∞ Φt (x) = e, there exists t0 0 such that one of the following holds as t → ∞, t t0 : (i) Φt (x) decreases monotonically to e; (ii) Φt (x) increases monotonically to e; (iii) Φt (x) ∈ Σe . Mierczyński also provides further important information: The trajectories in cases (i) and (ii) lie in curves tangent at e to the one-dimensional principle eigenspace Y1 of Φ1′ (e) described in the Krein–Rutman Theorem 2.17. The hypersurface Σe is locally unique in a neighborhood of e. Its tangent space is the closed complementary subspace Y2 , hence Σe is transverse to z = z(Φ1′ (e)) ≫ 0 at e. Strong monotonicity implies that when (i) or (ii) holds, e is asymptotically stable for the induced local flow in Σe , even when e is not stable.


281

2.4.1. Background and related results Smith and Thieme [197,199] introduced the compactness hypothesis (C) and obtained the Sequential Limit Set Trichotomy. This tool streamlines many of the arguments and leads to stronger conclusions so the presentation here follows [197,199]. Takáˇc [210] extends the compactness hypothesis, which leads to additional stability concepts. The results of Smith and Thieme [199] on generic convergence for SOP semiflows were motivated by earlier work of Poláˇcik [160], who obtained such results for abstract semilinear parabolic evolution systems assuming less compactness but more smoothness than Smith and Thieme. The set A of asymptotically stable points can be shown to be dense under suitable hypotheses. See, e.g., Hirsch [73, Theorem 9.6]; Smith and Thieme [197, Theorems 3.13 and 4.1]. Hirsch [69] shows that if K is a nonempty compact, invariant set that attracts all points in some neighborhood of itself, then K contains an order-stable equilibrium. It is not necessary to assume, as we have done here, that the semiflow is globally defined, that is, that trajectories are defined for all t 0; many of the results adapt to local semiflows. See Hirsch [73], Smith and Thieme [199].

3. Ordinary differential equations Throughout this section Rn is ordered by a cone K with nonempty interior. Our first objective is to explore conditions on a vector field that make the corresponding local semiflow monotone with respect to the order defined by K. It is convenient to work with timedependent vector fields. We then investigate the long-term dynamics of autonomous vector fields f that are K-cooperative, meaning that K is invariant under the forward flow of the linearized system. These results are applied to competitive vector fields by the trick of time-reversal. In fairly general circumstances, limit sets of cooperative or competitive systems in Rn are invariant sets for systems in Rn−1 . This leads to particularly sharp theorems for n = 2 and 3. A cone is polyhedral if it is the intersection of a finite family of closed half spaces. For example, the standard cone Rn+ is polyhedral, while the ice-cream cone is not. The dual cone to K is the closed cone K ∗ in the dual space (Rn )∗ of linear functions on n R , defined by ∗ K ∗ = λ ∈ Rn : λ(K) 0 .

To λ ∈ K ∗ we associate the vector a ∈ Rn such that λ(x) = a, x where a, x denotes the standard inner product on Rn . Under this association K ∗ is canonically identified with a cone in Rn , namely, the set of vectors a such that a is normal to a supporting hyperplane H of K, and a and K lie in a common halfspace bounded by H . We use the following simple consequence of general results on the separation of two closed convex sets: x∈K

⇐⇒ λ(x) 0 (λ ∈ K ∗ ).

282


See, e.g., Theorem 1.2.8 of Berman et al. [18]. P ROPOSITION 3.1. If x ∈ K, then x ∈ Int K if and only if λ(x) > 0 for all λ ∈ K ∗ \ {0}. P ROOF. Suppose x ∈ Int K, λ ∈ K ∗ \ {0}, and v ∈ X satisfies λ(v) = 0. Then x ± ǫv ∈ K for sufficiently small ǫ > 0, so λ(x ± ǫv) = λ(x) ± ǫλ(v) 0, implying that λ(x) > 0. To prove the converse, assume µ(x) > 0 for all functionals µ in the compact set Γ = {λ ∈ K ∗ : λ = 1}. As inf{µ(x): µ ∈ Γ } > 0, continuity of the map (x, λ) → λ(x) implies µ(y) > 0 for all y in some neighborhood U of x and all µ ∈ Γ . If λ ∈ K ∗ then λ −1 λ ∈ Γ and therefore λ(y) > 0 for all y ∈ U . This proves U ⊂ K. An immediate consequence of Proposition 3.1 is that if x ∈ ∂K, then there exists a nontrivial λ ∈ K ∗ such that λ(x) = 0. 3.1. The quasimonotone condition Let J ⊂ R be a nontrivial open interval, D ⊂ Rn an open set and f : J × D → Rn a locally Lipschitz function. We consider the ordinary differential equation x ′ = f (t, x).

(3.1)

For every (t0 , x0 ) ∈ J × D, the initial value problem x(t0 ) = x0 has a unique noncontinuable solution defined on an open interval J (t0 , x0 ) ⊂ R. We denote this solution by t → x(t, t0 , x0 ). The notation x(t, t0 , x0 ) will carry the tacit assumption that (t0 , x0 ) ∈ J × D and t ∈ J (t0 , x0 ). For fixed s0 , t0 the map x0 → x(s0 , t0 , x0 ) is a homeomorphism between open subsets of Rn , the inverse being x0 → x(t0 , s0 , x0 ). System (3.1) is called monotone if x0 x1 )⇒ x(t, t0 , x0 ) x(t, t0 , x1 ). The time-dependent vector field f : J × D → Rn satisfies the quasimonotone condition in D if for all (t, x), (t, y) ∈ J × D and φ ∈ K ∗ we have: (QM) x y and φ(x) = φ(y) implies φ(f (t, x)) φ(f (t, y)). The quasimonotone condition was introduced by Schneider and Vidyasagar [177] for finite-dimensional, autonomous linear systems and used later by Volkmann [224] for nonlinear infinite-dimensional systems. The following result is inspired by a result of Volkmann [224] and work of W. Walter [227]. See also Uhl [221], Walcher [226]. T HEOREM 3.2. Assume f satisfies (QM) in D, t0 ∈ J , and x0 , x1 ∈ D. Let ≺ denote any one of the relations , 0. Denote by x(t) := x(t, t0 , x0 ) and let yǫ (t) := x(t, t0 , xǫ , ǫ) denote the solution of the initial value problem x ′ (t) = fǫ (t, x), x(t0 ) = xǫ . It is well known that yǫ (t) is defined on [t0 , t1 ] for all sufficiently small ǫ. We show that x(t) ≪ yǫ (t) for t0 t t1 and all sufficiently small ǫ > 0. If not, then as x(t0 ) ≪ yǫ (t0 ), there would exist ǫ > 0 and s ∈ (t0 , t1 ] such that x(t) ≪ yǫ (t) for t0 t < s and yǫ (s) − x(s) ∈ ∂K. By Proposition 3.1, there exists a nontrivial φ ∈ K ∗ such that φ(yǫ (s) − x(s)) = 0 but φ(yǫ (t) − x(t)) > 0 for t0 t < s. It follows that d φ yǫ (t) − φ x(t) 0, dt t=s hence

φ f s, yǫ (s) < φ f s, yǫ (s) + ǫφ(v) = φ fǫ s, yǫ (s) φ f s, x(s) ,

where the last inequality follows from the one above. On the other hand, by (QM) we have φ f s, yǫ (s) φ f s, x(s) .

This contradiction proves that x(t) ≪ yǫ (t) for t0 t t1 and all small ǫ > 0. Since yǫ (t) = x(t, t0 , xǫ , ǫ) → x(t, t0 , x1 ) as ǫ → 0, by taking the limit we conclude that x(t, t0 , x0 ) x(t, t0 , x1 ) for t0 t t1 . Fix t0 and t ∈ J (t0 , x0 ). As the map h : x0 → x(t, t0 , x0 ) is injective, from x0 < x1 we infer x(t, t0 , x0 ) < x(t, t0 , x1 ). Note that h(D ∩ [x0 , x1 ]) ⊂ [x(t, t0 , x0 ), x(t, t0 , x1 )]. Therefore the relation x0 ≪ x1 implies Int D ∩ [x0 , x1 ] = ∅. Injectivity of h and invariance of domain implies Int[x(t, t0 , x0 ), x(t, t0 , x1 )] = ∅, which holds if and only if x(t, t0 , x0 ) ≪ x(t, t0 , x1 ). Conversely, suppose that (3.1) is monotone, t0 ∈ J , x0 , x1 ∈ D with x0 x1 and φ(x0 ) = φ(x1 ) for some φ ∈ K ∗ . Since x(t, t0 , x0 ) x(t, t0 , x1 ) for t t0 we conclude that dtd φ[x(t, t0 , x1 ) − x(t, t0 , x0 )]|t=t0 0, or φ(f (t0 , x1 )) φ(f (t0 , x0 )). Thus (QM) holds. Theorem 3.2 has been stated so as to minimize technical details concerning the domain J × D by assuming that J and D are open. In many applications, D is a closed set, for example, D = K or D = [a, b] where a ≪ b. The proof can be modified to handle these (and other) cases. If D = K and K is positively invariant for (3.1), the proof is unchanged because whenever x ∈ D then x + ǫv ∈ D for small positive ǫ, and because K is also positively invariant for the modified equation. If D = [a, b], then the result follows by applying Theorem 3.2 to f |J × [[a, b]] and using continuity. A set S is called positively invariant under (3.1) if S ⊂ D and solutions starting in S stay in S, or more precisely: (t0 , x0 ) ∈ J × S

and t ∈ J (t0 , x0 ), t t0

)⇒ x(t, t0 , x0 ) ∈ S.

284


It will be useful to have the following necessary and sufficient condition for invariance of K: P ROPOSITION 3.3. The cone K is positively invariant under (3.1) if and only if K ⊂ D and for each t ∈ J (P) λ ∈ K ∗ , x ∈ ∂K, λ(x) = 0 )⇒ λ(f (t, x)) 0. P ROOF. The proof that (P) implies positive invariance of K is similar to that of Theorem 3.2. Given x1 ∈ K, we pass immediately to xǫ ≫ x1 and the solution yǫ (t) of the perturbed equation defined in the proof of Theorem 3.2 and show that yǫ (t) ≫ 0 for t0 t t1 by an argument similar to the one used in the aforementioned proof. The result x(t, t0 , x1 ) 0 for t t0 is obtained by passage to the limit as ǫ → 0. The converse is also an easy modification of the converse argument given in the proof of Theorem 3.2. Since we will have occasion to apply (P) to systems other than (3.1), it will be convenient to refer to (P) by saying that (P) holds for f : J × D → Rn where K ⊂ D. Hypothesis (P) says that the time-dependent vector field f (t, x) points into K at points x ∈ ∂K. Let A(t) be a continuous n × n matrix-valued function defined on the interval J containing t0 and consider the linear initial value problem for the matrix solution X: X ′ = A(t)X,

X(t0 ) = I.

(3.2)

Observe that (P) and (QM) are equivalent for linear systems; therefore we have: C OROLLARY 3.4. The matrix solution X(t) satisfies X(t)K ⊂ K for t t0 if and only if for all t ∈ J , (P) holds for the function x → A(t)x. In fact, (P) implies that X(t) maps K \ {0} and Int K into themselves for all t > t0 . A matrix A is K-positive if A(K) ⊂ K. Corollary 3.4 implies that X(t) is K-positive for t t0 if (P) holds. If for every t ∈ J , there exists α ∈ R such that A + αI is K-positive, then (P) holds for A. Indeed, if λ ∈ K ∗ satisfies λ(x) = 0 then application of λ to (A + αI )x 0 yields that λ(A(t)x) 0. The converse is false for general cones but true for polyhedral cones by Theorem 8 of Schneider and Vidyasagar [177]. See also Theorem 4.3.40 of Berman and Neumann [18]. Lemmert and Volkmann [118] give the following example of a matrix 4

0 A= 0 1

0 0 0

1 0 0

5

which satisfies (P) for the ice-cream cone above but A + αI is not K-positive for any α. Recall that the domain D is p-convex if for every x, y ∈ D satisfying x y the line segment joining them also belongs to D. Let ∂f ∂x (t, x) be continuous on J × D. We say


285

that f (or system (3.1)) is K-cooperative if for all t ∈ J , y ∈ D, (P) holds for the function x → ∂f ∂x (t, y)x. By Corollary 3.4 applied to the variational equation X ′ (t) =

∂f t, x(t, t0 , x0 ) X, ∂x

X(t0 ) = I

we conclude that if f is K-cooperative then X(t) =

∂x ∂x0 (t, t0 , x0 )

is K-positive.

T HEOREM 3.5. Let ∂f ∂x (t, x) be continuous on J × D. Then (QM) implies that f is K-cooperative. Conversely, if D is p-convex and f is K-cooperative, then (QM) holds. P ROOF. Suppose that (QM) holds, x ∈ D, h ∈ ∂K, and φ ∈ K ∗ satisfies φ(h) = 0. Since x x + ǫh and φ(x) = φ(x + ǫh) for small ǫ > 0, (QM) implies that φ(f (t, x)) φ(f (t, x + ǫh)). Hence,

f (t, x + ǫh) − f (t, x) 0φ ǫ

and the desired result holds on taking the limit ǫ → 0. Conversely, suppose that f is K-cooperative and D is p-convex. If x, y ∈ D satisfy x y and φ(x) = φ(y) for some φ ∈ K ∗ , then either φ = 0 or y − x ∈ ∂K. Consequently φ f (t, y) − f (t, x) =

1

0

because the integrand is nonnegative.

∂f φ t, sy + (1 − s)x (y − x) ds 0 ∂x

If for each (t, x) ∈ J × D there exists α such that ( ∂f ∂x (t, x) + αI ) is K-positive, then f is K-cooperative. This is implied by the remark following Corollary 3.4. In the special case that K = Rn+ , the cone of nonnegative vectors, it is easy to see by using the standard inner product that we may identify K ∗ with K. The quasimonotone hypothesis reduces to the Kamke–Müller condition [91,148]: x y and xi = yi for some i implies fi (t, x) fi (t, y). This holds by taking φ(x) = ei , x (ei is the unit vector in the xi -direction) and noting that every φ ∈ K ∗ can be represented as a positive linear combination of these functionals. If f is differentiable, the Kamke–Müller condition implies ∂fi (t, x) 0, ∂xj

i = j.

(3.3)

Conversely, if ∂f ∂x (t, x) is continuous on J × D, (3.3) holds and D is p-convex, then the Kamke–Müller condition holds by an argument similar to the one used in the proof of the converse in Theorem 3.5. Stern and Wolkowicz [206] give necessary and sufficient conditions for (P) to hold for 2 xn2 , xn 0}. matrix A relative to the ice-cream cone K = {x ∈ Rn : x12 + x22 + · · · + xn−1 Let Q denote the n × n diagonal matrix with first n − 1 entries 1 and last entry −1. Then

286


(QM) holds for A if and only if QA + AT Q + αQ is negative semidefinite for some α ∈ R. Their characterization extends to other ellipsoidal cones.

3.2. Strong monotonicity with linear systems In this section, all matrices are assumed to be square. Recall that the matrix A is strongly positive if A(K \ {0}) ⊂ Int K. We introduce the following milder hypothesis on the matrix A, following Schneider and Vidyasagar [177]: (ST) For all x ∈ ∂K \ {0} there exists ν ∈ K ∗ such that ν(x) = 0 and ν(Ax) > 0. The following result for the case of constant matrices was proved by Elsner [44], answering a question in [177]. Our proof follows that of Theorem 4.3.26 of Berman et al. [18]. T HEOREM 3.6. Let the linear system (3.2) satisfy (P). Then the fundamental matrix X(t1 ) is strongly positive for t1 > t0 if there exists s satisfying t0 s t1 such that (ST) holds for A(s). P ROOF. Observe that the set of all s such that (ST) holds for A(s) is open. If the result is false, there exists x > 0 such that the solution of (3.2) given by y(t) = X(t)x satisfies y(t1 ) ∈ ∂K \ {0}. By Corollary 3.4, y(t) > 0 for t t0 and y(t) ∈ ∂K for t0 t t1 . Let s ∈ (t0 , t1 ] be such that (ST) holds for A(s). Then there exists ν ∈ K ∗ such that ν(y(s)) = 0 and ν(A(s)y(s)) > 0. As ν ∈ K ∗ and y(t) ∈ K, h(t) := ν(y(t)) 0 for t0 t t1 . But h(s) = 0 and dtd |t=s h(t) = ν(A(s)y(s)) > 0 which, taken together, imply that h(s − δ) < 0 for small positive δ, giving the desired contradiction. If (3.2) satisfies (P) and if x ∈ ∂K then for all φ ∈ K ∗ such that φ(x) = 0 we have φ(A(t)x) 0. Hypothesis (ST) asserts that if x = 0 then φ(A(t)x) > 0 for at least one such φ. Berman et al. [18] refer to (ST) (they include (P) in their definition) by saying that A is strongly K-subtangential; while we do not use this terminology, our notation is motivated by it. An example in [18] shows that (P) and (ST) are not necessary for strong positivity. Let K be the ice-cream cone K = {x ∈ R3 : x12 + x22 x32 , x3 0} and consider the constant coefficient system (3.2) with matrix A given by 4

5 0 1 0 A = −1 −1 0 . 0 0 0 An easy calculation shows that (x12 + x22 )′ = −2x22 so it follows easily that K is positively invariant, hence (P) holds by Corollary 3.4. The solution satisfying x(0) = (cos(θ ), sin(θ ), 1)T ∈ ∂K satisfies x(t) ∈ Int K for t > 0 since the calculation above and the fact that x2 (t) can have only simple zeros implies that x12 + x22 is strictly decreasing while x3 remains unchanged. The linear functional ν, defined ν(x) :=


287

(− cos(θ ), − sin(θ ), 1)x belongs to K ∗ by an easy calculation and satisfies ν(x(0)) = 0. It is unique, up to positive scalar multiple, with these properties because K is smooth so its positive normal at a point is essentially unique. But ν(Ax(0)) = sin2 (θ ) vanishes if θ = 0, π . Therefore (ST) fails although X(t) is strongly positive for t > 0. Theorem 3.6 leads to the following result on strong monotonicity for the nonlinear system (3.1). L EMMA 3.7. Assume D is p-convex, ∂f ∂x (t, x) is continuous on J × D and f is K-cooperative. Let x0 , x1 ∈ D satisfy x0 < x1 and t > t0 with t ∈ J (t0 , x0 ) ∩ J (t0 , x1 ). If there exists y0 on the line segment joining x0 to x1 and r ∈ [t0 , t] such that (ST) holds for ∂f ∂x (r, x(r, t0 , y0 )) then x(t, t0 , x0 ) ≪ x(t, t0 , x1 ). P ROOF. First, observe that for y0 on the segment it follows that t ∈ J (t0 , y0 ). We apply the formula x(t, t0 , x1 ) − x(t, t0 , x0 ) =

1 0

∂x t, t0 , sx1 + (1 − s)x0 (x1 − x0 ) ds, ∂x0

∂x ∂x0 (t, t0 , y0 ) is the fundamental matrix for (3.2) corresponding to the matrix ∂f ∂x (t, x(t, t0 , y0 )). The left-hand side belongs to K \ {0} if x0 < x1 by Theorems 3.5

where X(t) =

A(t) = and 3.2 but we must show it belongs to Int K. For this to be true, it suffices that for each t > t0 there exists s ∈ [0, 1] such that the matrix derivative in the integrand is strongly positive. In fact, this derivative is K-positive by Corollary 3.4 for all values of the arguments with t t0 , so application of any nontrivial φ ∈ K ∗ to the integral gives a nonnegative numerical result. If there exists s as above, then the application of φ to the integrand gives a positive numerical result for all s ′ near s by continuity and Proposition 3.1 and hence ∂x (t, t0 , y0 ) is strongly the integral belongs to Int K by Proposition 3.1. By Theorem 3.6, ∂x 0 positive for t > t0 if (ST) holds for A(r) = is guaranteed by our hypothesis.

∂f ∂x (r, x(r, t0 , y0 ))

for some r ∈ [t0 , t]. But this

T HEOREM 3.8. D is p-convex, ∂f ∂x (t, x) is continuous on J × D, and f is K-cooperative. Suppose for every x0 , x1 ∈ D with x0 < x1 and t0 ∈ J , there exists y0 on the line segment joining the xi such that (ST) holds for ∂f ∂x (t0 , y0 ). If x0 , x1 ∈ D, x0 < x1 , and t > t0 then t ∈ J (t0 , x0 ) ∩ J (t0 , x1 )

)⇒ x(t, t0 , x0 ) ≪ x(t, t0 , x1 ).

P ROOF. This is an immediate corollary of Lemma 3.7.

As the main hypothesis of Theorem 3.8 will be difficult to verify in applications, the somewhat stronger condition of irreducibility may be more useful because there is a large body of theory related to it [18,19]. We now introduce the necessary background. A closed subset F of K that is itself a cone is called a face of K if x ∈ F and 0 y x (inequalities

288


induced by K) implies that y ∈ F . For example, the faces of K = Rn+ are of the form {x ∈ Rn+ : xi = 0, i ∈ I } where I ⊂ {1, 2, . . . , n}. For the ice-cream cone K = {x ∈ Rn : x12 + 2 x22 + · · · + xn−1 xn2 , xn 0}, the faces are the rays issuing from the origin and passing through its boundary vectors. A K-positive matrix A is K-irreducible if the only faces F of K for which A(F ) ⊂ F are {0} and K. The following is a special case of Theorem 2.3.9 in Berman and Neumann [18]; see Berman and Plemmons [19] for proofs. These references contain additional related results. T HEOREM 3.9. Let A be an n × n K-positive matrix. Then the following are equivalent: (i) A is K-irreducible; (ii) No eigenvector of A belongs to ∂K; (iii) A has exactly one unit eigenvector in K and it belongs to Int K; (iv) (I + A)n−1 (K \ {0}) ⊂ Int K. The famous Perron–Frobenius Theory is developed for K-positive and K-irreducible matrices in the references above. In particular, the spectral radius of A is a simple eigenvalue of A with corresponding eigenvector described in (iii) above. Below we require the simple observation that if A is K-positive, then the adjoint A∗ is K ∗ -positive. Indeed, if ν ∈ K ∗ then (A∗ ν)(x) = ν(Ax) 0 for all x ∈ K so A∗ ν ∈ K ∗ . The next result is adapted from Theorem 4.3.17 of Berman et al. [18]. P ROPOSITION 3.10. Let A be an n × n matrix and suppose that there exists α ∈ R such that B := A + αI is K-positive. Then B is K-irreducible if and only if (ST) holds for A. P ROOF. Suppose that B = A + αI is K-positive and (ST) holds. If Ax = λx for some λ ∈ R and nonzero vector x ∈ ∂K then there exists ν ∈ K ∗ such that ν(x) = 0 and ν(Ax) > 0. But ν(Ax) = λν(x) = 0. Consequently, no eigenvector of B belongs to ∂K so by Theorem 3.9, B is K-irreducible. Conversely, suppose that B is K-positive and K-irreducible. Let x ∈ ∂K, x = 0 and let ν ∈ K ∗ satisfy ν = 0 and ν(x) = 0. By Theorem 3.9, C := B + I has the property that C n−1 is strongly positive so ν(C n−1 x) > 0. As C is K-positive, ν(C r x) 0 for r = 1, 2, . . . , n − 1. Because ν(x) = 0, we may choose p ∈ {1, 2, . . . , n − 1} such that ν(C p x) > 0 but ν(C p−1 x) = 0. Let ν˜ = (C ∗ )p−1 ν. Then ν˜ ∈ K ∗ , ν˜ (x) = 0 and ν˜ (Cx) > 0. But then A satisfies (ST) because ν˜ (Ax) = ν˜ (Cx) > 0. Motivated by Proposition 3.10, we introduce the following hypothesis for matrix A. (CI) There exists α ∈ R such that A + αI is K-positive and K-irreducible. In the special case that K = Rn+ , n 2, matrix A satisfies (CI) if and only if aij 0 for i = j and there is no permutation matrix P such that

B P AP = C T

0 , D


289

where B and D are square. This is equivalent to the assertion that the incidence graph of A is strongly connected. See Berman and Plemmons [19]. The following is an immediate consequence of Theorem 3.8. C OROLLARY 3.11. D is p-convex, ∂f ∂x (t, x) is continuous on J × D and f is Kcooperative. Suppose that for every x0 , x1 ∈ D with x0 < x1 and t0 ∈ J , there exists y0 on the line segment joining the xi such that (CI) holds for ∂f ∂x (t0 , y0 ). If x0 , x1 ∈ D, x0 < x1 , and t > t0 then t ∈ J (t0 , x0 ) ∩ J (t0 , x1 )

)⇒ x(t, t0 , x0 ) ≪ x(t, t0 , x1 ).

P ROOF. If (CI) holds then, by Proposition 3.10, (ST) holds for follows from Theorem 3.8.

∂f ∂x (t, x),

so the conclusion

Corollary 3.11 is an improvement of the restriction of Theorem 10 of Kunze and Siegel [111] to the case that K has nonempty interior; their results also treat the case that K has empty interior in Rn but nonempty interior in some subspace of Rn . Walter [228] gives a sufficient condition for strong monotonicity relative to K = Rn+ which does not require f to be differentiable. For polyhedral cones it can be shown that matrix A satisfies (P) and (ST) if and only if there exists α ∈ R such that A + αI is K-positive and K-irreducible. See Theorem 4.3.40 of Berman et al. [18]. For the case of polyhedral cones, therefore, Corollary 3.11 and Theorem 3.8 are equivalent.

3.3. Autonomous K-competitive and K-cooperative systems Our focus now is on the autonomous system of ordinary differential equations x ′ = f (x),

(3.4)

where f is a vector field on an open subset D ⊂ Rn ; all vector fields are assumed to be continuously differentiable. We change our notation slightly to conform to more dynamical notation, denoting x(t, 0, x0 ) by Φt (x), where Φ denotes the dynamical system (= local flow) in D generated by f discussed in Section 1. The notation Φt (x) carries the tacit assumption that t ∈ Ix , the open interval in R containing the origin on which the trajectory of x under Φ is defined. The positive semiorbit (respectively, (negative semiorbit) of x is γ + (x) := {Φt (x): t ∈ t 0} (respectively, γ − (x) := {Φt (x): t 0}). The limit sets of x can be defined as ω(x) =

1!

t0 τ t

Φτ (x),

α(x) =

1!

Φτ (x).

t0 τ t

We call f and Eq. (3.4) K-competitive in D if the time-reversed system x ′ = −f (x)

290


is K-cooperative. When K is the standard cone Rn+ , f is competitive if and only if ∂fi /∂xj 0 for i = j . Therefore if f is K-competitive with local flow Φ, then −f is

where Φ

t (x) = Φ−t (x); and conversely. Thus timeK-cooperative with local flow Φ, reversal changes K-competitive systems into K-cooperative ones, and vice-versa. This fact will be exploited repeatedly below. In the remainder of Section 3 we assume Rn is ordered by a cone K ⊂ Rn with nonempty interior. A map is locally monotone if every point in its domain has a neighborhood on which the map is monotone. A local flow or local semiflow Φ is locally monotone if Φt is a locally monotone map for all t > 0. Locally strongly monotone is defined similarly. T HEOREM 3.12. Let f be a K-cooperative vector field in an open set D ⊂ Rn , generating the local flow Φ. Then Φ is locally monotone, and monotone when D is p-convex. P ROOF. If D is p-convex, monotonicity follows from Theorem 3.2 (with f (t, x) := f (x)). Suppose D is not p-convex. Denote the domain of Φt by Dt . We first claim: For every p ∈ D there exists τ > 0 and a neighborhood N ⊂ Dτ such that Φt |N is monotone if t ∈ [0, τ ]. But this is obvious since by restricting f to a p-convex neighborhood of p, we can use Theorem 3.2. Now fix p ∈ D and let J (0, p) ∩ [0, ∞) = [0, r), 0 < r ∞. Let Ip be the set of all nonnegative s ∈ [0, r) such that there is a neighborhood Us of p, contained in Ds , such that Φt |Us is monotone for each t ∈ [0, s]. The previous claim implies that [0, τ ] ⊂ Ip and, by its definition, Ip is an interval. Furthermore, straightforward applications of the previous claim establish that Ip is both an open and a closed subset of [0, r). It follows that Ip = [0, r). The next theorem gives a sufficient condition for strong monotonicity. Define G(f ) to be the set of x ∈ D such that (ST) holds for A = f ′ (x). Note that x ∈ G(f ) provided (CI) holds for A = f ′ (x), by Proposition 3.10. If K = Rn+ , a sufficient condition for x ∈ G(f ) is that f ′ (x) is an irreducible matrix with nonnegative off-diagonal entries. T HEOREM 3.13. Let f be a K-cooperative vector field in an open set D ⊂ Rn , generating the local flow Φ. Assume D \ G(f ) does not contain any totally ordered line segment (which holds when D \ G(f ) is zero dimensional). Then Φ is locally strongly monotone, and strongly monotone when D is p-convex. P ROOF. Suppose D is p-convex, in which case Φ is monotone by from Theorem 3.2. By Theorem 3.8, Φ is strongly monotone. When D is not p-convex, Φ is locally monotone by Theorem 3.12, and the previous paragraph implies Φ is locally strongly monotone. The proof of Theorem 3.13 can be adapted to cover certain nonopen domains D, such as an order interval, a closed halfspace, and the cone K; see the discussion following the proof of Theorem 3.2.


291

Theorem 3.8 implies that Φ is strongly monotone provided D is p-convex and f satisfies the autonomous version of condition (ST) of Section 3.2, namely: (ST*) For all u ∈ D, x ∈ ∂K \ {0} there exists ν ∈ K ∗ such that ν(x) = 0 and ν(f ′ (u)x) > 0. Without p-convexity of D, condition (ST*) yields local strong monotonicity.

3.4. Dynamics of cooperative and competitive systems We continue to assume Rn is ordered by a cone K having nonempty interior; all notions involving order refer to that defined by K. For this section, the terms “competitive” and “cooperative” are tacitly understood to mean “K-competitive” and “K-cooperative,” and monotonicity refers to the ordering defined by K. We first apply results from Section 2 to obtain a generic stable convergence theorem for cooperative vector fields. Let Φ denote the local flow generated by a vector field f on D ⊂ Rn . We assume D is p-convex throughout this section without further mention. When Φt (x) is defined for all (t, x) ∈ [0, ∞) × D, as when all positive semiorbits have compact closure in D, the corresponding positive local semiflow Φ + is a semiflow. To Φ we associate C, S and E, denoting respectively the sets of convergent, stable and equilibrium points for Φ + . T HEOREM 3.14. Let f be a cooperative vector field on an open set D ⊂ Rn , generating a local flow Φ such that: (a) Every positive semiorbit of Φ has compact closure in D; (b) Condition (ST*) above is satisfied, and D = AC ∪ BC. Then Φ has the following properties: (i) C ∩ S contains a dense open subset of D, consisting of points whose trajectories converge to equilibria; (ii) If E is compact there is a stable equilibrium, and an asymptotically stable equilibrium when E is finite. P ROOF. Assumption (ST*) makes Φ strongly monotone. The hypothesis of Theorem 2.26, with X = D, is fulfilled: D is normally ordered and D = BC ∪ AC. Therefore Theorem 2.26 implies the conclusion. Theorem 3.14, like Theorem 3.13, holds for some more general domains D, including relatively open subsets of V where V denotes a closed halfspace, a closed order interval, or the cone K. One of the main results of this subsection is that n-dimensional competitive and cooperative systems behave like general systems of one less dimension. Theorems 3.21 and 3.22 illustrate this principle for n = 2 in a very strong form. In higher dimensions the principle holds for compact limit sets. The key tool in proving this is the following result due to Hirsch [67]:

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T HEOREM 3.15. A limit set of a competitive or cooperative system cannot contain two points related by ≪. P ROOF. By time reversal, if necessary, we assume the system is cooperative, hence the local flow is monotone. Now apply Proposition 1.10. A periodic orbit of a competitive or cooperative system is a limit set and consequently it cannot contain two points related by ≪. The following sharper result will be useful later: P ROPOSITION 3.16. Nontrivial periodic orbit of a competitive or cooperative system cannot contain two points related by 0 such that |F (y1 ) − F (y2 )| K|y1 − y2 | for all y1 , y2 ∈ Rk . With these definitions, we can state a result of Hirsch [67] that follows directly from Theorem 3.15. T HEOREM 3.17. The flow on a compact limit set of a competitive or cooperative system in Rn is topologically equivalent to a flow on a compact invariant set of a Lipschitz system of differential equations in Rn−1 . P ROOF. Let L be the limit set, v ≫ 0 be a unit vector and let Hv be the hyperplane orthogonal to v, i.e, Hv := {x: x, v = 0}. The orthogonal projection Q onto Hv is given by Qx = x − x, vv. By Theorem 3.15, Q is one-to-one on L (this could fail only if L contains two points that are related by ≪). Therefore, QL , the restriction of Q to L, is a Lipschitz homeomorphism of L onto a compact subset of Hv . We argue by contradiction to establish the existence of m > 0 such that |QL x1 − QL x2 | m|x1 − x2 | whenever x1 = x2 are points of L. If this were false, then there exists sequences xn , yn ∈ L, xn = yn such that |Q(xn ) − Q(yn )| |(xn − yn ) − vv, xn − yn | = →0 |xn − yn | |xn − yn | as n → ∞. Equivalently, |wn − vv, wn | → 0 as n → ∞ where wn = xn − yn /|xn − yn |. We can assume that wn → w as n → ∞ where |w| = 1. Then, w = vv, w and therefore, v, w2 = 1 so w = ±v. But then xn − yn /|xn − yn | → ±v as n → ∞ and this implies −1 that xn ≪ yn or yn ≪ xn for all large n, contradicting Theorem 3.15. Therefore, QL is Lipschitz on Q(L). Since L is a limit set, it is an invariant set for (3.4). It follows that the


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dynamical system restricted to L can be modeled on a dynamical system in Hv . In fact, if y ∈ Q(L) then y = QL (x) for a unique x ∈ L and Ψt (y) ≡ QL (Φt (x)) is a dynamical system on Q(L) generated by the vector field F (y) = QL f Q−1 L (y)

on Q(L). According to McShane [137], a Lipschitz vector field on an arbitrary subset of Hv can be extended to a Lipschitz vector field on all of Hv , preserving the Lipschitz constant. It follows that F can be extended to all of Hv as a Lipschitz vector field. It is easy to see that Q(L) is an invariant set for the latter vector field. We have established the topological equivalence of the flow Φ on L with the flow Ψ on Q(L). Q(L) is a compact invariant set for the (n − 1)-dimensional dynamical system on Hv generated by the extended vector field. A consequence of Theorem 3.17 is that the flow on a compact limit set, L, of a competitive or cooperative system shares common dynamical properties with the flow of a system of differential equations in one less dimension, restricted to the compact, connected invariant set Q(L). Notice, however, that L may be the limit set of a trajectory not in L, and therefore Q(L) need not be a limit set. On the other hand, the flow Ψ in a compact limit sets enjoys the topological property of chain recurrence, due to Conley [31,30], which will be important in the next subsection. The definition is as follows. Let A be a compact invariant set for the flow Φ. Given two points z and y in A and positive numbers ǫ and t, an (ǫ, t)-chain from z to y in A is an ordered set {z = x1 , x2 , . . . , xm+1 = y; t1 , t2 , . . . , tm } of points xi ∈ A and times ti t such that Φt (xi ) − xi+1 < ǫ, i

i = 1, 2, . . . , m.

(3.5)

A is chain recurrent for Φ if for every z ∈ A and for every ǫ > 0 and t > 0, there is an (ǫ, t)-chain from z to z in A. Conley proved that when A is compact and connected, a flow Φ in A is chain recurrent if and only if there are no attractors. This useful condition can be stated as follows: For every proper nonempty compact set S ⊂ A and all t > 0, there exists s > t such that Φs (S) ⊂ Int S. Compactness of A implies that chain recurrence of the flow in A is independent of the metric, and thus holds for any topologically equivalent flow. It is intuitively clear that, as Conley proved, flows in compact alpha and omega limit sets are chain recurrent. Indeed, orbit segments of arbitrarily long lengths through point x repeatedly pass near any point of ω(x) ∪ α(x). Of course these segments do not necessarily belong to ω(x); but by taking suitable limits of points in these segments, one can find enough (ǫ, t)-chains in ω(x) and α(x) to prove the flows in these sets chain recurrent. For a rigorous proof, see Smith [194].

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3.5. Smale’s construction Smale [182] showed that it is possible to embed essentially arbitrary dynamics in a competitive or cooperative irreducible system. His aim was to warn population modelers that systems designed to model competition could have complicated dynamics. His result is also very useful for providing counterexamples to conjectures in the theory of monotone dynamics, since by time reversal his systems are cooperative. In this section, competitive and cooperative are with respect to the usual cone. Smale constructed special systems of Kolmogorov type xi′ = xi Mi (x),

1 i n,

(3.6)

in Rn+ where the Mi are smooth functions satisfying ∂Mi 0, define Mi (x) = 1 − S(x) + ηp

"

# xj gi (x),

1 i n.


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Then (3.7) holds for sufficiently small η since p( xj ) vanishes identically outside a comn pact subset of Rn+ . Consider the system (3.6) with M as above. R+ is positively invariant; and the function S(x) = i xi , evaluated along a solution x(t) of (3.6), satisfies

d S x(t) = S x(t) 1 − S x(t) dt since xi gi (x) = hi (x) = 0. Consequently Σn , which is S −1 (1) ∩ Rn+ , is positively invariant. Moreover if x(0) ∈ Rn+ then S(x(0)) 0. This implies S(x(t)) → 1 as t → ∞, unless x(t) ≡ 0, and Σn attracts all nontrivial solutions of (3.6) in Rn+ . Restricted to Σn , (3.6) becomes xi′ = ηhi (x),

1 i n.

Therefore the dynamics of (3.6) restricted to Σn is equivalent, up to a change in time scale, to the dynamics generated by (3.8). As noted above, Smale’s construction has implications for cooperative and irreducible systems since the time-reversed system corresponding to (3.6) is cooperative and irreducible in Int Rn+ . Time-reversal makes the simplex a repellor for a cooperative system Φ in Rn+ . Therefore every invariant set in the simplex is unstable for Φ. Each trajectory of Φ that is not in the simplex is attracted to the equilibrium at the origin or to the virtual equilibrium at ∞. The simplex is the common boundary between the basins of attraction of these two equilibria.

3.6. Invariant surfaces and the carrying simplex It turns out that the essential features of Smale’s seemingly very special construction are found in a large class of totally competitive Kolmogorov systems xi′ = xi Mi (x),

x ∈ Rn+ .

(3.9)

Here and below i and j run from 1 to n. Let Φ denote the corresponding local flow. The unit (n − 1) simplex is ∆n−1 := {x ∈ Rn+ : xi = 1}.

T HEOREM 3.18. Assume (3.9) satisfies the following conditions: i (a) ∂M ∂xj < 0; (b) Mi (0) > 0; (c) Mi (x) < 0 for |x| sufficiently large. Then there exists an invariant compact hypersurface Σ ⊂ Rn+ such that (i) Σ attracts every point in Rn+ \ {0}; (ii) Σ ∩ Int Rn+ is a locally Lipschitz submanifold; (iii) Σ ∩ Int Rn+ is transverse to every line that is parallel to a nonnegative vector and meets Σ ∩ Int Rn+ ; (iv) Σ is unordered;

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(v) Radial projection defines a homeomorphism h : Σ → ∆n−1 whose inverse is locally Lipschitz on the open (n − 1)-cell ∆n−1 ∩ Int Rn+ . There is a flow Ψ on ∆n−1 such that Φt |Σ = h ◦ Φt ◦ h−1 . C OROLLARY 3.19. If n = 3, every periodic orbit in R3+ bounds an unordered invariant disk. Assumption (a) is the condition of total competition; (b) and (c) have plausible biological interpretations. The attracting hypersurface Σ , named the carrying simplex by M. Zeeman, is analogous to the carrying capacity K in the one-dimensional logistic equation dx/dt = rx(K − x). One can define Σ either as the boundary of the set of points whose alpha limit set is the origin, or as the boundary of the compact global attractor. These sets coincide if and only if Σ is unique, in which case it uniformly attracts every compact set in Rn+ \ {0}. Uniqueness holds under mild additional assumptions on the maps Mi (Wang and Jiang [230]). The geometry, smoothness and dynamics of carrying simplices have been investigated by Benaïm [14], Brunovsky [21], Miercyński [140,143,141], Tineo [220], van den Driessche and M. Zeeman [223], Wang and Jiang [230], E. Zeeman [239], E. Zeeman and M. Zeeman [240–242], M. Zeeman [243]. Theorem 3.18 is proved in Hirsch [72] using a general existence theorem for invariant hypersurfaces, of which the following is a generalization: T HEOREM 3.20. Let Φ be a strongly monotone local flow in a p-convex open set D ⊂ Rn . If L ⊂ D is a nonempty compact unordered invariant set, L lies in an unordered invariant hypersurface M that is a locally Lipschitz submanifold. I DEA OF P ROOF. Define U to be the set of x ∈ D such that Φt (x) ≫ y for some t > 0, and some y ∈ L. Continuity implies U is open, and it is nonempty since it contains z ∈ D where z > y ∈ L. It can be shown that the lower boundary of U in D (Section 1.1) is a hypersurface with the required properties, by arguments analogous to the proof of Theorem 3.17.

3.7. Systems in R2 Cooperative and competitive systems in R2 have particularly simple dynamics. Versions of the following result were proved in Hirsch [67], Theorem 2.7 and Smith [194], Theorem 3.2.2. It is noteworthy that in the next two theorems Φ does not need to be monotone, only locally monotone; hence p-convexity of D is not needed. T HEOREM 3.21. Let D ⊂ R2 be an open set and g : D → R2 a vector field that is cooperative or competitive for the standard cone. Let y(t) a nonconstant trajectory defined on an open interval I ⊂ R containing 0. Then there exists t∗ ∈ I such that each coordinate yi (t) is nonincreasing or nondecreasing on each connected component of I \ {t∗ }.


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P ROOF. It suffices to prove that yi′ (t) can change sign at most once. We assume g is cooperative, otherwise reversing time. Let Φ be local flow of g and set X(t, x) = ∂Φ ∂x (t, x). The matrix-valued function X(t, x) satisfies the variational equation ∂g ∂ Φ(t, x) · X(t, x), X(t, x) = ∂t ∂x

X(0, x) = I.

Cooperativity and Corollary 3.4 show that X(t, x) has nonnegative entries for t 0, i.e., matrix multiplication by X(t, x) preserves the standard cone. The tangent vector y ′ (t) to the curve y(t), being a solution of the variational equation, satisfies y ′ (t) = X(t, y(0))y ′ (0). Nonnegativity of X(t, x) implies that if y ′ (t0 ) lies in the first or third quadrants, then y ′ (t) stays in the same quadrant, and hence its coordinates have constant sign, for t > t0 . On the other hand if y ′ (t) for t t0 is never in the first or third quadrants, its coordinates again have constant sign. (Note that y ′ (t) cannot transit directly between quadrants 1 and 3, or 2 and 4, since it cannot pass through the origin.) We have shown that there is at most one t0 ∈ I at which y ′ (t) changes quadrants. If such a t0 exists, set t∗ = t0 ; otherwise let t∗ ∈ I be arbitrary. Variants of the next result have been proved many times for Kolmogorov type population models (Albrecht et al. [1], Grossberg [53], Hirsch and Smale [80], Kolmogorov [97], Rescigno and Richardson [168], Selgrade [178]). T HEOREM 3.22. Let g be a K-cooperative or K-competitive vector field in a domain D ⊂ R2 . If γ + (x) (respectively, γ − (x)) has compact closure in D, then ω(x) (respectively, α(x)) is a single equilibrium. P ROOF. For the standard cone, denoted here by P , this follows from Theorem 3.21. The general case follows by making a linear coordinate change y = T x mapping K onto the standard cone. Here T is any linear transformation that takes a basis for R2 contained in ∂P into the standard basis, which lies in ∂K. Then we have u K v if and only if T u P T v; in other words, T is an order isomorphism. It follows that the system x ′ = g(x) is K-cooperative (respectively, K-competitive) if and only if the system y ′ = h(y) := T g(T −1 y) is P -cooperative (respectively, P -competitive). Therefore T is a conjugacy between the local flows Φ, Ψ of the two dynamical systems, that is, T ◦ Φt = Ψt ◦ T . Consequently the conclusion for P , proved above, implies the conclusion for K.

3.8. Systems in R3 The following Poincaré–Bendixson theorem for three-dimensional cooperative and competitive systems is the most notable consequence of Theorem 3.17. It was proved by Hirsch [76] who improved earlier partial results [67,187]. The following result from Smith [194] holds for arbitrary cones K ⊂ R3 with nonempty interior:

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T HEOREM 3.23. Let g be a K-cooperative or K-competitive vector field in a p-convex domain D ⊂ R3 . Then a compact limit set of g that contains no equilibrium points is a periodic orbit. P ROOF. Let Φ denote the flow of the system, and L the limit set. By Theorem 3.17, the restriction of Φ to L is topologically equivalent to a flow Ψ , generated by a Lipschitz planar vector field, restricted to the compact, connected, chain recurrent invariant set Q(L). Since L contains no equilibria neither does Q(L). The Poincaré–Bendixson theorem implies that Q(L) consists of periodic orbits and, possibly, entire orbits whose omega and alpha limit sets are periodic orbits contained in Q(L). The chain recurrence of Ψ on Q(L) will be exploited to show that Q(L) consists entirely of periodic orbits. Let z ∈ Q(L) and suppose that z does not belong to a periodic orbit. Then ω(z) and α(z) are distinct periodic orbits in Q(L). Let ω(z) = γ and suppose for definiteness that z belongs to the interior component, V , of R2 \ γ so that Ψt (z) spirals toward γ in V . The other case is treated similarly. Then γ is asymptotically stable relative to V . Standard arguments using transversals imply the existence of compact, positively invariant neigh/ U1 and there exists t0 > 0 borhoods U1 and U2 of γ in V such that U2 ⊂ IntV U1 , z ∈ for which Ψt (U1 ) ⊂ U2 for t t0 . Let ǫ > 0 be such that the 2ǫ-neighborhood of U2 in D is contained in U1 . Choose t0 larger if necessary such that Ψt (z) ∈ U2 for t t0 . This can be done since ω(z) = γ . Then any (ǫ, t0 )-chain in Q(L) beginning at x1 = z satisfies Ψt1 (x1 ) ∈ U2 and, by (3.5) and the fact that the 2ǫ-neighborhood of U2 is contained in U1 , it follows that x2 ∈ U1 . As t2 > t0 , it then follows that Ψt2 (x2 ) ∈ U2 and (3.5) again implies that x3 ∈ U1 . Continuing this argument, it is evident that the (ǫ, t0 )-chain cannot return to z. There can be no (ǫ, t0 )-chain in Q(L) from z to z and therefore we have contradicted that Q(L) is chain recurrent. Consequently, every orbit of Q(L) is periodic. Since Q(L) is connected, it is either a single periodic orbit or an annulus consisting of periodic orbits. It follows that L is either a single periodic orbit or a cylinder of periodic orbits. To complete the proof we must rule out the possibility that Q(L) consists of an annulus of periodic orbits. We can assume that the system is cooperative. The argument will be separated into two cases: L = ω(x) or L = α(x). If L = ω(x) consists of more than one periodic orbit then Q(L) is an annulus of periodic orbits in the plane containing an open subset O. Then there exists t0 > 0 such that Q(Φt0 (x)) ∈ O. Let y be the unique point of L such that Q(y) = Q(Φt0 (x)). y = Φt0 (x) cannot hold since this would imply that L is a single periodic orbit so it follows that either y ≪ Φt0 (x) or Φt0 (x) ≪ y. Suppose that the latter holds, the argument is similar in the other case. Then there exists t1 > t0 such that Φt1 (x) is so near y that Φt0 (x) ≪ Φt1 (x). But then the Convergence Criterion from Chapter 1 implies that Φt (x) converges to equilibrium, a contradiction to our assumption that L contains no equilibria. This proves the theorem in this case. If L = α(x) and Q(L) consists of an annulus of periodic orbits, let C ⊂ L be a periodic orbit such that Q(L) contains C in its interior. Q(C) separates Q(L) into two components. Fix a and b in L \ C such that Q(a) and Q(b) belong to different components of Q(L) \ Q(C). Since Φt (x) repeatedly visits every neighborhood of a and b as t → −∞, Q(Φt (x)) must cross Q(C) at a sequence of times tk → −∞. Therefore, there exist zk ∈ C such that Q(zk ) = Q(Φtk (x)) and consequently, as in the previous case, either zk ≪ Φtk (x)


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or Φtk (x) ≪ zk holds for each k. Passing to a subsequence, we can assume that either zk ≪ Φtk (x) holds for all k or Φtk (x) ≪ zk holds for all k. Assume the latter, the argument is essentially the same in the other case. We claim that for every s < 0 there is a point w ∈ C such that Φs (x) > w. For if tk < s then Φs (x) = Φs−tk ◦ Φtk (x) < Φs−tk (zk ) ∈ C. If y ∈ L then Φsn (x) → y for some sequence sn → −∞. By the claim, there exists wn ∈ C such that Φsn (x) > wn . Passing to a subsequence if necessary, we can assume that wn → w ∈ C and y w. Therefore, every point of L is related by to some point of C. The same reasoning applies to every periodic orbit C ′ ⊂ L for which Q(C ′ ) belongs to the interior of Q(L): either every point of L is some point of C ′ or every point of L is some point of C ′ . Since there are three different periodic orbits in L whose projections are contained in the interior of Q(L), there will be two of them for which the same inequality holds between points of L and points of the orbit. Consider the case that there are two periodic orbits C1 and C2 such that every point of L is some point of C1 and some point of C2 . The case that the opposite relations hold is treated similarly. If u ∈ C1 then it belongs to L so we can find w ∈ C2 such that u < w (equality can’t hold since the points belong to different periodic orbits). But w ∈ L so we can find z ∈ C1 such that w < z. Consequently, u, z ∈ C1 satisfy u < z, a contradiction to Proposition 3.16. This completes the proof. A remarkable fact about three-dimensional competitive or cooperative systems on suitable domains is that the existence of a periodic orbit implies the existence of an equilibrium point inside a certain semi-invariant closed ball having the periodic orbit on its boundary. Its primary use is to locate equilibria, or conversely, to exclude periodic orbits. The construction below is adapted from Smith [187,194] where the case K = R3+ was treated; here we treat the general case that K has nonempty interior. The terms “competitive” and “cooperative” will be used to mean K-competitive and K-cooperative for brevity. A related result appears in Hirsch [75]. Throughout the remainder of this section, the system is assumed to be defined on a p-convex subset D of R3+ . We can assume the system is competitive. Let γ denote the periodic orbit and assume that there exist p, q with p ≪ q such that γ ⊂ [p, q] ⊂ D.

(3.10)

Define B = x ∈ R3 : x is not related to any point y ∈ γ = (γ + K)c ∩ (γ − K)c .

Here we use the notation Ac for the complement of the subset A in R3 . Observe that in defining B we ignored the domain D of (3.4), viewing γ as a subset of R3 . Another way to define B is to express its complement as B c = (γ + K) ∪ (γ − K). A 3-cell is a subset of R3 that is homeomorphic to the open unit ball.

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T HEOREM 3.24. Let γ be a nontrivial periodic orbit of a competitive system in D ⊂ R3 and suppose that (3.10) holds. Then B is an open subset of R3 consisting of two connected components, one bounded and one unbounded. The bounded component, B(γ ), is a 3-cell contained in [p, q]. Furthermore, B(γ ) is positively invariant and its closure contains an equilibrium. Combining this result with Theorem 3.23 leads to the following dichotomy from Hirsch [75]. C OROLLARY 3.25. Assume the domain D ⊂ R3 of a cooperative or competitive system contains [p, q] with p ≪ q. Then one of the following holds: (i) [p, q] contains an equilibrium; (ii) the forward and backward semi-orbits of every point of [p, q] meet D \ [p, q]. P ROOF. We take the system to be competitive, otherwise reversing time. Assume (ii) is false. Then [a, b] contains a compact limit set L. If L is not a cycle, it contains an equilibrium by Theorem 3.23. If L is a cycle, (i) follows from Theorem 3.24. P ROOF SKETCH OF T HEOREM 3.24. That B is open is a consequence of the fact that γ + K and γ − K are closed. We show that B ∩ D is positively invariant. If x ∈ B ∩ D, y ∈ γ and t > 0 then Φ−t (y) ∈ γ so x is not related to it. Since the forward flow of a competitive system preserves the property of being unrelated, Φt (x) is unrelated to y. Therefore, Φt (x) ∈ B ∩ D. As in the proof of Theorem 3.17, for v > 0, Hv denotes the hyperplane orthogonal to v and Q the orthogonal projection onto Hv along v. Q is one-to-one on γ so Q(γ ) is a Jordan curve in Hv . Let Hi and He denote the interior and exterior components of Hv \ Q(γ ). If x ∈ Q−1 (Q(γ )) then Q(x) = Q(y) for some y ∈ γ and therefore either x = y, x ≪ y or y ≪ x. In any case, x ∈ / B. Hence, B = B ∩ Q−1 (Hi ) ∪ B ∩ Q−1 (He ) .

Set B(γ ) = B ∩ Q−1 (Hi ). − Given z ∈ Hi , let A+ z := {s ∈ R: z + sv ∈ γ + K} and Az := {s ∈ R: z + sv ∈ γ − K}. + Az clearly contains all large s by compactness of γ and it is closed because γ + K is closed. If s ∈ A+ z , there exists y ∈ γ and k ∈ K such that z + sv = y + k so z + (s + r)v = + y + k + rv, implying that s + r ∈ A+ z for all r 0. It follows that Az = [s+ (z), ∞), and − + − similarly, Az = (−∞, s− (z)]. If s− (z) z+ (z) so Az ∩ Az is nonempty, then there exists s ∈ R, ki ∈ K, and yi ∈ γ such that z + sv = y1 + k1 = y2 − k2 . We must have k1 = k2 = 0 or else y2 > y1 , a contradiction to Proposition 3.16, but then z + sv = y1 so z = Qy1 contradicting that z ∈ Hi . We conclude that s− (z) < z+ (z) and that z + sv ∈ B(γ ) if and only if s− (z) < s < s+ (z). It follows that B(γ ) = z + sv: z ∈ Hi , s ∈ s− (z), s+ (z) .


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It is easy to show that the maps z → s± (z) are continuous and satisfy s+ (z) − s− (z) → 0 as z → y ∈ γ and this implies that B(γ ) is a 3-cell. See the argument given in Smith [187, 194]. To prove B(γ ) ⊂ [p, q], we identify K ∗ as the set of x such that x, k 0 for all k ∈ K (where x, k denotes inner product). Schneider and Vidyasagar [177] proved the elegant result that every vector x has a unique representation x = k − w,

k ∈ K, w ∈ K ∗ , w, k = 0.

Choose any z ∈ B ∩ (R3 \ [p, q]) and write z − p = k − w, q − z = k′ − w′ ,

k ∈ K, w ∈ K ∗ , w, k = 0, k ′ ∈ K, w ′ ∈ K ∗ , w ′ , k ′ = 0.

Observe that w > 0, w ′ > 0 because z ∈ B. Either k > 0 or k ′ > 0. For if k = k ′ = 0 then q − p = −(w + w ′ ), so 0 w + w ′ , q − p = − w + w ′ 2 0. This entails w + w ′ = 0 and thus p = q, a contradiction. We assume k > 0, as the case k ′ > 0 is similar, and even follows formally by replacing K with −K. Then w > 0. Consider the ray R = {z + tk: t 0}. If y ∈ γ , then w, z + tk − y = w, z − p + w, p − y w, z − p = − w 2 < 0. Because z and u are unrelated, there exists u ∈ K ∗ such that u, z − y > 0. So u, z + tk − y = u, z − y + t (z, k) u, z − y > 0. This shows that no point of R is related to any point of γ . Therefore R and hence z are in the unbounded component of B. As B(γ ) is a connected component of the positively invariant set B, it is positively invariant. Consequently its closure is a positively invariant set homeomorphic to the closed unit ball in R3 . It therefore contains an equilibrium by a standard argument using the Brouwer Fixed Point Theorem (see, e.g., Hale [57, Theorem I.8.2]). If B(γ ) contains only nondegenerate equilibria x1 , x2 , . . . , xm , then standard topological si degree arguments imply that m is odd and that 1 = m i=1 (−1) where si ∈ {0, 1, 2, 3} is the number of positive eigenvalues of Df (xi ). See Smith [187] for the proof and further information on equilibria in B(γ ). There are many papers devoted to competitive Lotka–Volterra systems in R3 , largely stimulated by the work of M. Zeeman. See for example [82,223,237,239,243,240,242] and references therein. The paper of Li and Muldowney [115] contains an especially nice

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application to epidemiology. Additional results for three-dimensional competitive and cooperative systems can be found in references [66,75–77,41,194,196,247,248]. The recent paper of Ortega and Sánchez [153] is noteworthy for employing a cone related to the ice-cream cone and observing that results for competitive systems are valid for general cones with nonempty interior. They show that if P is a symmetric matrix of dimension n having one positive eigenvalue λ+ with corresponding unit eigenvector e+ , and n − 1 negative eigenvalues, then (3.4) is monotone with respect to the order generated by the cone K := {x ∈ Rn : P x, x 0, x, e+ 0} if and only if there exists a function µ : Rn → R such that the matrix P · Dfx + (Dfx )T · P + µ(x)P is positive semidefinite for all x. They use this result to show that one of the results of R.A. Smith [204] on the existence of an orbitally stable periodic orbit, in the special case n = 3, follows from the results for competitive systems. It is not hard to see that if (3.4) satisfies the conditions above then after a change of variables in (3.4), the resulting system is monotone with respect to the standard ice-cream cone. For applications of competitive and cooperative systems, see for example Benaïm [15], Benaïm and Hirsch [16,17], Hirsch [69,74] Hofbauer and Sandholm [81], Hsu and Waltman [84], Smith [194,196], Smith and Waltman [202].

4. Delay differential equations 4.1. The semiflow The aim of the present section is to apply the theory developed in Sections 1 and 2 to differential equations containing delayed arguments. Such equations are often referred to as delay differential equations or functional differential equations. Since delay differential equations contain ordinary differential equations as a special case, when all delays are zero, the treatment is quite similar to the previous section. The main difference is that a delay differential equation generally can’t be solved backward in time and therefore there is not a well-developed theory of competitive systems with delays. Delay differential equations generate infinite-dimensional dynamical systems and there are several choices of state space. We restrict attention here to equations with bounded delays and follow the most well-developed theory (see Hale and Verduyn Lunel [61]). If r denotes the maximum delay appearing in the equation, then the space C := C([−r, 0], Rn ) is a natural choice of state space. Given a cone K in Rn , CK contains the cone of functions which map [−r, 0] into K. The section begins by identifying sufficient conditions on the right hand side of the delay differential equation for the semiflow to be monotone with respect to the ordering induced by this cone. This quasimonotone condition reduces to the quasimonotone condition for ordinary differential equations when no delays are present. Our main goal is to identify sufficient conditions for a delay differential equation to generate an eventually strongly monotone semiflow so that results from Sections 1 and 2 may be applied.


303

In order to motivate fundamental well-posedness issues for delay equations, it is useful to start with a consideration of a classical example that has motivated much research in the field (see, e.g., Krisztin et al. [105] and Hale and Verduyn Lunel [61]), namely the equation x ′ (t) = −x(t) + h x(t − r) ,

t 0,

(4.1)

where h is continuous and r > 0 is the delay. It is clear that x(t) must be prescribed on the interval [−r, 0] in order that it be determined for t 0. A natural space of initial conditions is the space of continuous functions on [−r, 0], which we denote by C, where n = 1 in this case. C is a Banach space with the usual uniform norm |φ| = sup{|φ(θ)|: −r θ 0}. If φ ∈ C is given, then it is easy to see that the equation has a unique solution x(t) for t 0 satisfying x(θ ) = φ(θ),

−r θ 0.

If the state space is C, then we need to construct from the solution x(t), an element of the space C to call the state of the system at time t. It should have the property that it uniquely determines x(s) for s t. The natural choice is xt ∈ C, defined by xt (θ ) = x(t + θ ),

−r θ 0.

Then, x0 = φ and xt (0) = x(t). The general autonomous functional differential equation is given by x ′ (t) = f (xt ),

(4.2)

where f : D → Rn , D is an open subset of C and f is continuous. In the example above, f is given by f (φ) = −φ(0) + h(φ(−r)) for φ ∈ C. Observe that (4.2) includes the system of ordinary differential equations x ′ = g(x), where g : Rn → Rn , as a special case. Simply let f (φ) = g(φ(0)) so that f (xt ) = g(xt (0)) = g(x(t)). It will always be assumed that (4.2), together with the initial condition x0 = φ ∈ D has a unique, maximally defined solution, denoted by x(t, φ), on an interval [0, σ ). The state of the system is denoted by xt (φ) to emphasize the dependence on the initial data. Uniqueness of solutions holds if, for example, f is Lipschitz on compact subsets of D (see Hale and Verduyn Lunel [61]). This holds, for example, if f ∈ C 1 (D) has locally bounded derivative. If uniqueness of solutions of initial value problems hold, then the map (t, φ) → xt (φ) is continuous. Therefore, a (local) semiflow on D can be defined by Φt (φ) = xt (φ).

(4.3)

In contrast to the case of ordinary differential equations, x(t, φ) cannot usually be defined for t 0 as a solution of (4.2) and consequently, Φt need not be one-to-one.

304


It will be convenient to have notation for the natural embedding of Rn into C. If x ∈ Rn , let xˆ ∈ C be the constant function equal to x for all values of its argument. The set of equilibria for (4.2) is given by ˆ =0 . E = xˆ ∈ D: x ∈ Rn and f (x) 4.2. The quasimonotone condition Given that C is a natural state space for (4.2), we now consider what sort of cones in C will yield useful order relations. The most natural such cones are those induced by cones in Rn . Let K be a cone in Rn with nonempty interior and K ∗ denote the dual cone. All inequalities hereafter are assumed to be those induced on Rn by K. The cone K induces a cone CK in the Banach space C defined by CK = φ ∈ C: φ(θ) 0, −r θ 0 .

It has nonempty interior in C given by Int CK = {φ ∈ CK : φ(θ) ≫ 0, θ ∈ [−r, 0]}. The usual notation , t0 , then x(t, t0 , ψǫ , gǫ ) is also defined on this same interval for all sufficiently small positive ǫ and x(t, t0 , ψǫ , gǫ ) → x(t, t0 , ψ, g),

ǫ → 0,

for t ∈ [t0 , t1 ] by Hale and Verduyn Lunel [61, Theorem 2.2.2]. We will show that x(t, t0 , φ, f ) ≪ x(t, t0 , ψǫ , gǫ ) on [t0 − r, t1 ] for small positive ǫ. The result will then follow by letting ǫ → 0. If the assertion above were false for some ǫ, then applying the remark below Proposition 3.1, there exists s ∈ (t0 , t1 ] such that x(t, t0 , φ, f ) ≪ x(t, t0 , ψǫ , gǫ ) for t0 t < s and η(x(s, t0 , φ, f )) = η(x(s, t0 , ψǫ , gǫ )) for some nontrivial η ∈ K ∗ . As η(x(t, t0 , φ, f )) < η(x(t, t0 , ψǫ , gǫ )) for t0 t < s, by Proposition 3.1, we conclude that d d dt |t=s η(x(s, t0 , φ, f )) dt |t=s η(x(s, t0 , ψǫ , gǫ )). But d η x(s, t0 , ψǫ , gǫ ) = η g s, xs (t0 , ψǫ , gǫ ) + ǫη(e) dt t=s > η f s, xs (t0 , ψǫ , gǫ ) η f s, xs (t0 , φ, f ) d = η x(s, t0 , φ, f ) , dt t=s

where the last inequality follows from (QMD). This contradiction implies that no such s can exist, proving the assertion.

306


In the case of the autonomous system (4.2), taking f = g in Theorem 1.1 implies that xt (φ) xt (ψ) for t 0 such that both solutions are defined. In other words, the semiflow Φ defined by (4.3) is monotone. In contrast to Theorem 3.2 of the previous section, if φ < ψ we cannot conclude that x(t, φ) < x(t, ψ) or xt (φ) < xt (ψ) since Φt is not generally one-to-one. A simple example is provided by the scalar equation (4.2) with r = 1 and f (φ) := max φ, which satisfies (QMD). Let φ < ψ be strictly increasing on [−1, −1/2], φ(−1) = ψ(−1) = 0, φ(−1/2) = ψ(−1/2) = 1, and φ(θ) = ψ(θ) = −2θ for −1/2 < θ 0. It is easy to see that x(t, φ) = x(t, ψ) for t 0. It is useful to have sufficient conditions for the positive invariance of K. By this we mean that t0 ∈ J and φ 0 implies x(t, t0 , φ) 0 for all t t0 for which it is defined. The following result provides the expected necessary and sufficient condition. The proof is similar to that of Theorem 4.1; the result is the delay analog of Proposition 3.3. T HEOREM 4.2. Assume that J × K ⊂ Ω where J is an open interval. Then K is positively invariant for (4.4) if and only if for all t ∈ J (PD) φ 0, λ ∈ K ∗ and λ(φ(0)) = 0 implies λ(f (t, φ)) 0 holds. Let L : J → L(C, Rn ) be continuous, where L(C, Rn ) denotes the space of bounded linear operators from C to Rn , and consider the initial value problem for the linear nonautonomous functional differential equation x ′ = L(t)xt ,

xt0 = φ.

(4.5)

Observing that (PD) and (QMD) are equivalent for linear systems, we have the following corollary. C OROLLARY 4.3. Let x(t, t0 , φ) be the solution of (4.5). Then x(t, t0 , φ) 0 for all t t0 and all φ 0 if and only if for each t ∈ J , (PD) holds for L(t). As in the case of ordinary differential equations, a stronger condition than (PD) for linear systems is that for every t ∈ J , there exists α ∈ R such that L(t)φ + αφ(0) 0 whenever φ 0. It is useful to invoke the Riesz Representation Theorem [171] in order to identify L(t) with a matrix of signed Borel measures η(t) = (η(t)ij ): L(t)φ =

0

dη(t)φ.

(4.6)

−r

The Radon–Nikodym decomposition of ηij with respect to the Dirac measure δ with unit mass at 0 gives ηij (t) = aij (t)δ + η˜ ij (t) where aij is a scalar and η˜ ij (t) is mutually singular with respect to δ. In particular, the latter assigns zero mass to {0}. Therefore, ˜ L(t)φ = A(t)φ(0) + L(t)φ,

˜ L(t)φ :=

0

−r

dη(t)φ. ˜

(4.7)


307

Continuity of the map t → A(t) follows from continuity of t → L(t). The decomposition (4.7) leads to sharp conditions for (PD) to hold for L(t). P ROPOSITION 4.4. (PD) holds for L(t) if and only if (a) A(t) satisfies (P) of Proposition 3.3, and ˜ (b) L(t)φ 0 whenever φ 0. P ROOF. If (a) and (b) hold, φ 0, λ ∈ K ∗ and λ(φ(0)) = 0 then λ(L(t)φ) = λ(A(t)φ(0)) ˜ + λ(L(t)φ) 0 because each summand on the right is nonnegative. Conversely, if (PD) holds for L(t), v ∈ ∂K, λ ∈ K ∗ , and λ(v) = 0, define φn (θ ) = enθ v on [−r, 0]. Then φn 0 and φn converges point-wise to zero, almost everywhere with respect to η(t). ˜ By (PD), ˜ λ(L(t)φn ) = λ(A(t)v + L(t)φ n ) 0. Letting n → ∞, we get λ(A(t)v) 0 implying that (P) holds for A(t). Let φ 0 be given and define φn (θ ) = [1 − enθ ]φ(θ) on [−r, 0], n 1. φn converges point-wise to φχ , where χ is the indicator function of the set [−r, 0), and φχ = φ almost everywhere with respect ˜ to η(t). ˜ If λ ∈ K ∗ , then λ(φn (0)) = 0 so applying (PD) we get 0 λ(L(t)φn ) = L(t)φ n. Letting n → ∞ we get (b). For the remainder of this section, we suppose that Ω = J × D where J is a nonempty ∂f open interval and D ⊂ C is open. Suppose that ∂φ (t, ψ) exists and is continuous on J × D n to L(C, R ). In that case, x(t, t0 , φ) is continuously differentiable in its last argument and ∂x y(t, t0 , χ) = ∂φ (t, t0 , φ)χ satisfies the variational equation y ′ (t) =

∂f t, xt (t, φ) yt , ∂φ

yt0 = χ.

(4.8)

See Theorem 2.4.1 of Hale and Verduyn Lunel [61]. We say that f (or (4.4)) is K-co∂f operative if for all (t, χ) ∈ J × D the function ψ → ∂φ (t, χ)ψ satisfies (PD). By Corollary 4.3 applied to the variational equation we have the following analog of Theorem 3.5 for functional differential equations. The proof is essentially the same. ∂f T HEOREM 4.5. Let ∂φ (t, ψ) exist and be continuous on J × D. If (QMD) holds for (4.4), then f is K-cooperative. Conversely, if D is p-convex and f is K-cooperative, then (QMD) holds for f .

Consider the nonlinear system x ′ (t) = g x(t), x(t − r1 ), x(t − r2 ), . . . , x(t − rm ) ,

(4.9)

308


where g(x, y 1 , y 2 , . . . , y m ) is continuously differentiable on R(m+1)n and rj +1 > rj > 0. Then ∂g ∂f ∂g (ψ) = (x, Y )δ + (x, Y )δ−rk , ∂φ ∂x ∂y k

(4.10)

k

where δ−rk is the Dirac measure with unit mass at {−rk } and x = ψ(0), y k = ψ(−rk ) and (x, Y ) := (x, y 1 , y 2 , . . . , y m ). By Theorem 4.5, Corollary 4.3, and Proposition 4.4, ∂g ∂g (QMD) holds if and only if for each (x, Y ), ∂x (x, Y ) satisfies condition (P) and ∂y k (x, Y ) is K-positive. If K = Rn+ , the condition becomes for all i, j, k; if, in addition, n = 1 then

∂gi ∂xj

(x, Y ) 0, for i = j and

∂g (x, Y ) 0 ∂y k

∂gi (x, Y ) 0 ∂yjk

for all k suffices.

4.3. Eventual strong monotonicity We begin by considering the linear system (4.5). The following hypothesis for the continuous map L : J → L(C, Rn ) reduces to (ST) of the previous section when r = 0: (STD) for all t ∈ J and φ 0 with φ(0) ∈ ∂K satisfying one of the conditions (a) φ(−r) > 0 and φ(0) = 0, or (b) φ(s) > 0 for −r s 0, there exists ν ∈ K ∗ such that ν(φ(0)) = 0 and ν(L(t)φ) > 0. The following result is the analog of Theorem 3.6 of the previous section for delay differential equations. T HEOREM 4.6. Let linear system (4.5) satisfy (PD) and (STD) and let t0 ∈ J . Then φ > 0, t t0 + 2r

)⇒ x(t, t0 , φ) ≫ 0.

In particular, xt (t0 , φ) ≫ 0 for t t0 + 3r. P ROOF. By Corollary 4.3, we have that x(t) := x(t, t0 , φ) 0 for all t t0 that belong to J . There exists t1 ∈ (t0 , t0 + r) such that x(t1 − r) = φ(t1 − r) = xt1 (−r) > 0 since φ > 0. If x(t1 ) = 0, then (STD)(a) implies the existence of ν ∈ K ∗ such that ν(L(t1 )xt1 ) > 0. As ν(x(t)) 0 for t t0 and ν(x(t1 )) = 0 we conclude that d d dt |t=t1 ν(x(t)) 0. But dt |t=t1 ν(x(t)) = ν(L(t1 )xt1 ) > 0, a contradiction. Therefore, x(t1 ) > 0. Now, by (4.7) ˜ x ′ = A(t)x + L(t)x t from which we conclude x(t) = X(t, t1 )x(t1 ) +

t t1

˜ X(t, r)L(r)x r dr,


309

where X(t, t0 ) is the fundamental matrix for y ′ = A(t)y satisfying X(t0 , t0 ) = I . From (a) of Proposition 4.4 and Corollary 3.4, it follows that X(t, t0 ) is K positive for t t0 . This, the fact that xr 0, and (b) of Proposition 4.4 imply that the integral belongs to K so we conclude that x(t) X(t, t1 )x(t1 ) > 0,

t t1 .

We claim that x(t) ≫ 0 for t t1 + r. If not, there is a t2 t1 + r such that x(t2 ) = xt2 (0) ∈ ∂K but xt2 (s) > 0 for −r s 0. Then (STD) implies the existence of ν ∈ K ∗ such that ν(x(t2 )) = 0 and ν(L(t2 )xt2 ) > 0. Since ν(x(t)) 0 for t t0 we must have d d dt |t=t2 ν(x(t)) 0. But dt |t=t2 ν(x(t)) = ν(L(t2 )xt2 ) > 0, a contradiction. We conclude that x(t) ≫ 0 for t t1 + r. In a sense, (STD)(a) says that r has been correctly chosen; (STD)(b) is more fundamental. The next result gives sufficient conditions for it to hold. P ROPOSITION 4.7. If L(t) satisfies (PD) and either (a) A(t) satisfies (ST), or ˜ (b) φ > 0 )⇒ L(t)φ ≫0 then (STD)(b) holds. P ROOF. This is immediate from the definitions, the decomposition (4.7), Proposition 4.4, ˜ and the expression ν(L(t)φ) = ν(A(t)φ(0)) + ν(L(t)φ). Theorem 4.6 leads immediately to a result on eventual strong monotonicity for the nonlinear system (4.4) where we assume that Ω = J × D as above. ∂f ∂φ (t, ψ)

T HEOREM 4.8. Let D be p-convex, L(C, Rn ),

exist and be continuous on J × D to

and f be K-cooperative. Suppose that (STD) holds for (t, ψ) ∈ J × D. Then φ0 , φ1 ∈ D, φ0 < φ1

∂f ∂φ (t, ψ),

for each

)⇒ x(t, t0 , φ0 ) ≪ x(t, t0 , φ1 )

for all t t0 + 2r for which both solutions are defined. P ROOF. By Theorem 4.5, we have x(t, t0 , φ0 ) x(t, t0 , φ1 ) for t t0 for which both solutions are defined. We apply the formula x(t, t0 , φ1 ) − x(t, t0 , φ0 ) =

0

1

∂x t, t0 , sφ1 + (1 − s)φ0 (φ1 − φ0 ) ds. ∂φ

Here, for ψ ∈ D and β ∈ C, y(t, t0 , β) :=

∂x ∂φ (t, t0 , ψ)β

∂f ∂φ (t, xt (t0 , ψ)).

satisfies the variational equa-

tion (4.5) where φ = β and L(t) = See Theorem 2.4.1 of Hale and Verduyn Lunel [61]. The desired conclusion will follow if we show that y(t, t0 , β) ≫ 0 for

310


t t0 + 2r for ψ = sφ1 + (1 − s)φ0 and β = φ1 − φ0 > 0. By Theorem 4.6, it suffices to show that L(t) satisfies (PD) and (STD). But this follows from our hypotheses. In the next result, Theorem 4.8 is applied to system (4.9). We make use of notation introduced below Theorem 4.5. C OROLLARY 4.9. Let g : R(m+1)n → Rn be continuously differentiable and satisfy ∂g (x, Y ) satisfies (P) for each (x, Y ) ∈ Z; (a) ∂x ∂g (b) for each k, ∂y k (x, Y ) is K positive; ∂g ∂g (x, Y ) satisfies (ST) or some ∂y (c) either ∂x k (x, Y ) is strongly positive on K. Then the hypotheses of Theorem 4.8 hold for (4.9).

P ROOF. Recalling (4.10), it is evident that (a) and (b) imply that (4.9) is K-cooperative. Hypothesis (c) and Proposition 4.7 imply that (STD) holds. In the special case that (4.9) is a scalar equation, m = 1 and K = R+ , then suffices to ensure an eventually strongly monotone semiflow.

∂g ∂y (x, y) > 0

4.4. K is an orthant 6 Our results can be improved in the case that K is a product cone such as Rn+ = ni=1 R+ , i.e., an orthant. The following example illustrates the difficulty with our present set up. x1′ (t) = −x1 (t) + x2 (t − 1/2), x2′ (t) = x1 (t − 1) − x2 (t).

Observe that (PD) holds for the standard cone. For initial data, take φ = (φ1 , φ2 ) ∈ C (r = 1) where φ1 = 0 and φ2 (θ ) > 0 for θ ∈ (−1, −2/3) and φ2 (θ ) = 0 elsewhere in [−1, 0]. The initial value problem can be readily integrated by the method of steps of length 1/2 and one sees that x(t) = 0 for all t −2/3. In the language of semiflows, φ > 0 yet Φt (φ) = Φt (0) = 0 for all t 0. The problem is that C([−1, 0], R2 ) is not the optimal state space; a better one is the product space X = C([−1, 0], R) × C([−1/2, 0], R). Obviously, an arbitrary cone in R2 will not induce a cone in the product space X. For the remainder of this section we focus on the standard cone but the reader should observe that an analogous construction works for any orthant K = {x: (−1)mi xi 0}. Motivated by the example in the previous paragraph, let r = (r1 , r2 , . . . , rn ) ∈ Rn+ be a vector of delays, R = max ri and define n 7 Cr = C [−ri , 0], R . i=1


311

Note that we allow some delays to be zero. We write φ = (φ1 , φ2 , . . . , φn ) for a generic point of Cr . Cr is a Banach space with the norm |φ| = |φi |. Let Cr+

n 7 C [−ri , 0], R+ = i=1

denote the cone of functions in Cr with nonnegative components. It has nonempty interior given by those functions with strictly positive components. As usual, we use the notation , 0 then we may redefine xt ∈ Cr as xt = (xt1 , xt2 , . . . , xtn ) where xti (θ ) = xi (t + θ ) for θ ∈ [−ri , 0]. Notice that now, the subscript signifying a particular component will be raised to a superscript when using the subscript “t” to denote a function. If D ⊂ Cr is open, J is an open interval and f : J × D → Rn is given, then the standard existence and uniqueness theory for the initial value problem associated with (4.4) is unchanged. Furthermore, Theorems 4.1 and 4.2, and Corollary 4.3 remain valid in our current setting where, of course, we need only make use of the coordinate maps η(x) = xi , 1 i n in (QMD) and (PD). Our goal now is to modify (STD) so that we may obtain a result like Theorem 4.6 that applies to systems such as the example above. We begin by considering the linear system (4.5) where L : J → L(Cr , Rn ) is continuous and let Li (t)φ := ei , L(t)φ, 1 i n. In our setting, L(t) satisfies (PD) if and only if: φ 0 and φi (0) = 0 implies Li (t)φ 0. T HEOREM 4.10. Let linear system (4.5) satisfy (PD) and (i) t ∈ J , rj > 0, φ 0, φj (−rj ) > 0 )⇒ Li (t)φ > 0 for some i; (ii) for every proper subset I of N := {1, 2, . . . , n}, there exists j ∈ N \ I such that Lj (t)φ > 0 whenever φ 0, φi (s) > 0, −ri s 0, i ∈ I . Then x(t, φ, t0 ) ≫ 0 if φ > 0 for all t t0 + nR. P ROOF. By (PD) and Corollary 4.3 we have x(t) 0 for t t0 . An application of the Riesz Representation Theorem and Radon–Nikodym Theorem implies that for i = 1, 2, . . . , n, we have Li (t)φ = ai (t)φi (0) +

n

0

j =1 −rj

φj (θ ) dθ ηij (t, θ ) = ai (t)φi (0) + L¯ i (t)φ,

where ηij (t) is a positive Borel measure on [−rj , 0], ai (t) ∈ R and L¯ i (t)φ 0 whenever φ 0. Moreover, t → ηij (t) and t → ai (t) are continuous. See Smith [190,194] for details. The representation of Li in terms of signed measures, η¯ ij , is standard; (PD) implies that ηij := η¯ ij must be positive for i = j and that η¯ ii has the Lebesgue decomposition η¯ ii = ai δ + ηii with respect to δ, the Dirac measure of unit mass at zero, and ηii is a positive measure which is mutually singular with respect to δ.

312


If xi (t1 ) > 0 for some i and t1 > t0 then from xi′ (t) = ai (t)xi (t) + L¯ i (t)xt ai (t)xi (t) we conclude from standard differential inequality arguments that xi (t) > 0 for t t1 . As φ > 0, there exists j such that φj > 0. If rj = 0 then xj (t0 ) > 0; if rj > 0 then xj (t1 − rj ) > 0 for some t1 ∈ (t0 , t0 + rj ). In this case, it follows from (i) that xi′ (t1 ) = Li (t1 )φ > 0 for some i and hence xi (t1 ) > 0. Hence, xi (t) > 0 for t t1 by the previous paragraph. Applying (ii) with I = {i} and t = t2 = t1 + ri we may find k = i such that xk′ (t2 ) = Lk (t2 )xt2 > 0 because xti2 (s) > 0, −ri s 0. Therefore, we must have xk (t2 ) > 0 and hence xk (t) > 0 for t t2 . Obviously, we may continue in this manner until we have all components positive for t t0 + nR as asserted. Theorem 4.10 leads directly to a strong monotonicity result for the nonlinear nonautonomous delay differential equation (4.4) in the usual way. We extend the definition of K-cooperativity of f to our present setup with state space Cr exactly as before. T HEOREM 4.11. Let D ⊂ Cr be p-convex,

∂f ∂φ (t, ψ)

, Rn ),

exist and be continuous on J × D to

L(Cr and f be K-cooperative. Suppose that for all (t, ψ) ∈ J × D, L(t) := satisfies the conditions of Theorem 4.10. Then φ0 , φ1 ∈ D, φ0 < φ1 , t t0 + nR

)⇒

∂f ∂φ (t, ψ)

x(t, t0 , φ0 ) ≪ x(t, t0 , φ1 ).

The biochemical control circuit with delays, modeled by the system x1′ (t) = g xn (t − rn ) − α1 x1 (t),

xj′ (t) = xj −1 (t − rj −1 ) − αj xj (t),

2j n

(4.11)

with decay rates αj > 0 and delays ri 0 with R > 0 provides a good application of Theorem 4.11 which cannot be obtained by Theorem 4.8 if the delays are distinct. We assume the g : R+ → R+ is continuously differentiable and g ′ > 0. Equation (4.11) is an autonomous system for which Cr+ is positively invariant by Theorem 4.2. See Smith [191, 194] for more on this application.

4.5. Generic convergence for delay differential equations The aim of this section is to apply Theorem 4.8 and Theorem 4.11 to the autonomous delay differential equation (4.2) to conclude that the generic solution converges to equilibrium. To Φ, defined by (4.3), we associate C, S and E, denoting respectively the sets of convergent, stable and equilibrium points. The main result of this section is the following. T HEOREM 4.12. Let f ∈ C 1 (D), (4.2) be cooperative on the p-convex open subset D of C or Cr and satisfy: (a) The hypotheses of Theorem 4.8 or of Theorem 4.11 hold; (b) Every positive semiorbit of Φ has compact closure in D and D = AC ∪ BC. Then


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(i) C ∩ S contains a dense open subset of D, consisting of points whose trajectories converge to equilibria; (ii) If E is compact there is a stable equilibrium, and an asymptotically stable equilibrium when E is finite. P ROOF. For definiteness, suppose that (4.2) is cooperative on the p-convex open subset D of C and that the hypotheses of Theorem 4.8 hold. The other case is proved similarly. Assumption (a) ensures that Φ is eventually strongly monotone. Moreover, the derivative of Φt (φ) with respect to φ exists and Φτ′ (φ)χ = yτ (t0 , χ), where y(t, t0 , χ) is the solution ∂f (xt (φ)) satisof the variational equation (4.8). As our hypotheses ensure that L(t) = ∂φ ′ fies (STD), we conclude from Theorem 4.6 that Φτ (φ) is strongly positive for τ 3r. Compactness of Φτ′ (φ) : C → C for τ r follows from the fact that a bound for yτ (t0 , χ), uniform for χ belonging to a bounded set B ⊂ C, can be readily obtained so, using (4.8), we may also find a uniform bound for y ′ (t, t0 , χ), τ − r t τ . See, e.g., Hale [58, Theorem 4.1.1] for more detail. The hypotheses of Theorem 2.26, with X = D, are fulfilled: D is normally ordered and D = BC ∪ AC; while (M) and (D ∗ ) hold as noted above. Therefore Theorem 2.26 implies the conclusion. In the special case that (4.2) is scalar (n = 1) we note that the set E of equilibria is totally ordered in Cr or C so the set of quasiconvergent points coincides with the set of convergent points: Q = C. The classical scalar delay differential equation (4.1) has been thoroughly investigated in the case of monotone delayed feedback (f (0) = 0 and f ′ > 0) by Krisztin et al. [105]. They characterize the closure of the unstable manifold of the trivial solution in case it is three-dimensional and determine in remarkable detail the dynamics on this invariant set. Smith and Thieme [198,200,194] introduce an exponential ordering, not induced by a cone in Rn , that extends the scope of application of the theory described here. One of the salient results from this work is that a scalar delay equation for which the product of the delay r and the Lipschitz constant of f is smaller than e−1 generates an eventually strongly monotone semiflow with respect to the exponential ordering and therefore the generic orbit converges to equilibrium: the dynamics mimics that of the associated ordinary differential equation obtained by ignoring the delay. See also work of Pituk [159]. We have considered only bounded delays. Systems of delay differential equations with unbounded and even infinite delay are also of interest. See Wu [234] for extensions to such systems. Wu and Freedman [235] and Krisztin and Wu [106–108] extend the theory to delay differential equations of neutral type.

5. Monotone maps 5.1. Background and motivating examples One of the chief motivations for the study of monotone maps is their importance in the study of periodic solutions to periodic quasimonotone systems of ordinary differential

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equations. See for example the monograph of Krasnosel’skii [99], the much cited paper of de Mottoni and Schiaffino [42], Hale and Somolinos [60], Smith [188,189], Liang and Jiang [121], and Wang and Jiang [229–231]. To fix ideas, let f : R × Rn → Rn be a locally Lipschitz function and consider the ordinary differential equation x ′ = f (t, x).

(5.1)

As usual, denote by x(t, t0 , x0 ) the noncontinuable solution of the initial value problem x(t0 ) = x0 , which for simplicity we assumed is defined for all t. If f is periodic in t of period one: f (t + 1, x) = f (t, x) for all (t, x), then it is natural to consider the period map T : Rn → Rn defined by T (x0 ) = x(1, 0, x0 ).

(5.2)

Its fixed points (periodic points) are in one-to-one correspondence with the periodic (subharmonic) solutions of (5.1). If K is a cone in Rn for which f satisfies the quasimonotone condition (QM), then it follows from Theorem 3.2 that T is a monotone map: x y implies T x T y. Moreover, T has the important property, not shared with general monotone maps, that it is an orientation-preserving homeomorphism. In a similar way, periodic solutions for second order parabolic partial differential equations with time-periodic data can be analyzed by considering period maps in appropriate function spaces. Here monotonicity comes from classical maximum principles. Hess [63] remains an up-to-date survey. See also Alikakos et al. [3] and Zhao [245]. Remarkable results are known for equations on a compact interval with standard boundary conditions. Chen and Matano [23] show that every forward (backward) bounded solution is asymptotic to a periodic solution; Brunovsky et al. [22] extend the result to more general equations. Chen et al. [24] give conditions for the period map to generate Morse–Smale dynamics and thus be structurally stable. Although monotonicity of the period map is an important consideration in these results, it is not the key tool. The fact that the number of zeros on the spatial interval of a solution of the linearized equation is non-increasing in time is far more important. See Hale [59] for a nice survey. A different theme in order-preserving dynamics originates in the venerable subject of nonlinear elliptic and parabolic boundary value problems. The 1931 edition of Courant and Hilbert’s famous book [34] refers to a paper of Bieberbach in Göttingen Nachrichten, 1912 dealing with the elliptic boundary value problem ∆u = eu in Ω, u|∂Ω = f , in a planar region Ω. A solution is found by iterating a monotone map in a function space. Courant and Hilbert extended this method to a broad class of such problems. Out of this technique grew the method of “upper and lower solutions” (or “supersolutions and subsolutions”) for solving, both theoretically and numerically, second order elliptic PDEs (see Amann [4], Keller and Cohen [95], Keller [93,94], Sattinger [176]). Krasnosel’skii and Zabreiko [101] trace the use of positivity in functional analysis—closely related to monotone dynamics— to a 1924 paper by Uryson [222] on concave operators. The systematic use of positivity in PDEs was pioneered Krasnosel’skii and Ladyzhenskaya [100] and Krasnosel’skii [98]. Amann [5] showed how a sequence {un } of approximate solutions to an elliptic problem can be viewed as the trajectory {T n u0 } of u0 under a certain monotone map T in a suitable


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function space incorporating the boundary conditions, with fixed points of T being solutions of the elliptic equation. The dynamics of T can therefore be used to investigate the equation. Thus when T is globally asymptotically stable, there is a unique solution; while if T has two asymptotically stable fixed points, in many cases degree theory yields a third fixed point. As Amann [6] emphasized, a few key properties of T —continuity, monotonicity and some form of compactness—allow the theory to be efficiently formulated in terms of monotone maps in ordered Banach spaces. Many questions in differential equations are framed in terms of eigenvectors of linear and nonlinear operators on Banach spaces. The usefulness of operators that are positive in some sense stems from the theorem of Perron [158] and Frobenius [51], now almost a century old, asserting that for a linear operator on Rn represented by a matrix with positive entries, the spectral radius is a simple eigenvalue having a positive eigenvector, and all other eigenvalues have smaller absolute value and only nonpositive eigenvectors. In 1912 Jentzsch [85] proved the existence of a positive eigenfunction with a positive eigenvalue for a homogeneous Fredholm integral equation with a continuous positive kernel. In 1935 the topologists Alexandroff and Hopf [2] reproved the Perron–Frobenius theorem by applying Brouwer’s fixed-point theorem to the action of a positive n × n matrix on the space of lines through the origin in Rn+ . This was perhaps the first explicit use of the dynamics of operators on a cone to solve an eigenvalue problem. In 1940 Rutman [173] continued in this vein by reproving Jentzsch’s theorem by means of Schauder’s fixed-point theorem, also obtaining an infinite-dimensional analog of Perron–Frobenius, known today as the Krein–Rutman theorem [104,214]. In 1957 G. Birkhoff [20] initiated the dynamical use of Hilbert’s projective metric for such questions. The dynamics of cone-preserving operators continues to play an important role in functional analysis; for a survey, see Nussbaum [149,150]. One outgrowth of this work has been a focus on purely dynamical questions about such operators; some of these results are presented below. Polyhedral cones in Euclidean spaces have lead to interesting quantitative results, including a priori bounds on the number of periodic orbits. For recent work see Lemmens et al. [117], Nussbaum [151], Krause and Nussbaum [102], and references therein. Monotone maps frequently arise as mathematical models. For example, the discrete Lotka–Volterra competition model (see May and Oster [136]): (un+1 , vn+1 ) = T (un , vn ) := un exp r(1 − un − bvn ) , vn exp s(1 − cun − vn )

generates a monotone dynamical system relative to the fourth-quadrant cone only when the intrinsic rate of increase of each population is not too large (r, s 1) and then only on the order interval [0, r −1 ] × [0, s −1 ] (Smith [192]). Fortunately in this case, every point in the first quadrant enters and remains in this order interval after one iteration. As is typical in ecological models, the Lotka–Volterra map is neither injective nor orientationpreserving or orientation-reversing. For monotone maps as models for the spread of a gene or an epidemic through a population, see Thieme [218], Selgrade and Ziehe [181], Weinberger [232], Liu [123] and the references therein.

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5.2. Definitions and basic results A continuous map T : X → X on the ordered metric space X is monotone if x y ⇒ T x T y, strictly monotone if x < y ⇒ T x < T y, strongly monotone if x < y ⇒ T x ≪ T y, and eventually strongly monotone if whenever x < y, there exists n0 1 such that T n x ≪ T n y. We call T strongly order-preserving (SOP) if T is monotone, and whenever x < y there exist respective neighborhoods U, V of x, y and n0 1 such that n n0 ⇒ T n U T n V .1 As with semiflows, eventual strong monotonicity implies the strong order preserving property. The orbit of x is O(x) := {T n x}n0 , and the omega limit set of x is ω(x) := 3 k k0 O(T x). If O(x) has compact closure, ω(x) is nonempty, compact, invariant (that is, T ω(x) = ω(x)) and invariantly connected. The latter means that ω(x) is not the disjoint union of two closed invariant sets [116]. If T (x) = x then x is a fixed point or equilibrium. E denotes the set of fixed points. More generally, if T k x = x for some k 1 we call x periodic, or k-periodic. The minimal such k is called the period of x (and O(x)). Let Y denotes an ordered Banach space with order cone Y+ . A linear operator A ∈ L(Y ) is called positive if A(Y+ ) ⊂ Y+ (equivalently, A is a monotone map) and strongly positive if A(Y+ \ {0}) ⊂ Int Y+ ) (equivalently, A is a strongly monotone map). The following result is useful for proving smooth maps monotone or strongly monotone: L EMMA 5.1. Let X ⊂ Y be a p-convex set and f : X → Y a locally C 1 map with quasiderivative h : U → L(Y ) defined on an open set U ⊂ Y . If the linear maps h(x) ∈ L(Y ) are positive (respectively, strongly positive) for all x ∈ U , then f is monotone (respectively, strongly monotone). P ROOF. By p-convexity it suffices to prove that every p ∈ X has a neighborhood N such that f |N ∩ X is monotone (respectively, strongly monotone). We take N to be an open ball in U centered at p. Suppose p + z ∈ X ∩ N , z > 0. By p-convexity, X ∩ N contains the line segment from p to p + z. The definition (above Lemma 2.15) of locally C 1 implies that the map g : [0, 1] → Y , t → f (p + tz) is C 1 with g ′ (t) = h(tz)z. Therefore f (p + z) − f (z) = g(0) − g(1) =

1 0

g ′ (t) dt =

1

h(tz)z dt. 0

Because h(tz) ∈ L(Y ) is positive and z > 0, we have h(tz)z ∈ Y+ , therefore f (p + z) − f (p) 0. If the operators h(tz) are strongly positive, f (p + z) − f (p) ≫ 0. P ROPOSITION 5.2 (Nonordering of Periodic Orbits). A periodic orbit of a monotone map is unordered. 1 Our use of “strongly order-preserving” conflicts with Dancer and Hess [38], who use these words to mean what we have defined as “strongly monotone”. Our usage is consistent with that of several authors. Takáˇc [208,209] uses “strongly increasing” for our SOP.


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P ROOF. If not, there exists x in the orbit such that T k (x) > x for some k > 0. Induction on n shows that T nk (x) > x for all n > 0. But if x has period m > 0, induction on k proves that T mk (x) = x. L EMMA 5.3 (Monotone Convergence Criterion). Assume T is monotone and O(z) has compact closure. If m 1 is such that T m z < z or T m z > z then ω(z) is an m-periodic orbit. P ROOF. Consider first the case m = 1. Compactness of O(z) implies the decreasing sequence {T k z} converges to a point p = ω(x). Now suppose m > 1. Applying the case just proved to the map T m , we conclude that {T km z} converges to a point p = T m (p). It follows that ω(z) = {p, Tp, T 2 p, . . . , T m−1 p}. Lemma 5.3 yields information on one-sided stability of compact limit sets when T is SOP; see Hirsch [70]. In order to state the following lemma succinctly, we call a set J ⊂ N an interval if it is nonempty and contains all integers between any two of its members. For a, b ∈ N we set [a, b] = {j ∈ N: a j b} (there will be no confusion with real intervals). Two intervals overlap if they have more than one point in common. Let J ⊂ N be an interval and f : J → X be a map. A subinterval [a, b] ⊂ J , a < b is rising if f (a) < f (b), and falling if f (b) < f (a). T HEOREM 5.4. A trajectory of a monotone map cannot have both a rising interval and a falling interval. P ROOF. Follows from Theorem 1.6.

L EMMA 5.5. If T is monotone, ω(z) cannot contain distinct points having respective neighborhoods U, V such that T r (U ) T r (V ) for some r 0. P ROOF. Follows from Theorem 5.4 (see proof of Lemma 1.7).

The next result is fundamental to the theory of monotone maps: T HEOREM 5.6 (Nonordering Principle). Let ω(z) be an omega limit set for a monotone map T . (i) No points of ω(z) are related by ≪. (ii) If ω(z) is a periodic orbit or T is SOP, no points of ω(z) are related by 1, the Limit Set Dichotomy as formulated above must fail: take a point q > p so near to p that O(p) = ω(p) = ω(q). Clearly ω(p), being a nontrivial periodic orbit, contains no fixed points. Thus the second assertion of the Limit Set Dichotomy fails in this case. Dancer and Hess [38] gave a simple example in Rk for prime k of a strongly monotone map with an asymptotically stable periodic point of period k which we describe below. Therefore the second alternative of the Limit Set Dichotomy can be no stronger than that ω(a) = ω(b) is a periodic orbit. The Limit Set Dichotomy fails even for strictly monotone maps in R2 . Let f (x) = 2 arctan(x), let a > 0 be its unique positive fixed point, and note that 0 < f ′ (a) < 1. Define T0 : R2 → R2 by T0 (x, y) := (f (y), f (x)). Then E = {(−a, −a), (0, 0), (a, a)} since f has no points of period 2. The fixed points of T02 are the nine points obtained by taking all pairings of −a, 0, a. An easy calculation shows that {(−a, a), (a, −a)} is an asymptotically stable period-two orbit of T0 because the Jacobian matrix of T02 is f ′ (a)2 times the identity matrix. T 0 is strictly monotone but not strongly monotone. Now consider the perturbations Tǫ (x, y) := T0 (x, y) + (ǫx, ǫy). It is easy to see that Tǫ is strongly monotone for ǫ > 0; and by the implicit function theorem, for small ǫ > 0, Tǫ has an asymptotically stable periodtwo orbit O(pǫ ) with pǫ near (−a, a). As noted in [38], this example can be generalized to Rk for prime k. Takáˇc [212] shows that linearly stable periodic points can arise for the period map associated with monotone systems of ordinary and partial differential equations. Other counterexamples for low-dimensional monotone maps can be found in Smith [192,195].


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As we have shown, asymptotically stable periodic orbits that are not singletons can exist for monotone, even strongly monotone maps. Later we will show that the generic orbit of a smooth, dissipative, strongly monotone map converges to a periodic orbit. Here, we show that every attractor contains a stable periodic orbit. Recall that a point p is wandering if there exists a neighborhood U of p and a positive integer n0 such that T n (U ) ∩ U = ∅ for n > n0 . The nonwandering set Ω, consisting of all points q that are not wandering, contains all limit sets. In the following, we assume that X is an open subset of the strongly ordered Banach space Y and T : X → X is monotone with compact orbit closures. The following result is adapted from Hirsch [71, Theorems 4.1, 6.3]. T HEOREM 5.8. If T is strongly monotone and K is a compact attractor, then K contains a stable periodic orbit. The proof relies on the following result that does not use strong monotonicity nor that K attracts uniformly: T HEOREM 5.9. Let p ∈ K be a maximal (resp., minimal) nonwandering point. Then p is periodic, and every neighborhood of p contains an open set W ≫ p (resp., W ≪ p) such that ω(x) = O(p) for all x ∈ W . P ROOF. Suppose K attracts the open neighborhood U of K and fix y ≫ p, y ∈ U . Since p is nonwandering there exists a convergent sequence xi → p and a sequence ni → ∞ such that T ni xi → p. For all large i, xi y. Passing to a subsequence, we assume that T ni y → q. By monotonicity and xi y for large i, we have q p. But q ∈ K ∩ Ω and the maximality of p requires q = p. Since p ≪ y and T ni y → p it follows that T m y ≪ y for some m. Lemma 5.3 implies that ω(y) is an m-periodic orbit containing p. As this holds for every y ≫ p, the result follows. L EMMA 5.10. Let p, q ∈ K be fixed points such that p ≪ q, p is order stable from below, and q is order stable from above. Then K ∩ [p, q] contains a stable equilibrium. P ROOF. Let R be a maximal totally ordered set of fixed points in K ∩ [p, q]. An argument similar to the one in the proof of Theorem 1.30 shows that the fixed point e := inf{z ∈ E ∩ R: z is order stable from above} is order stable. That e is stable follows from the analog of Proposition 1.28.

P ROOF OF T HEOREM 5.8. Theorem 5.9 shows that some iterate T n , n 0 has fixed points p, q as in Lemma 5.10, which result therefore implies Theorem 5.8. Jiang and Yu [90, Theorem 2] implies that if T is analytic, order compact with strongly positive derivative, then K must contain an asymptotically stable periodic orbit.

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5.3. The order interval trichotomy In this section we assume that X is a subset of an ordered Banach space Y with positive cone Y+ , with the induced order and topology. Much of the early work on monotone maps on ordered Banach spaces focused on the existence of fixed points for self maps of order intervals [a, b] such that a, b ∈ E; see especially Amann [6]. The following result of Dancer and Hess [38], quoted without proof, is crucial for analyzing such maps. Let u, v be fixed points of T . A doubly-infinite sequence {xn }n∈Z (Z is the set of all integers) in Y is called an entire orbit from u to v if xn+1 = T (xn ),

lim xn = u, lim xn = v.

n→−∞

n→∞

If xn xn+1 (respectively, xn < xn+1 ), the entire orbit is increasing (respectively, strictly increasing). If xn xn+1 (respectively, xn > xn+1 ), the entire orbit is decreasing (respectively, strictly decreasing). If the entire orbit {xn } is increasing but not strictly increasing, then xn = v for all sufficiently large n; and similarly for decreasing. Consider the following hypothesis: (G) X = [a, b] where a, b ∈ Y , a < b and T a = a, T b = b. The map T : X → X is monotone and T (X) has compact closure in X. T HEOREM 5.11 (The Order Interval Trichotomy). Under hypothesis (G), at least one of the following holds: (a) there is a fixed point c such that a < c < b; (b) there exists an entire orbit from a to b that is increasing, and strictly increasing if T is strictly monotone; (c) there exists an entire orbit from b to a that is decreasing, and strictly decreasing if T is strictly monotone. An extension of Theorem 5.11 to allow additional fixed points on the boundary of [a, b] is carried out in Hsu et al. [83]. Wu et al. [236] weaken the compactness condition. See Hsu et al. [83], Smith [192], and Smith and Thieme [201] for applications to generalized two-species competition dynamics. For related results see Hess [63], Matano [133], Poláˇcik [162], Smith [184,194]. A fixed point q of T is stable if every neighborhood of q contains a positively invariant neighborhood of q. An immediate corollary of the Order Interval Trichotomy is: C OROLLARY 5.12. Assume hypothesis (G), and let a and b be stable fixed points. Then there is a third fixed point in [a, b]. Corollary 5.14 establishes a third fixed point under different assumptions. In general, more than one of the alternatives (a), (b), (c) may hold (see [83]). The following complement to the Order Interval Trichotomy gives conditions for exactly one to hold; (iii) is taken from Proposition 2.2 of [83]. Consider the following three conditions:


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(a′ ) there is a fixed point c such that a < c < b; (b′ ) there exists an entire orbit from a to b; (c′ ) there exists an entire orbit from b to a. P ROPOSITION 5.13. Assume hypothesis (G). (i) If T is strongly order-preserving, exactly one of (a′ ), (b′ ), (c′ ) can hold. More precisely: Assume a < y < b and y has compact orbit closure. Then ω(y) = {b} if there is an entire orbit from a to b, while ω(y) = {a} if there is an entire orbit from b to a. (ii) If a ≪ b, at most one of (b′ ), (c′ ) can hold. (iii) Suppose a ≪ b, and E ∩ [a, b] \ {a, b} = ∅ implies E ∩ [[a, b]] \ {a, b} = ∅. Then at most one of (a′ ), (b′ ), (c′ ) can hold. P ROOF. For (i), consider an entire orbit {xn } from a to b. There is a neighborhood U of a such that T k U T k y for sufficiently large k. Choose xj ∈ U . Then T k xj T k y b for all large k. As limk→∞ T k xj = b and the order relation is closed, b is the limit of every convergent subsequence of {T k y}. The case of an entire orbit from b to a is similar. In (ii), choose neighborhoods U, V of a, b respectively such that U ≪ V . Fix j so that xj ∈ U . If y ∈ V then an argument similar to the proof of (i) shows that ω(y) = {b}. Hence there cannot be an entire orbit from b to a, since it would contain a point of V . Assume the hypothesis of (iii), and note that (ii) makes (b′ ) and (c′ ) incompatible. If ′ (a ), there is a fixed point c ∈ [[a, b]], and arguments similar to the proof of (ii) show that neither (b′ ) nor (c′ ) holds. C OROLLARY 5.14. In addition to hypothesis (G), assume T is strongly order preserving with precompact image. If some trajectory does not converge, there is a third fixed point. P ROOF. Follows from the Order Interval Trichotomy 5.11 and Proposition 5.13(i).

A number of authors have considered the question of whether a priori knowledge that every fixed point is stable implies the convergence of every trajectory. See Alikakos et al. [3], Dancer and Hess [38], Matano [133] and Takáˇc [209] for such results. The following theorem is adapted from [38]. A set A ⊂ X is a uniform global attractor for the map T : X → X if T (A) = A and dist(T n x, A) → 0 uniformly in x ∈ X. T HEOREM 5.15. Let a, b ∈ Y with a < b. Assume T : [a, b] → [a, b] is strongly order preserving with precompact image, and every fixed point is stable. Then E is a totally ordered arc J that is a uniform global attractor, and every trajectory converges. P ROOF. We first show that there exists a totally ordered arc of fixed points; this will not use the SOP property. O(a) is an increasing sequence converging to the smallest fixed point in [a, b]. Similarly, O(b) is a decreasing sequence converging to the largest fixed point in [a, b]. By renaming a and b as these fixed points, we may as well assume that a, b ∈ E. The stability hypothesis and Corollary 5.12 implies there is a fixed point c satisfying a < c < b.

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The same reasoning applies to [a, c] and [c, b], and can be repeated indefinitely to show that every maximal totally ordered set of fixed points is compact and connected, hence an arc (Wilder [233, Theorem I.11.23]). Thus by Zorn’s Lemma there is a totally ordered arc J ⊂ E joining a to b. Next we prove: Every unordered compact invariant set K is a point of J . This will not use precompactness of T ([a, b]). Set q = inf{e ∈ J : K e}. It suffices to prove q ∈ K, for then K, being unordered, reduces to {q}. If q ∈ / K then q > k. By SOP and invariance of K there is a are neighborhoods V of p and n > 0 such that K = T n (K) T (V ), hence K T n (V ∩ J ) = V ∩ J . This gives the contradiction K inf(V ∩ J ) < q. Every ω(x) is compact by the precompactness assumption, and unordered by the Nonordering Principle 5.6(ii). Total ordering of J therefore implies ω(x) is a point of J . This proves every trajectory converges. To show that J is a global attractor, let N be the open ǫ-neighborhood of J for an arbitrary ǫ > 0. The stability hypothesis implies N contains a positively invariant open neighborhood W of J . It suffices to prove T n (X) ⊂ W when n is sufficiently large. Convergence of all trajectories implies that for every x ∈ X there exists an open neighborhood U (x) of n Precompactness of T (X) implies x and n(x) > 0 such that T (x) ∈ W for all n n(x). T (X) ⊂ U (xi ) for some finite set {xi }. Hence T n (X) ⊂ W provided n > max{n(xi )}. If the map T in Theorem 5.15 is C 1 and strongly monotone, then E is a smooth totally ordered arc by a result of Takáˇc [211].

5.3.1. Existence of fixed points Dancer [37] obtained remarkable results concerning the dynamics of monotone maps with some compactness properties: Limit sets can always be bracketed between two fixed points, and with additional hypotheses these fixed points can be chosen to be stable. The next two theorems are adapted from [37]. A map T : Y → Y is order compact if it takes each order interval, and hence each order bounded set, into a precompact set. T HEOREM 5.16. Let X be an order convex subset of Y . Assume that T : X → X is monotone and order compact, with every orbit having compact closure in X and every omega limit set order bounded. Then for all z ∈ Y there are fixed points f, g such that f ω(z) g. P ROOF. There exists u ∈ X such that u ω(z) because omega limit sets order bounded. Since T (ω(z)) = ω(z), it follows that ω(z) T i u for all i, hence ω(z) ω(u). Similarly, there exists s ∈ X such that ω(u) ω(s). The set F := {x ∈ Y : ω(z) x ω(s)} is the intersection of closed order intervals, hence closed and convex, nonempty because it contains ω(u), and obviously order bounded. Moreover F ⊂ X because X is order convex. Therefore T (F ) is defined and is precompact. Monotonicity of T and invariance of ω(z) and ω(s) imply T (F ) ⊂ F . It follows from the Schauder fixed point theorem that there is a fixed point g ∈ F , and g ω(z) as required. The existence of f is proved similarly. The cone Y+ is reproducing if Y = Y+ − Y+ . This holds for many function spaces whose norms do not involve derivatives. If Y+ has nonempty interior, it is reproducing: any x ∈ Y


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can be expressed as x = λe − λ(e − λ−1 x) ∈ Y+ − Y+ , where e ≫ 0 is arbitrary and λ > 0 is a sufficiently large real number. T HEOREM 5.17. Let X ⊂ Y be order convex. Assume T : X → X is monotone, completely continuous, and order compact. Suppose orbits are bounded and omega limits sets are order bounded. (i) For all z ∈ X there are fixed points f, g such that f ω(z) g. (ii) Assume Y+ is reproducing, X = Y or Y+ , and E is bounded. Then there are fixed points eM = sup E and em = inf E, and all omega limit sets lie in [em , eM ]. Moreover, if x em then ω(x) = {em }, while if x eM then ω(x) = {eM }. (iii) Assume Y+ is reproducing, X = Y or Y+ , E is bounded, and T is strongly order preserving. Suppose z0 ∈ Y is not convergent. Then there are three fixed points f < p < g such that f < ω(z0 ) < g. If T is strongly monotone, f and g can be chosen to be stable. P ROOF. We prove all assertions except for the stability in (iii). Complete continuity implies that every positively invariant bounded set is precompact. Therefore orbit closures are compact and omega limit sets are compact and nonempty, so (i) follows from Theorem 5.16. To prove (ii), note that E is compact because it is bounded invariant and closed. Choose a maximal element eM ∈ E (Lemma 1.1). We must show that eM e for every e ∈ E. Since the order cone is reproducing, eM − e = v − w with v, w 0. Set u := e + v + w. Then u ∈ X, u e, and u eM . Monotonicity implies eM = T i eM T i u for all i 0, hence eM ω(u). By Theorem 5.16 there exists g ∈ E such that ω(u) g. Hence eM g, whence eM = g by maximality. We now have eM ω(u) g = eM , so ω(u) = {eM }. Monotonicity implies (as above) e ω(u), therefore e eM as required. This proves eM = sup E, and the dual argument proves em = inf E. If x em then ω(x) em by monotonicity; but ω(x) em by (i), so ω(x) = {em }. Similarly for the case x eM . To prove the first assertion of (iii), note that em < ω(z) < eM by (i) and the Nonordering Principle 5.6(ii). Monotonicity and order compactness of T imply [em , eM ] is positively invariant with precompact image. As T is SOP, there is a third fixed point in [em , eM ] by Corollary 5.14.

5.4. Sublinearity and the cone limit set trichotomy Motivated by the problem of establishing the existence of periodic solutions of quasimonotone, periodic differential equations defined on the positive cone in R n , Krasnosel’skii pioneered the dynamics of sublinear monotone self-mappings of the cone [99]. We will prove Theorem 5.20 below, adapted from the original finite-dimensional version of Krause and Ranft [103]. Let Y denote an ordered Banach space with positive cone Y+ . Denote the interior (possibly empty) of Y+ by P . A map T : Y+ → Y+ is sublinear (or “subhomogeneous”) if 0 < λ < 1 )⇒ λT (x) T (λx),

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and strongly sublinear if 0 < λ < 1, x ≫ 0 )⇒ λT (x) ≪ T (λx). Strong sublinearity is the strong concavity assumption of Krasnosel’skii [99]. It can be verified by using the following result from that monograph: L EMMA 5.18. T : P → Y is strongly sublinear provided T is differentiable and T x ≫ T ′ (x)x for all x ≫ 0. P ROOF. Let F (s) = s −1 T (sx) for s > 0 and some fixed x ≫ 0. Then F ′ (s) = −s −2 T (sx) + s −1 T ′ (sx)x ≪ 0 by our hypothesis. So for 0 < λ < 1, we have φ T x − λ−1 T (λx) = φ F (1) − φ F (λ) < 0

for every nontrivial φ ∈ Y+∗ , the dual cone in Y ∗ , because conclusion follows from Proposition 3.1.

d ds φ(F (s))

< 0. The desired

C OROLLARY 5.19. Assume Y is strongly ordered. A continuous map T : Y+ → Y is sublinear provided T is differentiable in P and T x T ′ (x)x for all x ≫ 0. P ROOF. By continuity it suffices to prove T |P is sublinear. Fix e ≫ 0. For each δ > 0 the map P → Y , x → T x + δe is strongly sublinear by Lemma 5.18. Sending δ to zero implies T is sublinear. Krause and Ranft [103] have results establishing sublinearity of some iterate of T , which is an assumption used in Theorem 5.20 below. The following theorem demonstrates global convergence properties for order compact maps that are monotone and sublinear in a suitably strong sense. T HEOREM 5.20 (Cone Limit Set Trichotomy). Assume T : Y+ → Y+ is continuous and monotone and has the following properties for some r 1: (a) T r is strongly sublinear; (b) T r x ≫ 0 for all x > 0; (c) T r is order compact. Then precisely one of the following holds: (i) each nonzero orbit is order unbounded; (ii) each orbit converges to 0, the unique fixed point of T ; (iii) each nonzero orbit converges to q ≫ 0, the unique nonzero fixed point of T . A key tool in the proofs of such results is Hilbert’s projective metric and the related part metric due to Thompson [219]. We define the part metric p(x, y) here in a very limited way, as a metric on P (which is the “part”). For x, y ≫ 0, define p(x, y) := inf ρ > 0: e−ρ x ≪ y ≪ eρ y .


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The family of open order intervals in P forms a base for the topology of the part metric. It is easy to see that the identity map of P is continuous from the original topology on P to that defined by the part metric. When Y = Rn with vector ordering, with P = Int(Rn+ ), the part metric is isometric to the max metric on Rn , defined by dmax (x, y) = maxi |xi − yi |, via the homeomorphism Int(Rn+ ) ≈ Rn , x → (log x1 , . . . , log xn ). Restricted to compact sets in Int(Rn+ ), the part metric and the max metric are equivalent in the sense that there exist α, β > 0 such that α p(x, y) |x − y|max β p(x, y). The usefulness of the part metric in dynamics stems from the following result. Recall map T between metric spaces is a contraction if it has a Lipschitz constant < 1, and it is nonexpansive if it has Lipschitz constant 1. We say T is strictly nonexpansive if p(T x, T y) < p(x, y) whenever x = y. P ROPOSITION 5.21. Let T : P → P be a continuous, monotone, sublinear map. (i) T is nonexpansive for the part metric. (ii) If T is strongly sublinear, T is strictly nonexpansive for the part metric. (iii) If T is strongly monotone, A ⊂ P , and no two points of A are linearly dependent, then T |A is strictly nonexpansive for the part metric. (iv) Under the assumptions of (ii) or (iii), 3 if L ⊂ A is compact (in the norm topology) and T (L) ⊂ L, then the set L∞ = n>0 T n (L) is a singleton.

P ROOF. Fix distinct points x, y ∈ A and set ep(x,y) = λ > 1, so that λ−1 x y λx and λ is the smallest number with this property. By sublinearity and monotonicity, λ−1 T x T λ−1 x T y T (λx) λT x

(5.3)

which implies p(T x, T y) p(x, y). If T is strongly sublinear, the first and last inequalities in (5.3) can be replaced by ≪, which implies p(T x, T y) < p(x, y). When x and y are linearly independent, λ−1 x < y < λx. If also T is strongly monotone, (5.3) is strengthened to λ−1 T x T λ−1 x ≪ T y ≪ T (λx) λT x

which also implies p(T x, T y) < p(x, y). To prove (iv), observe first that if L is compact in the norm metric, it is also compact in the part metric. In both (ii) and (iii) T reduces the diameter in the part metric of every compact subset of L. Since T maps L∞ onto itself but reduces its part metric diameter, (iv) follows. P ROOF OF THE C ONE L IMIT S ET T RICHOTOMY 5.20. We first work under the assumption that r = 1. In this case Proposition 5.21 shows that every compact invariant set in P reduces to a fixed point, and there is at most one fixed point in P . It suffices to consider the orbits of points x ∈ P , by (b).

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Suppose there is a fixed point q ≫ 0. There exist numbers 0 < λ < 1 < µ such that x ∈ [λq, µq] ⊂ P . For all n we have 0 ≪ λq = λT n q T n (λq) T n x T n (µq) µT n q = µq. Hence O(x) ⊂ [λq, µq], so O(T x) lies in T ([λp, µq]), which is precompact by (c). Therefore ω(x) is a compact unordered invariant set in P . Proposition 5.21(iii) implies that ω(x) = {q}. This verifies (iii). Case I: If some orbit O(y) is order unbounded, we prove (i). We may assume y ≫ 0. There exists 0 < γ < 1 such that γ y ≪ x. Then γ T n y T n (γ y) T n x, implying O(x) is unbounded. Case II: If 0 ∈ ω(y) for some y, we prove (ii). We may assume y ≫ 0. Fix µ > 1 with x ≪ µy. Then 0 T n x T n (µy) µT n y → 0. Therefore O(x) is compact and T n x → 0. Case III: If the orbit closure O(x) ⊂ [a, b] ⊂ P , then (iii) holds. For O(x) is compact by (c), so ω(x) is a nonempty compact invariant set. Because ω(x) ⊂ O(x) ⊂ P , Case I implies (iii). Cases I, II and III cover all possibilities, so the proof for r = 1 is complete. Now assume r > 1. One of the statements (i), (ii), (iii) is valid for T r in place of T . If (i) holds for T r , it obviously holds for T . Assume (ii) holds for T r . If x > 0 then ω(x) = {0, T (0), . . . , T r−1 (0)}. As this set is compact and T r invariant, it reduces to {0}, verifying (ii) for T . A similar argument shows that if (iii) holds for T r , it also holds for T . The conclusion of the Cone Limit Trichotomy can fail for strongly monotone sublinear maps—simple linear examples in the plane have a line of fixed points. But the following holds: T HEOREM 5.22. Assume: (a) T : Y+ → Y+ is continuous, sublinear, strongly monotone, and order compact; (b) for each x > 0 there exists r ∈ N such that T r x ≫ 0. Then: (i) either O(x) is not order bounded for all x > 0, or O(x) converges to a fixed point for all x 0; (ii) the set of fixed points > 0 has the form {λe: a λ b} where e ≫ 0 and 0 a b ∞. P ROOF. Let y > 0 be arbitrary. If O(y) is not order bounded, or 0 ∈ ω(y), the proof of (i) follows Cases I and II in the proof of the Cone Limit Set Trichotomy 5.20. If O(x) ⊂ [a, b] ⊂ P , then ω(y) is a compact invariant set in P , as in Case III of 5.20. As ω(y) is unordered, every pair of its elements are linearly independent. Therefore Proposition 5.21(iv) implies ω(y) reduces to a fixed point, proving (i). The same reference shows that all fixed points lie on a ray R ⊂ Y+ through the origin, which must pass through some


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e ≫ 0 by (b). Suppose p, q are distinct fixed points and 0 ≪ p ≪ x 0, κ ∈ (ρ, 1) such that for each x ∈ U and all n n T x − p cκ n x − p .

In the more delicate case that ρ 1, Mierczyński [139] obtains a smooth hypersurface C, which is an analog for T of the codimension-one linear subspace V2 invariant under the linearized mapping T ′ (p):

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T HEOREM 5.24. If ρ 1 there exists a codimension-one embedded invariant manifold C ⊂ X of class C 1 having the following properties: (i) C = {x + P w + R(w)v: w ∈ O} where R : O → R is a C 1 map defined on the relatively open subset O of V2 containing 0, satisfying R(0) = R ′ (0) = 0. In particular, C is tangent to V2 at p. (ii) C is unordered. (iii) C = {p ∈ X: T n x − p /κ n → 0} = {x ∈ X: T n x − p /κ n is bounded}, for any κ, τ < κ < ρ. In particular, C ⊂ K. (iv) K \ C = {x ∈ K: T n x − p /κ n → ∞} = {x ∈ K: T n x − p /κ n is unbounded}, for any κ, τ < κ < ρ. (v) K \ C = K ∩ M. Conclusion (v) implies most orbits converging to p do so monotonically, but more can be said. Indeed, K ∩ M+ = {x ∈ K: (T n x − p)/ T n x − p → −v} and a similar result for K ∩ M− with v replacing −v holds. The manifold C is a local version of the unordered invariant hypersurfaces obtained by Takáˇc in [209]. Corresponding to the space V1 spanned by v ≫ 0 for T ′ (p), a locally forward invariant, one dimensional complement to the codimension one manifold C is given in the following result. T HEOREM 5.25. There is ǫ > 0 and a one-dimensional locally forward invariant C 1 manifold W ⊂ B(p; ǫ), tangent to V at p. If ρ > 1, then W is locally unique, and for each x ∈ W there is a sequence {x−n } ⊂ W with T x−n = x−n+1 , x0 = x, and κ n x−n − p → 0 for any κ, 1 < κ < ρ. Here B(p; ǫ) is the open ǫ-ball centered at p. Local forward invariance of W means that x ∈ W and T x ∈ B(x; ǫ) implies T x ∈ W . Related results are obtained by Smith [184]. In summary, the above results assert that the dynamical behavior of the nonlinear map T behaves near p like that of its linearization T ′ (p). Obviously, the above results can be applied at a periodic point p of period k by considering the map T k which has all the required properties. Mierczyński [139] uses the results above to classify the convergent orbits of T . Similar results are obtained by Takáˇc in [210]. It is instructive to consider the sort of stable bifurcations that can occur from a linearly stable fixed point, or a linearly stable periodic point, for a one parameter family of mappings satisfying the hypotheses of the previous results, as the parameter passes through a critical value at which ρ = 1. The fact that there is a simple positive dominant eigenvalue of (T k )′ (p) ensures that period-doubling bifurcations from a stable fixed point or from a stable periodic point, as a consequence of a real eigenvalue passing through −1, cannot occur. In a similar way, a Neimark–Sacker [113] bifurcation to an invariant closed curve cannot occur from a stable fixed or periodic point. These sorts of bifurcations can occur from unstable fixed or periodic points but then they will “be born unstable.” The generic orbit of a smooth strongly order preserving semiflow converges to fixed point but such a result fails to hold for discrete semigroups, i.e., for strongly order preserving mappings. Indeed, such mappings can have attracting periodic orbits of period


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exceeding one as we have seen. However, Terešˇcák [217], improving earlier joint work with Poláˇcik [164,165], and [65], has obtained the strongest result possible for strongly monotone, smooth, dissipative mappings. T HEOREM 5.26 (Terešˇcák, 1996). Let T : Y → Y be a completely continuous, C 1 , point dissipative map whose derivative is strongly positive at every point of the ordered Banach space Y having cone Y+ with nonempty interior. Then there is a positive integer m and an open dense set U ⊂ Y such that the omega limit set of every point of U is a periodic orbit with period at most m. The map P is point dissipative (see Hale [58]) provided there is a bounded set B with the property that for every x ∈ X, there is a positive integer n0 = n0 (x) such that P n x ∈ B for all n n0 . We note that the hypothesis that T ′ (x) is strongly positive implies that T is strongly monotone by Lemma 5.1.

5.6. Monotone planar maps A remarkable convergence result for planar monotone maps was first obtained by de Mottoni and Schiaffino [42]. They focused on the period-map for the two-species, Lotka– Volterra competition system of ordinary differential equations with periodic coefficients. The full generality of their arguments was recognized and improved upon by Hale and Somolinos [60] and Smith [188,189,192]. We follow the treatment Smith in [192]. In addition to the usual order relations on R2 , , 0 for x ∈ A.


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(c) T ′ (x)(K) ⊂ K for x ∈ A. (d) T is injective. Hypothesis (H− ) is identical except the inequality is reversed in (b). L EMMA 5.29. If T : A → A satisfies (H+ ), then T is competitive and (O+ ) holds. If (H− ) holds, then T is competitive and (O− ) holds. P ROOF. T is competitive by hypothesis (c) since A is p-convex with respect to K . Assuming that (H+ ) holds, x, y, T x, T y ∈ A and T x ≪ T y, we will show that x ≪ y. According to Lemma 5.27, the only alternative to x ≪ y is y ≪ x so we assume the latter for contradiction. Let a and b be the northwest and southeast corners of the rectangle [y, x] ⊂ A so that a ≪K b and [y, x] = [a, b]K . Since T is competitive on A, T ([y, x]) ⊂ [T a, T b]K and T x ≪ T y implies that T a ≪K T b. Consider the oriented Jordan curve forming the boundary of [y, x] starting at a and going horizontally to x, then going vertically down to b, horizontally back to y and vertically up to a. As T is injective on A, the image of this curve is an oriented Jordan curve. Monotonicity of T implies that the image curve is contained in [T a, T b]K , begins at T a and moves monotonically with respect to K (southwest) through T x and then monotonically to T b before moving monotonically (decreasing or northwest) from T b through T y and on to T a. (H+ )(b) implies that T is locally orientation preserving, so upon traversing the first half of the image curve from T a to T y to T b, the curve must make a “right turn” at T b before continuing on to T x and to T a. As the image curve cannot intersect itself, we see that T x ≪ T y cannot hold, a contradiction. In specific examples it is often difficult to check that T is injective. It automatically holds if A is compact and connected and there exists z ∈ T (A) such that the set T −1 (z) is a single point. This is because the cardinality of T −1 (w) is finite and constant for w ∈ T (A) by Chow and Hale [26, Lemma 2.3.4]. The following is an immediate corollary of Theorem 5.28 and Lemma 5.29. C OROLLARY 5.30. If T : A → A satisfies (H+ ), then {T n x} is eventually component-wise monotone for every x ∈ A. In this case, if an orbit has compact closure in A, then it converges to a fixed point of T . If T satisfies (H− ), then {T 2n x} is eventually component-wise monotone for every x ∈ A. In this case, if an orbit has compact closure in A, then its omega limit set is either a fixed point or a period-two orbit. As an application of Corollary 5.30, we recall the celebrated results of de Mottoni and Schiaffino [42] for the periodic Lotka–Volterra system x ′ = x r(t) − a(t)x − b(t)y , (5.4) y ′ = y s(t) − c(t)x − b(t)y ,

where r, s, a, b, c, d are periodic of period one and a, b, c, d 0. The period map T : R2+ → R2+ , defined by (5.2) for (5.4), is strictly monotone relative to the fourth quadrant cone K by virtue of Theorem 3.5. Indeed, (5.4) is a competitive system relative to

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the cone R2+ (the off-diagonal entries of the Jacobian J = J (t, x, y) of the right-hand side are nonpositive), and every such system is monotone relative to K. Observe that J + αI , for large enough α > 0, has nonnegative diagonal entries so (J + αI )(u, v)T ∈ K if (u, v)T ∈ K (i.e., u 0, v 0). T is strongly monotone relative to K in Int R2+ if b, c > 0 by Corollary 3.11. Because T is injective and orientation preserving by Liouville’s theorem, (H+ ) holds. Orbits are seen to be bounded by simple differential inequality arguments, e.g., applied to x ′ x[r(t) − a(t)x]. Consequently, by Corollary 5.30, all orbits O(T ) converge to a fixed point; equivalently, every solution of (5.4) is asymptotic to a period-one solution. System (5.4) is most interesting when each species can survive in the absence of its competitor, i.e. the time average of r and s are positive. In that case, aside from the trivial fixed point E0 := (0, 0), there are unique fixed points of type E1 := (e, 0) and E2 := (0, f ). Of course, e, f > 0 give initial data corresponding to the unique nontrivial one-periodic solutions of the scalar equations: x ′ = x[r(t) − a(t)x] and y ′ = y[s(t) − d(t)y]. The dynamics of the period map for these equations is described by alternative (iii) of Theorem 5.20. It is shown by de Mottoni and Schiaffino that there is a monotone, relative to K, T -invariant curve joining E1 to E2 which is the global attractor for the dynamics of T in R2+ \ {E0 }. This work has inspired a very large amount of work on competitive dynamics. See Hale and Somolinos [60], Smith [188,189], Hess and Lazer [64], Hsu et al. [83], Smith and Thieme [201], Wang and Jiang [230,231,229], Liang and Jiang [121], Zanolin [238].

6. Semilinear parabolic equations The purpose of this section is to analyze the monotone dynamics in a broad class of second order, semilinear parabolic equations. For basic theory and further information on many topics we refer the reader to books of Amann [11], Henry [62] Cholewa and Dlotko [25], Hess [63], Lunardi [124] and Martin [125], the papers of Amann [7–10], and the survey article of Poláˇcik [163]. Solution processes for semilinear parabolic problems have been obtained by many authors; see for example [3,8,38,62,63,124,125,134,147,163,194,174,208,246]. We briefly outline the general procedure, due to Henry, with important improvements by Mora and Lunardi. To balance the sometimes conflicting goals of order, topology and dynamics, the domain of a solution process must be chosen carefully. We rely on results of Mora [147], refined by Lunardi [124], for solution processes in Banach subspaces CBk (Ω) ⊂ C k (Ω), k = 0, 1 determined by the boundary operator B.

6.1. Solution processes for abstract ODEs If Y and X are spaces such that Y is a subset of X and the inclusion map Y → X is continuous, we write Y ֒→ X. When Y and X are ordered Banach space structures, this notation tacitly states that Y is a linear subspace of X and Y+ = Y ∩ X+ . The domain and range of any map h are denoted by D(h) and R(h).


333

:= {(t, t0 , z) ∈ R+ × R+ × 6.1.1. Processes Let Z be a topological space and set Z Z: t t0 }. A process in Z is a family Θ = {Θt,t0 }0t0 t0 has the corresponding property. 6.1.2. Solution processes Let X be a Banach space. A denotes a linear operator (usually unbounded) in X with domain D(A) ⊂ X, that is sectorial in the following strong sense: • A is a densely defined, closed operator generating an analytic semigroup {et A }t0 in L(X), and the resolvent operators (λI − A)−1 ∈ L(X) are compact for sufficiently large λ 0. The latter property ensures that et A is compact for t > 0 [156, Theorem 2.3.3]. We make D(A) into a Banach space with the graph norm x D(A) = x + Ax , or any equivalent norm. Then A : D(A) → X is bounded, and D(A) ֒→ X. For 0 α 1 we define the fractional power domain of Aα to be X α = X α (A) := D(Aα ). Thus we have [62] D(A) ֒→ X α ֒→ X,

D(A) = X.

Let F : [0, ∞) × X α → X be a continuous map that is locally Lipschitz in the second variable, i.e.: • F |[0, τ ] × B(r) has Lipschitz constant L(τ, r) in the second variable whenever [0, τ ] ⊂ [0, ∞) and B(r) is the closed ball of radius r in X α . Locally Hölder in the first variable is defined analogously. We say F is C 1 in the second variable if ∂w F (t, w) is continuous.

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The data (X, A, F ) determine the abstract initial value problem

u′ (t) = Au(t) + F (t, u(t)) u(t0 ) = u0 ∈ X.

(t > t0 ),

(6.1)

A continuous curve u : [t0 , τ ) → X, t0 < τ ∞ is a (classical) solution through (t0 , u0 ) if u(t) ∈ D(A) for t0 < t < τ and (6.1) holds. It is well known (e.g., Lunardi [124, 4.1.2]) that every solution is also a mild solution, i.e., it satisfies the integral equation u(t) = e(t−t0 )A u0 +

t

t0

e(t−s)A F s, u(s) ds

(t0 t < τ ).

(6.2)

Moreover, every mild solution is a solution provided F is locally Hölder in t (Lunardi [124, Proposition 7.1.3]). A classical or mild solution is maximal if it does not extend to a classical or mild solution on a larger interval in [t0 , ∞); it is then referred to as a trajectory at (t0 , u0 ), and its image is an orbit. When such a trajectory is unique it is denoted by t → u(t, t0 , u0 ). In this case the escape time of (t0 , u0 ) is τ (t0 , u0 ) := τ . If τ = ∞ the trajectory is called global. The following basic result means that Eq. (6.1) is well-posed in a strong sense, and that solutions enjoy considerable uniformity and compactness. T HEOREM 6.1. Let (t0 , u0 ) ∈ R+ × X α . There is a unique mild trajectory at (t0 , u0 ), and it is a classical trajectory provided F (t, u) is locally Hölder in t. If t0 < t1 < τ (t0 , u0 ), there is a neighborhood U of x0 in X α and M > 0 such that

u(t, t0 , u1 ) − u(t, t0 , u2 ) Xα M u1 − u2 Xα ,

u1 , u2 ∈ U.

There exist C > 0, t0 < t1 < τ (t0 , u0 ), a bounded neighborhood N of u0 in X and a continuous map Ψ : [t0 , t1 ] × N → X,

(t, v) → u(t, t0 , v),

where u(t, t0 , v) is a mild solution, such that the following hold. If s, t ∈ (t0 , t1 ], 0 α < 1 and v, w ∈ N : (i) Ψ (s, v) − Ψ (s, w) C v − w ; (ii) Ψ (s, v) − Ψ (s, w) Xα (s − t0 )−α C v − w ; (iii) Ψ ([s, t1 ] × N ) is precompact in X α ; (iv) u(·, t0 , v) : (t0 , t] → X α and u(·, t0 , v) : [t0 , t] → X are continuous; (v) trajectories bounded in X α are global. P ROOF. Lunardi [124, Theorems 7.1.2, 7.1.3 and 7.1.10] proves the first assertion. Items (i), (ii) and (iv) follow from [124, Theorem 7.1.5], and (v) follows from Theorem 7.1.8 (see also Henry [62, 3.3.4]). Fix β with α < β < 1. As N is bounded in X, Ψ (s × N ) is bounded in X β by (ii) (with α in (ii) replaced by β). Therefore Ψ (s × N ) is precompact in X α , and (iii) follows because Ψ defines a local semiflow on R+ × X α .


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Equation (6.1) induces a solution process Θ in X, defined by Θt,t0 (u0 ) := u(t, t0 , u0 ). Its restriction to X α defines an induced solution process on that space. When Eq. (6.1) is autonomous, i.e., F (t, u) = F (u), this solution process boils down to a local semiflow Φ in X α , defined by Φt (t0 , u0 ) = u(t + t0 , t0 , u0 ). When F (t, u) has period λ > 0 in t, the solution process is λ-periodic: Θt,t0 ≡ Θt+λ, t0 +λ . In this case Θ reduces to a local semiflow on S1 × X α , the dynamics of which are largely determined by the Poincaré map T := Θλ,0 which maps an open subset of X α continuously into X α . Let S be a set and Z a Banach space. We use expressions such as “S is bounded in Z” or “S ⊂ Z is bounded” to mean S ⊂ Z and supu∈S u Z < ∞. Note that S may also be unbounded in other Banach spaces. A map defined on a metric space is compact if every bounded set in its domain has precompact image. It is locally compact if every point of the domain has a neighborhood with precompact image. A Banach space Y is adapted to the data (X, A, F ) if the following two conditions hold: X α ֒→ Y ֒→ X

(6.3)

and the map (t, u0 ) → Θt,t0 u0 from [t0 , τ ) × D(t, t0 ) ∩ Y to Y is continuous. The solution Y is the process Θ determines the induced solution process Θ Y in Y . The domain of Θt,t 0 open subset D Y (t, t0 ) := Dt,t0 ∩ Y of Y . Rather than work with fractional power spaces, one can assume that F : [0, ∞)×K → X where K is a suitable subset of X. The subset K ⊂ X is locally closed in the Banach space X if for each x ∈ K there exists r > 0 such that {y ∈ K: x −y r} is closed in X. Closed and open subsets K of X are locally closed. Note that the following result gives existence and uniqueness of mild solutions while at the same time giving positive invariance. It is a special case of Theorems VIII.2.1 and VIII.3.1 in Martin [125]. Assumptions on the semigroup et A remain as above. T HEOREM 6.2. Let K be a nonempty locally closed subset of a Banach space X and let F : [0, ∞) × K → X be continuous and satisfy: For each R > 0 there are LR > 0 and γ ∈ (0, 1] such that for x, y ∈ K, x , y R, 0 s, t R F (t, x) − F (s, y) LR |t − s|γ + x − y .

(6.4)

Suppose also that: (a) et A (K) ⊂ K for all t 0, and (b) lim infhց0 h1 dist(x + hF (t, x), K) = 0 for (t, x) ∈ [0, ∞) × K. Then for each (t0 , u0 ) ∈ [0, ∞) × K, there is a unique classical trajectory u(t, t0 , u0 ) of (6.2) defined on a maximal interval [t0 , τ ), and u(t) ∈ K for t0 t < τ . This result is useful for parabolic systems when X = C k (Ω), k = 0, 1 but not when X = The substitution operators are well-behaved in the former cases but require very stringent growth conditions for the latter; see Martin [125]. By virtue of the uniqueness Lp (Ω).

336


assertions of Theorem 6.1 and Theorem 6.2, the solution processes given by the two results agree on K if (6.4) holds. Hypothesis (a) is obviously required for the positive invariance of K in case F = 0. Hypothesis (b), called the subtangential condition, is easily seen to be a necessary condition for the positive invariance of K if A = 0. See Martin [125, Theorem VI.2.1]. Both hypotheses are trivially satisfied if K = X. The following result is a special case of [125, Proposition VIII.4.1]: P ROPOSITION 6.3. Let F : [0, ∞) × X → X be continuous and satisfy (6.4) with K = X and let u(t) = u(t, t0 , x0 ) be the unique classical trajectory defined on a maximal interval [t0 , τ ) guaranteed by Theorem 6.2. If τ < ∞ then limt→τ u(t) = ∞. 6.1.3. Monotone processes Given our interest in establishing monotonicity properties of solution processes induced by parabolic systems in various functions spaces, there are two approaches one may take. One is to establish the properties on spaces of smooth functions such as fractional power spaces X α for α < 1 near unity and then try to extend the monotonicity to larger spaces, e.g., C 0 (Ω), by approximation. An alternative is to establish the monotonicity properties on the larger spaces first and then get corresponding properties on the smaller spaces by restriction. We give both approaches here, beginning with the former. A process Θ is very strongly order preserving (= VSOP) if it is monotone and has the following property: Given t0 0, u > v, and ǫ > 0, there exist s ∈ (t0 , t0 + ǫ] and neighborhoods U, V of u, v respectively such that t s

)⇒ Θt,t0 (U ∩ Dt,t0 ) > Θt,t0 (V ∩ Dt,t0 ).

This implies Θ is SOP and strictly monotone. T HEOREM 6.4. Assume X is an ordered Banach space and Y ֒→ X an ordered Banach space such that Y is dense in X and the order cone Y+ := Y ∩ X+ is dense in X+ . Let Θ be a process in X that induces a monotone process Θ Y in Y . Then: (a) Θ is monotone. (b) Assume R(Θt,t0 ) ⊂ Y for all t > t0 0. Then Θ is strictly monotone if Θ Y is strictly monotone, and Θ is VSOP provided Θ Y is strongly monotone and Θt,t0 : D(t, t0 ) → Y is continuous for t > t0 . P ROOF. (a) Fix u and v > u in X. The closed line segment uv spanned by u and v is compact, hence there exists ρ > t0 with uv ⊂ Dt0 ,ρ . By the density assumptions there exist convergent sequences un → u, vn → v in Dt0 ,ρ such that un , vn ∈ Y and un < vn . As Θ Y is induced from Θ, it follows that un , vn ∈ DtY0 ,ρ . For all t ∈ [t0 , ρ), Y Y Θt,t0 (un ) = Θt,t (un ) Θt,t (vn ) = Θt,t0 (vn ). 0 0

Taking limits as n → ∞ proves Θt,t0 (u) Θt,t0 (v). Thus Θ is monotone.


337

(b) Assume now that Θ Y is strictly monotone. We show that Θ is strictly monotone. Let u(t), v(t) be local trajectories with u(t0 ) < v(t0 ). If r ∈ (t0 , t1 ] is sufficiently near t0 , then u(r), v(r) are distinct points of Y , and u(r) < v(r) by (a). Hence u(t1 ) < v(t1 ) by strict monotonicity of Θ Y . To prove Θ is VSOP, let u(t), v(t) be as above with u(t0 ), v(t0 ) ∈ Dt,t0 . If t0 < s < r < t, strict monotonicity implies u(s) > v(s). These points are in Y , Θ Y is strongly monotone, and Θ agrees with Θ Y in Y . Therefore there are disjoint neighborhoods U1 , V1 ⊂ Y of u(s), v(s) respectively, such that Θr,s (U1 ∩ Dr,s ) ≫ Θr,s (V1 ∩ Dr,s ) and strict monotonicity implies that t >r

)⇒ Θt,r (U1 ∩ Dt,r ) > Θt,r (V1 ∩ Dt,r ).

(6.5)

As Θr,t0 : D(r, t0 ) → Y is continuous, we may define neighborhoods U, V ⊂ X of u(t0 ), v(t0 ) respectively by −1 U = Θr,t (U1 ), 0

−1 V = Θr,t (V1 ). 0

By (6.5) and the cocycle identities, t >r

)⇒ Θt,t0 (U ∩ Dt,t0 ) > Θt,t0 (V ∩ Dt,t0 ).

Let X be an ordered Banach space with positive cone X+ and K a locally closed subset. The mapping F : K → X is said to be quasimonotone (relative to X+ ) if: (QM) For all (t, x), (t, y) ∈ [0, ∞) × K satisfying x y we have: 1 dist y − x + h F (t, y) − F (t, x) , X+ = 0. hց0 h lim

The next result is due to [125, Proposition VIII.6.1 and Lemma 6.3] (see also [129] in case of abstract delay differential equations). T HEOREM 6.5. Assume the hypotheses of Theorem 6.2 hold, F is quasimonotone, and et A is a positive operator for t 0. In addition, suppose one of the following: (i) K is open. (ii) K + X+ ⊂ K. (iii) X is a Banach lattice and K = [u, v] for some u, v ∈ X ∪ {−∞, ∞}, u v. Then x, y ∈ K, x y )⇒ u(t, x) u(t, y) 0 t min{τx , τy } .

By [−∞, v], v ∈ X, is meant the set {x ∈ X: x v}; similarly for other intervals involving ±∞. Of course, −∞ v ∞ for every v ∈ X. Observe that K = [u, ∞] is covered by both (ii) and (iii).

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R EMARK 6.6. If F has the property that for each x, y ∈ K with x y, there exists λ > 0 such that F (t, x) + λx F (t, y) + λy then F is quasimonotone because y − x + h F (t, y) − F (t, x) = (1 − λh)(y − x) + h F (t, y) + λy − F (t, x) − λx ∈ X+

when h < λ−1 .

R EMARK 6.7. It is well-known that et A is a positive operator if and only if (λI − A)−1 is a positive operator for all large positive λ. See, e.g., [11, Theorem II 6.4.1] or [125, Proposition 7.5.3]. Indeed, if K is a closed convex subset of X, then et A K ⊂ K if and only if (λI − A)−1 K ⊂ K for all large positive λ. A Banach space X is a Banach lattice if for each x, y ∈ X, x ∨ y := sup{x, y} exists and the norm is monotone in the sense: |x| |y| )⇒ x y , where |x| denotes the absolute value of x: |x| := (−x) ∨ x (see Vulikh [225]). Banach lattices are easy to work with due to simple formulas such as dist(x, X+ ) = x − x+ = x− , where x+ := x ∨ 0 and x− = −(−x)+ . The requirement that X be a Banach lattice is a rather strong hypothesis which essentially restricts applicability to X = Lp (Ω), C 0 (Ω) or C00 (Ω). However, the latter two will be important for reaction–diffusion systems. 6.2. Semilinear parabolic equations Let Ω ⊂ Rn be the interior of a compact n-dimensional manifold with C 2 boundary ∂Ω. We consider the semilinear system of m coupled equations (1 i m): ∂ui = (Ai ui )(t, x) + fi (t, x, u, ∇u) ∂t (Bi ui )(t, x) = 0 ui (t0 , x) = v0,i (x)

(x ∈ Ω, t > t0 ), (x ∈ ∂Ω, t > t0 ), (x ∈ Ω).

(6.6)

Here the unknown function is u = (u1 , . . . , um ) : Ω → Rm , and ∇u := (∇u1 , . . . , ∇um ) ∈ ∂ui ∂ui ). Each Ai (x) is a , . . . , ∂x (Rn )m lists the spatial gradients ∇ui of the ui , i.e., ∇ui := ( ∂x n 1 second order, elliptic differential operator of the form Ai (x) =

n

l,j =1

n

Clji (x)

∂ ∂ ∂ bji (x) + ∂xl ∂xj ∂xj j =1

(6.7)


339

with uniformly continuous and bounded coefficients. Each n × n matrix C i (x) := [Clji (x)] is assumed positive definite: $ % 0 < inf C i (x)y, y

x ∈ Ω, y ∈ Rn , |y| = 1 ,

where ·, · denotes the Euclidean inner product on Rn . The function

m f := (f1 , . . . , fm ) : R+ × Ω × Rm × Rn → Rm

is continuous, and f (t, x, u, ξ ) is locally Lipschitz in (u, ξ ) ∈ Rm × (Rn )m . Each boundary operator Bi acts on sufficiently smooth functions v : [t0 , τ ) × Ω → R in one of the following ways, where x ∈ ∂Ω: Dirichlet:

(Bi v)(t, x) = v(t, x);

Robin:

(Bi v)(t, x) = γi v(t, x) +

Neumann: (Bi v)(t, x) =

∂v (t, x), ∂ξi

∂v (t, x); ∂ξi

where γi : Ω → [0, ∞) is continuously differentiable, and ξi : Ω → Rn is a continuously differentiable vector field transverse to ∂Ω and pointing outward from Ω. Note that Neumann is a special case of Robin. We rewrite (6.6) as an initial-boundary value problem for an unknown vector-valued function u := (u1 , . . . , um ) : [t0 , τ ) × Ω → Rm , ∂u = (Au)(t, x) + f (t, x, u, ∇u) ∂t (Bu)(t, x) = 0 u(t0 , x) = u0 (x)

(x ∈ Ω, t > t0 ), (x ∈ ∂Ω, t > t0 ), (x ∈ Ω),

(6.8)

where the operators A := A1 × · · · × Am and B := B1 × · · · × Bm act componentwise on u = (u1 , . . . , um ). By a solution process for Eq. (6.8) we mean a process in some function space on Ω, whose trajectories are solutions to (6.8). Of special interest are autonomous systems, for which f = f (x, u, ∇u); and the reaction–diffusion systems, characterized by f = f (t, x, u). Assume n < p < ∞. To Eq. (6.8) we associate an abstract differential Eq. (6.1) in Lp (Ω, Rm ). The pair of operators (Ai , Bi ) has a sectorial realization Ai in Lp (Ω) with domain D(Ai ) ֒→ Lp (Ω) (Lunardi [124, 3.1.3]). The operator A := A1 × · · · × Am is sectorial on X := Lp (Ω, Rm ) = [Lp (Ω)]m . For α ∈ [0, 1) set X α := X α (A). We choose α so that f defines a continuous substitution operator F : R+ × X α → X,

F (t, u)(x) := f t, x, u(x), ∇u(x) .

340


It suffices to take α 1>α>

n 1 1+ , 2 p

(6.9)

for then X α ֒→ C 1 (Ω, Rm ) by the Sobolev embedding theorems. The data (A, F ) thus determine an abstract differential equation u′ = Au + F (t, u) in X, whose trajectories u(t) correspond to solutions u(t, x) := u(t)(x) of (6.6). The assumptions on f make F (t, u) locally Lipschitz in u ∈ X α . By Theorem 6.1 and the Sobolev embedding theorem we have: P ROPOSITION 6.8. Equation (6.8) defines a solution process Θ on X := Lp (Ω, Rm ) which induces a solution process in X β for every β ∈ [0, 1) with β α. We quote a useful condition for globality of a solution: P ROPOSITION 6.9. Assume there are constants C > 0 and 0 < ǫ 1 such that f (t, x, v, ξ ) C 1 + v + ξ 2−ǫ

for all (t, x, v, ξ ) ∈ R+ × Ω × S × Rn . (6.10)

If u : [t0 , τ ) → Lp (Ω, Rm ) is a trajectory such that lim supu(t)Lp (Ω,Rm ) < ∞

(6.11)

t→τ −

then τ = ∞.

P ROOF. Follows from Amann [9, Theorem 5.3(i)], taking the constants of that result to be m = k = p0 = γ0 = 1, κ = s0 = 0, γ1 = 2 − ǫ. Solutions u : [t0 , τ ) × Ω → Rm to (6.8) enjoy considerable smoothness. For example, if the data ∂Ωi , fi , Ai , Bi are smooth of class C 2+2ǫ , 0 < 2ǫ < 1, then u ∈ C 1+ǫ,2+2ǫ ([t1 , t2 ] × Ω, Rm ) for all t0 < t1 < t2 < τ (Lunardi [124, 7.3.3(iii)]). While useful for many purposes, solution processes in the spaces X α suffer from the drawback that X α and its norm are defined implicitly, leaving unclear the domains of solutions and the meaning of convergence, stability, density and similar topological terms. In addition, the topology of X α might be unsuitable for a given application. To overcome these difficulties we could appeal to results of Colombo and Vespri [29], Lunardi [124] and Mora [147], establishing induced processes in Banach spaces of continuous, smooth or Lp functions; or we can apply Theorem 6.2. We now define these spaces. For r ∈ N let C r (Ω) denotes the usual Banach space of C r functions on Ω. Set C0r Ω := v ∈ C r Ω : v|∂Ω = 0 .


341

With γ , ξ as in a Robin boundary operator and r 1, define Cγr ,ξ

∂v r (x) = 0 (x ∈ ∂Ω) . Ω := v ∈ C Ω : γ (x)v(x) + ∂ξ

It is not hard to show that: • C 0 (Ω), C 1 (Ω) and Cγ1,ξ (Ω) are strongly ordered, with u ≫ 0 if and only if u(x) > 0 for all x ∈ Ω; • C01 (Ω) is strongly ordered, with u ≫ 0 if and only if u(x) > 0 for all x ∈ Ω and ∂u/∂ν > 0 where ν : ∂Ω → Rn is the unit vector field inwardly normal to ∂Ω; • C00 (Ω) is not strongly ordered. Both C00 (Ω) and C 0 (Ω) are Banach lattices. In terms of the boundary operators Bi , for k = 0, 1 we define Banach spaces   Ck Ω if Bi is Dirichlet,  0k k if Bi is Robin and k = 1, CBi Ω := Cγ ,ξ Ω   C0 Ω if Bi is Robin and k = 0.

Note that CB1 i (Ω) is strongly ordered, while CB0 i (Ω) is strongly ordered if and only if Bi is Robin; CB0 i (Ω) is a Banach lattice. The ordered Banach space CBk Ω, Rm := 'i CBk i Ω ,

with the product order cone, is strongly ordered if k = 1, or k = 0 and no Bi is Dirichlet. The order cone Lp (Ω, Rm )+ is the subset of Lp (Ω, Rm ) comprising equivalence classes p m represented by functions Ω → Rm + . Note that L (Ω, R ) is normally ordered but not strongly ordered. It is known that the pair of operators (Ai , Bi ) has a sectorial realization Ai on C k (Bi ) and therefore the product operator A is sectorial on CBk (Ω, Rm ). See Corollary 3.1.24, Theorems 3.1.25, 3.1.26 in [124]. L EMMA 6.10. For X = Lp (Ω, Rm ) or CBk (Ω, Rm ), the analytic semigroup et A is a positive operator for t 0 with respect to the cone of componentwise nonnegative functions in X. P ROOF. As noted in Remark 6.7, it suffices to show that (λI − A)−1 is positive for large λ > 0, or equivalently, that for each i and fi 0, the solution gi ∈ D(Ai ) of fi = λgi − Ai gi satisfies gi 0. The existence of gi is not the issue but rather it’s positivity. Thus it boils down to λgi − Ai gi 0 )⇒ gi 0. But these follow from standard maximum principle arguments. See Lemma 3.1.4 in [155]. With X = Lp (Ω, Rm ) and A and α as above, we have a chain of continuous inclusions of ordered Banach spaces

1 Ω, Rm ֒→ CB0 Ω, Rm ֒→ Lp Ω, Rm , D(A) ֒→ X α ֒→ CB

342


with a solution process in Lp (Ω, Rm ) and an induced solution process in X α . P ROPOSITION 6.11. Let Θ be the solution process in Lp (Ω, Rm ) for Eq. (6.1) with n < p < ∞. (a) For all t > t0 , Θt,t0 maps Dt,t0 continuously into CB1 (Ω, Rm ). (b) Θ induces a solution process Θ 1 in CB1 (Ω, Rm ). (c) Θ induces a solution process Θ 0 in CB0 (Ω, Rm ) provided f = f (t, x, u). P ROOF. By uniqueness of solutions it suffices to establish induced solution processes in CB1 (Ω, Rm ) ֒→ Lp (Ω, Rm ), and in CB0 (Ω, Rm ) ֒→ Lp (Ω, Rm ) when f = f (t, x, u). This is done in Lunardi [124, Proposition 7.3.3] for m = 1, and the general case is similar. Part (c) follows from Theorem 6.2. Henceforth Θ k , k ∈ {0, 1}, denotes the process Θ 0 or Θ 1 as in Proposition 6.11. 6.2.1. Dynamics in spaces XΓ

For any set Γ ⊂ Rm and k = 0, 1 define

XΓk := u ∈ CBk Ω, Rm : u Ω ⊂ Γ , XΓ := u ∈ Lp Ω, Rm : u(Ω) ⊂ Γ .

(6.12)

A rectangle in Rm is a set of the form J = J1 × · · · × Jm where each Ji ⊂ R is a nondegenerate closed interval. Rm , Rm + and closed order intervals [a, b], a b are rectangles. m P ROPOSITION 6.12. Let J := 'm i=1 Ji be a rectangle in R such that either 0 ∈ Ji or Bi is Neumann, and the following hold for all x ∈ Ω, u ∈ ∂J :

fi (t, x, u, 0) 0 if ui = inf Ji ,

fi (t, x, u, 0) 0

if ui = sup Ji .

(6.13)

Then: (i) In the reaction–diffusion case, XJ is positively invariant for Θ and XJk is positively invariant for Θ k (k = 0, 1). (ii) Suppose k = m = 1 and J ⊂ R is an interval. Then XJ is positively invariant for Θ and XJ1 is positively invariant for Θ 1 . P ROOF. For the reaction–diffusion case we sketch a proof that XJ0 is Θ 0 -positively invariant using Theorem 6.2. The proof that XJ is Θ-positively invariant follows from this 0 (u ) where u ∈ X 0 approximates u ∈ X in Lp since Θt,t0 (u) is the Lp limit limk Θt,t k k J J 0 0 0 and the facts: Θ = Θ on XJ , a dense subset of the closed subset XJ . In order to verify the subtangential condition for XJ0 , it suffices to verify the subtangential condition for J : lim inf hց0

1 dist u + hf (t, x, u), J = 0 h

(6.14)


343

for each (t, x, u) ∈ [0, ∞) × Ω × J by Martin [125, Proposition IX.1.1]. But (6.14) is a necessary condition for J to be positively invariant for the ODE v ′ = f (t, x, v), where x is a parameter. See, e.g., [125, Theorem VI.2.1]. It is well-known and easy to prove that condition (6.13) implies the positive invariance of J for the ODE (see, e.g., Proposition 3.3, Smith and Waltman [203, Proposition B.7], or Walter [227, Chapter II, Section 12, Theorem II]). It follows that (6.14) holds. Therefore the subtangential condition for XJ0 holds. Finally, we must verify that et A XJ0 ⊂ XJ0 or, equivalently, that et Ai CB0 i (Ω, Ji ) ⊂ CB0 i (Ω, Ji ). This follows from Remark 6.7 and standard maximum principle arguments. It also follows from standard comparison principles for parabolic equations. See, e.g., Pao [155, Lemma 2.1] or Smith [194, Corollary 2.4]. The case k = m = 1 is a special case of [227, Chapter IV, Section 25, Theorem II, Section 31, Corollaries IV and V]. Consider the case that (6.6) is autonomous: ∂ui = Ai ui + fi (x, u, ∇u) ∂t Bi ui = 0

(x ∈ Ω, t > t0 ),

(6.15)

(x ∈ ∂Ω, t > t0 ),

i = 1, . . . , m. The solution processes Θ, Θ 1 , Θ 0 reduce to local semiflows. We introduce a mild growth condition, trivially satisfied in the reaction–diffusion case: For each s > 0 there exists C(s) > 0 such that |v| s )⇒ f (x, v, ξ ) C(s) 1 + |ξ |2−ǫ .

(6.16)

The following result gives sufficient conditions for solution processes in XΓ to be global, and to admit compact global attractors: P ROPOSITION 6.13. Assume system (6.15) satisfies (6.16). Let Γ ⊂ Rm be a nonempty compact set such that XΓ is positively invariant for (6.15). Then: (a) There are solution semiflows Φ, Φ 1 in XΓ , XΓ1 respectively. Φ 1 is compact. (b) Assume (6.15) is reaction–diffusion. Then there is also a solution semiflow Φ 0 in XΓ0 . The semiflows Φ, Φ 0 , Φ 1 are compact and order compact. There is a compact set K ⊂ XΓ1 which is the global attractor for all three semiflows. P ROOF. (a) Let Γ lie in the open ball of radius R > 0 about the origin in Rm and let h : Rm → Rm be any smooth bounded function that agrees with the identity on the open ball of radius R. Define g by g(x, v, ξ ) = f (x, h(v), ξ ). Every trajectory in XΓ of (6.15) is also a trajectory of the analogous system in which f is replaced by g (compare Poláˇcik [163, pp. 842–843]). Nonlinearity g satisfies (6.16) with C(s) constant so (6.10) holds. As lim supu(t)C 0 (Ω,Rm ) R, t→τ −

344


which implies (6.11), all trajectories are global by Proposition 6.9. Thus, the restrictions of Ψ, Ψ 1 in X and CB1 (Ω, Rm ) respectively to XΓ and XΓ1 define semiflows Φ and Φ 1 . As Ψ 1 is compact by Hale [58], Theorem 4.2.2, Φ 1 is compact because XΓ1 is closed in CB1 (Ω, Rm ). (b) In the reaction–diffusion case a similar argument establishes a compact solution semiflow Φ 0 in XΓ0 ; and Φ 0 is order compact because order intervals in XΓ0 are bounded. To prove Φ 0 order compact, let N be an order interval in XΓ . For every t = 2s > 0, Φs maps N continuously into an order interval N ′ of XΓ0 . Precompactness in XΓ of Φt N follows from the precompactness in XΓ0 of Φs0 N ′ , already established, and the continuous inclusion Φt N = Φs0 ◦ Φs N ⊂ Φs0 N ′ . To prove order compactness of Φ 1 , let N1 ⊂ XΓ1 be an order interval. N1 is contained in an order interval N0 of XΓ0 . Let Ck denote closure in XΓk . For all t > 0 we have C1 (Φt1 N1 ) = C1 (Φt0 N1 ) ⊂ C1 C0 (Φt0 N0 ), and the latter set is compact because Φ 0 is order compact. This proves Φt1 N1 is precompact in XΓ1 . XΓ0 is closed and bounded in X 0 , hence Φt0 XΓ0 is precompact in XΓ0 for all t > 0 by (a). 3 Therefore K := t>0 Φt0 XΓ0 is a compact global attractor for Φ 0 . Similarly, K (with the same topology) is a compact global attractor for Φ. We rely on the identity Φt1 = Φt0 |XΓ1 and continuity of Φt0 : XΓ0 → XΓ1 for all t > 0. As K is invariant under Φ 0 , it follows that K is a compact subset of XΓ1 . To prove K a global attractor for Φ 1 , it suffices to prove: For arbitrary sequences {x(i)} in XΓ1 , and t (i) → ∞ in R+ with t (i) > ǫ > 0, there is a sequence ik → ∞ in N such that {Φt1(ik ) x(ik )} converges in XΓ1 to a point of K. Choose {ik } so that Φt0(ik )−ǫ (ik ) converges XΓ0 as k → ∞ to p ∈ K; this is possible because K is a compact global attractor for Φ 0 . Then Φt1(ik ) x(ik ) = Φǫ0 ◦ Φt0(ik )−ǫ x(ik ), which converges in XΓ1 as k → ∞ to Φǫ0 p ∈ K. E XAMPLE . Let the ui denote the concentrations or densities of entities such as chemicals or species. Such quantities are inherently positive, so taking the state space to be m k Lp (Ω, Rm + ) or CB (Ω, R+ ) is appropriate. We make the plausible assumption that sufficiently high density levels must decrease. Modeling this situation by (a) and (b) below, we get the following result. P ROPOSITION 6.14. In Eq. (6.15) assume f = f (x, u) and let the following hold for i = 1, . . . , m: (a) fi (x, u) 0 if ui = 0; (b) there exists κ > 0 such that fi (x, u) < 0 if ui κ. k m Then for k = 0, 1 solution processes in the order cones Lp (Ω, Rm + ), CB (Ω, R+ ) are dek k fined by semiflows Φ, Φ respectively; and there is a compact set K ⊂ X[0,κ]m that is the global attractor for Φ, Φ 0 and Φ 1 . m k P ROOF. Proposition 6.12 and (a) proves Lp (Ω, Rm + ) and CB (Ω, R+ ) are positively invariant under the solution process. Consider the compact rectangles J (c) := [0, cκ]m ⊂ Rm , c 1. Assumption (b) and Proposition 6.12 entail positive invariance of XJ (c) . Proposition 6.13 shows that there are


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solution semiflows in XJ (c) and XJk (c) having a compact global attractor Kc ⊂ XJ1 (c) in common. As the J (c) are nested and exhaust Rm + , these semiflows come from solution semiflows Φ, Φ k as required. Moreover, all the attractors Kc coincide with the compact set K := K1 ⊂ XJ1 (1) . It is easy to see that K is the required global attractor. Results on global solutions and positively invariant sets can be found in many places. See for example Amann [9,10], Cholewa and Dlotko [25], Cosner [33], Lunardi [124], Poláˇcik [163], Smith [194], Smoller [205]. 6.2.2. Monotone solution processes for parabolic equations We restrict attention here to monotonicity properties with respect to the standard point-wise and component-wise ordering of functions Ω → Rm : f g if and only if fi (x) gi (x) for all x and all i. The natural ordering on Lp (Ω, Rm ) is defined on equivalence classes by the condition on representatives that fi (x) gi (x) almost everywhere. Orderings induced by orthants in Rn other than the positive orthant can be handled easily by change of variables. See Mincheva [144] and [145] for results in the case of polyhedral cones in Rn . Consider the case m = 1 in Eq. (6.8). T HEOREM 6.15. In Eq. (6.8), assume m = 1 and f is C 1 . Then: (i) Θ is VSOP on Lp (Ω, Rm ). (ii) Θ 1 is strongly monotone in CB1 (Ω). (iii) If f = f (t, x, u) the induced process Θ 0 on CB0 (Ω) is VSOP, and strongly monotone if all boundary operators are Robin. P ROOF. Let u, v : [t0 , t1 ] × Ω → R be solutions with v(t0 , x) − u(t0 , x) 0 for all x and > 0 for some x. Then w := v − u is the solution to the problem n

∂w ∂w = Aw + bj + cw ∂t ∂xj

Bw(t, x) = 0 w(t0 , x) 0,

j =1

w(t0 , x) ≡ 0

(x ∈ Ω, t > t0 ),

(6.17)

(x ∈ ∂Ω, t > t0 ), (x ∈ Ω)

where bj = bj (t, x) and cj = cj (t, x) are obtained as follows. Evaluate u, v and their spatial gradients at (t, x), and for s ∈ [0, 1] set Z(s) = (1 − s)(t, x, u, ∇u) + s(t, x, v, ∇v), 1 b(t, x) = b1 (t, x), . . . , bn (t, x) = D4 f Z(s) ds, 0

c(t, x) =

0

1

D3 f Z(s) ds

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where D4 f and D3 f denote respectively the derivatives of f (t, x, y, ξ ) with respect to ξ ∈ Rn and y ∈ R. By Taylor’s theorem f (t, x, v, ∇v) − f (t, x, u, ∇u) = b(t, x)(∇u − ∇v) + c(t, x)(u − v), whence (6.17) follows. The parabolic maximum principle and boundary point lemma ([194, Theorems 7.2.1, 7.2.2]) imply that the function w(t1 , ·), considered as an element of CB1 (Ω), is ≫ 0. This proves (ii), and the first assertion of (iii) follows from Theorem 6.4(b). The proof of strong monotonicity for Robin boundary conditions is similar to the arguments given above. Part (i) follows from strong monotonicity of Θ 1 , Theorem 6.4 and continuity of Θt,t0 : Lp (Ω, Rm ) → X α ֒→ CB1 (Ω, Rm ). For m 2 we impose further conditions on system (6.6) in order to have a monotone solution process: it must be of reaction–diffusion type, and the vector fields f (t, x, ·) on Rm must be cooperative. In other words, f (t, x, u) is C 1 in u and ∂fi /∂uj 0 for all i = j . (The latter condition holds vacuously if m = 1). When this holds then the system is called cooperative. If in addition, there exists x¯ ∈ Ω such that the m × m Jacobian ¯ u)] is irreducible for all (t, u), we call the system cooperative and matrix [∂fi /∂uj (t, x, irreducible T HEOREM 6.16. If system (6.15) is cooperative, then Θ, Θ k , k = 0, 1 are monotone. If the system is also irreducible, then: (i) Θ is VSOP on Lp (Ω, Rm ). (ii) Θ 1 is strongly monotone in CB1 (Ω, Rm ). (iii) Θ 0 is VSOP in CB0 (Ω, Rm ) and is strongly monotone when all boundary operators are Robin. P ROOF. Monotonicity in CB0 (Ω, Rm ) follows directly from Theorem 6.5 and Remark 6.6. Indeed, let u v in CB0 (Ω, Rm ) and t be fixed. Then F (t, v) − F (t, u) + λ(v − u) (x) 1 ∂f t, x, su(x) + (1 − s)v(x) + λI ds(v − u)(x) 0 = ∂u 0 for some λ > 0 and all x ∈ Ω by cooperativity of f and compactness of Ω. This implies that (QM) holds. The positivity of et A follows from Lemma 6.10. Monotonicity of Θ in Lp (Ω, Rm ) follows from monotonicity of Θ 0 and Theorem 6.4. The proof of VSOP and strong monotonicity for Robin boundary conditions in CB0 (Ω, Rm ) is like that of Theorem 6.15(i), exploiting the maximum principle for weakly coupled parabolic systems (Protter and Weinberger [166, Chapter 3, Theorems 13, 14, 15 and pp. 192, Remark (i)]). See Smith [194, Section 7.4] for a similar proof. Monotonicity of Θ 1 follows from monotonicity of Θ 0 . Strong monotonicity of Θ 1 , in the case of Dirichlet boundary conditions, requires exploiting the maximum principle as in


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the previous case (the same references apply). VSOP of Θ follows from strong monotonicity of Θ 1 , Theorem 6.4 and continuity of the composition Θt,t0 : Lp (Ω, Rm ) → X α → CB1 (Ω, Rm ). 6.3. Parabolic systems with monotone dynamics We now treat autonomous systems (6.15) having monotone dynamics. Our goal is Theorem 6.17, a sample of the convergence and stability results derivable from the general theory. In addition to the assumptions for (6.6), we require the following conditions to hold for the solution process Θ in X := Lp (Ω, Rm ), with p satisfying (6.9) and XΓk defined in (6.12): (SP) If m 2 in system (6.15) then f = f (x, u) and the system is cooperative and irreducible. Γ ⊂ Rm is a nonempty set, either an open set or the closure of an open set. The solution process induces semiflows Φ, Φ 1 in XΓ , XΓ1 respectively, and Φ 0 in XΓ0 for the reaction–diffusion case. These semiflows are assumed to have compact orbit closures. Simple conditions implying (SP) can be derived from Propositions 6.13. The following statements follow from (SP), assertions about Φ 0 having the implied hypothesis f = f (x, u): • XΓ1 is dense in XΓ0 and in XΓ . • Φ and Φ 0 agree on XΓ0 , and Φ, Φ 0 and Φ 1 agree on XΓ1 . • Φt (respectively, Φt0 ) maps XΓ (respectively, XΓ0 ) continuously into XΓ1 for t > 0 (Proposition 6.11). • Φ, Φ 1 and Φ 0 have the same omega limit sets, compact attractors and equilibria. • If Γ is open or order convex and f (x, u, ξ ) is C 1 in (u, ξ ), the Improved Limit Set Dichotomy (ILSD) holds for Φ 1 by Theorem 2.16, and for Φ and Φ 0 by Proposition 2.21. • If Γ is compact then Φ 1 is compact. In the reaction–diffusion case with Γ compact, Φ, Φ 1 and Φ 0 are compact and order compact, and a common compact global attractor (Propositions 6.13). • Φ 1 is strongly monotone; Φ 0 is VSOP, and strongly monotone if all boundary operators are Robin; Φ is VSOP (Theorem 6.16). The sets of quasiconvergent, convergent and stable points for any semiflow Ψ are denoted respectively by Q(Ψ ), C(Ψ ), S(Ψ ). References to intrinsic or extrinsic topology of these sets (e.g., closure, density) for Φ, Φ 1 or Φ 0 are to be interpreted in terms of the topology of the corresponding domain XΓ , XΓ1 or XΓ0 . T HEOREM 6.17. If system (6.15) satisfies hypothesis (SP), then: (i) The sets Q(Φ), Q(Φ 0 ) and Q(Φ 1 ) are residual. (ii) Assume Γ is open or order convex and f (x, u, ξ ) is C 1 in (u, ξ ). Then the sets C(Φ) ∩ S(Φ), C(Φ 0 ) ∩ S(Φ 0 ) and C(Φ 1 ) have dense interiors.

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(iii) Assume f = f (x, u) and Γ is compact. Then the semiflows Φ, Φ 0 , Φ 1 are compact and order compact, and they have a compact global attractor in common. (iv) Assume Γ is open or order convex and EΓ is compact. Then some p ∈ EΓ is stable for Φ. Every such p is also stable for Φ 1 , and for Φ 0 in the reaction–diffusion case. When EΓ is finite, the same holds for asymptotically stable equilibria. P ROOF. (i) follows from Theorem 1.21. (ii) for Φ and Φ 0 follows from Theorem 2.25(b). For Φ 1 , (ii) follows from Theorem 2.26(a). (iii) is a special case of Proposition 6.13(b). In (iv), to find a p ∈ EΓ having the asserted stability properties for Φ, it suffices to verify the hypotheses of Theorem 1.30: (a) follows from (i), while (b) and (c) holds by the assumptions on Γ and compactness of E. Similarly for Φ 0 in the reaction–diffusion case. To prove the stability properties for p under Φ 1 , it suffices by Theorem 1.31 to show that p has a neighborhood in XΓ1 that is attracted to a compact set. By (i) and the assumptions on Γ , there are sequences {uk }, {vk } in Q(Φ 1 ) converging to p in XΓ , such that uk uk+1 p vk+1 vk and p = inf XΓ

)⇒

uk < uk+1 < p,

p = sup XΓ

)⇒ p < vk+1 < vk .

Replacing uk , vk by their images under Φǫk for sufficiently small ǫk > 0, we see from strong monotonicity of Φ 1 that we can assume: p = inf XΓ

)⇒

uk ≪ uk+1 ≪ p,

p = sup XΓ

)⇒ p ≪ vk+1 ≪ vk .

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CHAPTER 5

Planar Periodic Systems of Population Dynamics Julián López-Gómez† Departamento de Matemática Aplicada, Universidad Complutense de Madrid, 28040-Madrid, Spain E-mail: [email protected]

Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Basic preliminaries. The single logistic equation . . . . . . . . . . . . . . d + V : C1 → C 2.1. The differential operator dt T . . . . . . . . . . . . . T 2.2. The single logistic equation . . . . . . . . . . . . . . . . . . . . . . . 2.3. Point-wise behaviour of the map ρ → θ[ρα,β] . . . . . . . . . . . . 2.4. Attractiveness of θ[ρα,β] . . . . . . . . . . . . . . . . . . . . . . . . 3. Linearized stability of the semi-trivial solutions . . . . . . . . . . . . . . 4. The curves of change of stability of the semi-trivial positive solutions . . 4.1. The species u and v compete (b > 0 and c > 0) . . . . . . . . . . . . 4.2. The species v preys on u (b > 0 and c < 0) . . . . . . . . . . . . . . 4.3. The species u and v cooperate (b < 0 and c < 0) . . . . . . . . . . . 4.4. The general case when b and c change of sign . . . . . . . . . . . . 5. The existence of coexistence states . . . . . . . . . . . . . . . . . . . . . 5.1. Abstract unilateral bifurcation from semi-trivial states . . . . . . . . 5.2. The existence of coexistence states in the general case . . . . . . . . µ 5.3. Local structure of Cλµ and Cλ at (µ0 , θ[λℓ,a] , 0) and (λ0 , 0, θ[µm,d] ) 6. The symbiotic model (b < 0 and c < 0) . . . . . . . . . . . . . . . . . . . 6.1. Periodic systems of cooperative type . . . . . . . . . . . . . . . . . 6.2. Structure of the set of coexistence states . . . . . . . . . . . . . . . . µ 6.3. Stability of the coexistence states along Cλµ and Cλ . . . . . . . . . 6.4. Low and strong symbiosis effects . . . . . . . . . . . . . . . . . . . 7. The competing species model (b > 0 and c > 0) . . . . . . . . . . . . . . 7.1. Periodic systems of quasi-cooperative type . . . . . . . . . . . . . . µ 7.2. Structure of the components Cλµ and Cλ . . . . . . . . . . . . . . . . µ 7.3. Stability of the coexistence states along Cλµ and Cλ . . . . . . . . . 7.4. Some bifurcation diagrams . . . . . . . . . . . . . . . . . . . . . . . 7.5. Dynamics of (1.1) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8. The species v preys on u (b > 0 and c < 0) . . . . . . . . . . . . . . . . . 8.1. Characterizing the existence of coexistence states . . . . . . . . . .

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† Supported by the Ministry of Science and Technology of Spain under grant REN2003-00707.


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8.2. Dynamics of (1.1) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 458 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 459

Abstract This chapter analyzes the dynamics of the positive solutions of a general class of planar periodic systems including those of Lotka–Volterra type and a more general class of models simulating symbiotic interactions within global competitive environments. It seems this is the first occasion where this problematic has been addressed within the context of periodic planar systems. Most of our mathematical analysis is focused towards the study of the existence of coexistence states and the problem of ascertaining the structure, multiplicity and stability of these coexistence states in purely symbiotic, and competitive, environments.

Keywords: Lotka–Volterra systems, symbiosis in competitive environments, coexistence states. MSC: 34A34, 34C12, 92B05.

Planar periodic systems of population dynamics

361

1. Introduction Throughout this chapter, for any T > 0 we denote by CT the Banach space of real T -periodic continuous functions endowed with the norm

u CT := maxu(t) = max u(t). t∈R

t∈[0,T ]

Similarly, CT1 stands for the Banach space of real T -periodic functions of class C 1 endowed with the norm

u C 1 := u CT + u′ C , T

T

where ′ =

Note that

d dt .

The Banach space CT is ordered by its cone of non-negative functions

P := u ∈ CT : u(t) 0, t ∈ R . Int P = u ∈ CT : u(t) > 0, t ∈ R .

Given u, v ∈ CT , we shall write u v if u − v ∈ P , u > v if u − v ∈ P \ {0}, and u ≫ v if u − v ∈ Int P . The main goal of this chapter is analyzing the dynamics of  ′ 2   u (t) = λ ℓ(t)u(t) − a(t)u (t) − b(t)u(t)v(t), (1.1) v ′ (t) = µ m(t)v(t) − d(t)v 2 (t) − c(t)u(t)v(t),   u(0) = x > 0, v(0) = y > 0, and, in particular, the existence, attractiveness and multiplicity of the component-wise nonnegative T -periodic solutions of u′ (t) = λℓ(t)u(t) − a(t)u2 (t) − b(t)u(t)v(t), (1.2) v ′ (t) = µm(t)v(t) − d(t)v 2 (t) − c(t)u(t)v(t),

where {ℓ, m, a, b, c, d} ⊂ CT satisfy ℓ > 0,

m > 0,

a > 0,

d > 0,

(1.3)

and (λ, µ) ∈ R2 are regarded as two real parameters. System (1.2) exhibits three different types of non-negative T -periodic solution pairs. Namely, the trivial state (0, 0), the semitrivial positive states (u, 0) and (0, v) with u ≫ 0 and v ≫ 0, and the coexistence states, which are the solution pairs (u, v) ∈ CT1 × CT1 with u ≫ 0 and v ≫ 0. The interest of analyzing these states coming from the fact that in many circumstances they govern the dynamics of (1.1).

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It should be noted that we are not imposing any sign restriction on the coupling coefficient functions b(t) and c(t). Thus, (1.2) is far from falling within the classical family of Lotka–Volterra periodic systems, since b and c might not have a constant sign. Actually, if given h ∈ CT we denote h+ := max{h, 0},

h− := h+ − h,

I+h := Int supp h+ ,

I−h := Int supp h− ,

and I0h := Int h−1 (0) = R \ I¯+h ∪ I¯−h ,

then, the species u and v interact according to the following patterns: • u and v compete if t ∈ I+b ∩ I+c —periods of time where b(t) > 0 and c(t) > 0. • u and v cooperate if t ∈ I−b ∩ I−c —periods of time where b(t) < 0 and c(t) < 0. • u preys on v if t ∈ I−b ∩ I+c , and v preys on u if t ∈ I+b ∩ I−c —periods of time where b(t)c(t) < 0. • u is free from the action of v if t ∈ I0b , and v is free from the action of u if t ∈ I0c — periods of time where b(t)c(t) = 0. Consequently, within our general setting (1.1) allows all different types of interactions between the species u and v as time passes by. T T Due to (1.3), we have that 0 a > 0 and 0 d > 0, and, hence, the change of variable T u := T U, 0 a

T v := T V , 0 d

* :=

λ T

T

ℓ, 0

M :=

µ T

T

m,

0

transforms (1.2) into  a(t) b(t) ℓ(t)    U ′ (t) = * 1 T U (t) − 1 T U 2 (t) − 1 T U (t)V (t),   T 0 ℓ T 0 a T 0 d

 d(t) c(t) m(t)  2 ′    V (t) = M 1 T V (t) − 1 T V (t) − 1 T U (t)V (t). T 0 m T 0 d T 0 a

Consequently, without lost of generality, we will throughout assume that the following conditions are satisfied: 1 T 1 T 1 T 1 T ℓ= m= a= d = 1. (1.4) T 0 T 0 T 0 T 0 Therefore, h=1

if h ∈ {ℓ, m, a, d} is assumed to be constant.

(1.5)

Throughout this chapter, given any function h ∈ CT we shall denote 1 hˆ := T

T

h(t) dt, 0

hM := max h, R

hL := min h. R

(1.6)


363

Using these notations, conditions (1.3) and (1.4) can be summarized as follows: {ℓ, m, a, d} ⊂ P \ {0},

ℓˆ = m ˆ = aˆ = dˆ = 1.

(1.7)

This work is distributed as follows. In Section 2 we provide some basic preliminaries needed for the subsequent mathematical analysis. Basically, it collects some well known results for the single logistic equation. Section 3 ascertains the linearized stability character of the semi-trivial positive solutions of (1.2). Section 4 analyzes the minimal complexity of the components of the (λ, µ)-plane determined by the curves of neutral stability of the semi-trivial states. Several different situation cases will be differentiated, according to the nature of the interactions between the species u and v. The mathematical analysis carried out in Section 4 is reminiscent from J. Eilbeck and J. López-Gómez [12], where attention was exclusively focused into the competing species model. In Section 5 we give an abstract unilateral global bifurcation result for systems. The main theorem of Section 5 is new in its full generality, and it admits a number of applications to the search of coexistence states in wide classes of nonlinear elliptic boundary value problems and planar periodic systems. Here, we will apply it to get all available existence results concerning the existence of coexistence states of (1.2). We point out that the abstract result of Section 5 does not follow as a direct application of the unilateral theory developed by P.H. Rabinowitz [31], but from the updated unilateral theorem of [19]. Section 6 considers the symbiotic prototype model (b < 0 and c < 0) and uses the theory of monotone periodic systems to show that the set of coexistence states linking the surfaces of the semi-trivial states along their respective curves of neutral stability is a real analytic surface, and that the stability character of the coexistence states changes as one crosses any turning point along that surface, while it remains unchanged when an hysteresis point is passed by. The theory developed here goes back to [17], within the context of quasi-cooperative systems, though here we are considerably tidying up the mathematical analysis of [17] and adding all necessary technical details that were omitted there in. Some of our abstract results for linear periodic systems provide with substantial improvements of some of the results of M.A. Krasnosel’skii [16]. Most precisely, the characterization of the attractive character of the system in terms of the existence of a strict positive supersolution seems to be a completely new result. This theorem is reminiscent of the characterization of the strong maximum principle for second order linear elliptic operators found by J. López-Gómez and M. Molina-Meyer [21,20]. Section 7 adapts the mathematical analysis of Section 6 to the competing species model (b > 0 and c > 0), which possesses a quasi-cooperative structure. Finally, in Section 8 we briefly collect some of the main results available for predator prey models (b > 0 and c < 0, or b < 0 and c > 0). In a forthcoming chapter, we will adapt the theory developed by J. López-Gómez and M. Molina-Meyer [22,23], in order to discuss the effects of strategic symbiosis in competitive environments in order to show that strategic symbiosis allows the species to avoid extinction, while, simultaneously—and quite strikingly—the productivity of the ecosystem grows. For historical remarks and a precise account of some of the most important works available about these models, the reader is sent to the expository chapter of J. Mawhin [27,

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28], which bring an excellent complement to the mathematical analysis carried out in this chapter. Throughout this chapter, given two real Banach spaces, X and Y , we denote by L(X; Y ) the space of linear continuous operators between X and Y , and given T ∈ L(X; Y ), N[T ], R[T ], and spr T will stand for the null space (kernel), the image (rank), and the spectral radius of T , respectively. The identity in X will be denoted by IX , and, given R > 0 and x ∈ X, BR (x) will stand for the ball of radius R centered at x. 2. Basic preliminaries. The single logistic equation In this section we focus our attention into the single logistic equation w ′ (t) = ρα(t)w(t) − β(t)w 2 (t),

(2.1)

where α, β ∈ CT satisfy αˆ > 0,

β > 0,

(2.2)

and ρ ∈ R is regarded as a real parameter. This equation provides us with the semi-trivial states—positive—of (1.2) when (α, β) ∈ {(ℓ, a), (m, d)}. 2.1. The differential operator

d dt

+ V : CT1 → CT

We begin studying some useful properties of the differential operator d + V : CT1 −→ CT , dt

w → w ′ + V w,

(2.3)

where V ∈ CT . The following result collects its main positivity properties. P ROPOSITION 2.1. Suppose V , f ∈ CT and consider the periodic problem w ′ + V w = f,

w ∈ CT1 .

(2.4)

Then, the following assertions are true: T (a) (2.4) has a unique solution for each f ∈ CT if, and only if, 0 V = 0. In such case, we denote by ψ[V ,f ] its unique solution. T (b) In case 0 V > 0, ψ[V ,f ] ≫ 0 if f > 0, and ψ[V ,f ] ≪ 0 if f < 0. T (c) In case 0 V < 0, ψ[V ,f ] ≪ 0 if f > 0, and ψ[V ,f ] ≫ 0 if f < 0. T (d) In case 0 V = 0, (2.4) possesses a solution if, and only if,

0

T

e

s 0

V

f (s) ds = 0.

(2.5)


365

In particular, (2.4) cannot admit a solution if either f > 0 or f < 0. Actually, under condition (2.5) any solution of w′ + V w = f must be T -periodic. P ROOF. For any w0 ∈ R, the unique solution of the Cauchy problem

w ′ + V w = f, w(0) = w0 ,

is given by w(t) = e−

t

t s w0 + e 0 V f (s) ds ,

V

0

t ∈ R,

0

(2.6)

and it is T -periodic if, and only if, w(0) = w(T ). Equivalently,

T V e 0 − 1 w0 = Thus, in case

T 0

w0 :=

T

e

0

s 0

V

f (s) ds.

(2.7)

V = 0, T

e

0

e

s 0

T 0

V

f (s) ds

V

(2.8)

−1

T is the unique initial value to a T -periodic solution, while, if 0 V = 0, then identity (2.7) implies (2.5). As a result from this elementary analysis, substituting (2.8) into (2.6) and rearranging T terms, we find that under assumption 0 V = 0 the function ψ[V ,f ] (t) := =

e−

e

T 0

T 0

0

V

e−

e

t

−1

t 0

V

V

V

−1

T

e

0

s

T

t

e

0

s 0

T f (s) ds + e 0 V − 1

V

V

f (s) ds + e

T 0

V

0

0

t s

e

0

V

t s

e

0

V

f (s) ds

f (s) ds ,

t ∈ R,

provides us with the unique solution of (2.4). Note that, for any V ∈ CT , the auxiliary function (t) :=

t

T

e

s 0

V

f (s) ds + e

T 0

V

0

t s

e

0

V

f (s) ds,

t ∈ R,

(2.9)

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satisfies ≫ 0 if f > 0, Consequently, in case ψ[V ,f ] (t) =

T 0

V > 0 we have that, for each t ∈ R,

e−

e

T 0

and ≪ 0 if f < 0.

t 0

V

V

(t) > 0

−1

T if f > 0, whereas ψ[V ,f ] (t) < 0 if f < 0. Similarly, in case 0 V < 0, we have that ψ[V ,f ] ≫ 0 if f < 0, and ψ[V ,f ] ≪ 0 if f > 0, which concludes the proof of parts (a), (b) and (c). T Finally, suppose 0 V = 0. In this case, we already know that (2.5) is necessary for the existence of a solution to (2.4). Suppose (2.5). Then, for each w0 ∈ R, we have that (2.6) satisfies T T s e 0 V f (s) ds = w0 = w(0) w(T ) = e− 0 V w0 + 0

and, therefore, it provides us with a solution of (2.4). This concludes the proof.

T As an immediate consequence from Proposition 2.1, in case 0 V = 0 the linear differential operator (2.3) is a bijection. Clearly, it is continuous. So, it follows from the open mapping theorem that it defines a linear isomorphism between CT1 and CT . Subsequently, we shall denote by J the canonical injection J : CT1 → CT . By Ascoli–Arzela’s theorem, J is compact, i.e., it sends bounded sets of CT1 into relatively compact subsets of CT . Therefore, the resolvent operator RV := J

d +V dt

−1

: CT → CT

is as well compact. Actually, it is strongly positive if T if 0 V < 0, i.e., RV P \ {0} ⊂ Int P

if

(2.10) T 0

V > 0, while it is strongly negative

T

V > 0,

(2.11)

0

while, RV P \ {0} ⊂ −Int P

if

0

T

V < 0.

(2.12)


367

As a consequence from these positivity properties, one can easily get the main comparison properties associated to Problem (2.4). To state them we need the following elementary concepts. D EFINITION 2.2. Given V , f ∈ CT , (1) a function w ∈ CT1 is said to be a subsolution (resp. strict subsolution) of (2.4) if w ′ + V w f (resp. w ′ + V w < f ); (2) a function w ∈ CT1 is said to be a supersolution (resp. strict supersolution) of (2.4) if w ′ + V w f (resp. w ′ + V w > f ). T P ROPOSITION 2.3. Suppose V , f ∈ CT , with 0 V = 0. Then: T (a) In case 0 V > 0, any strict subsolution w of (2.4) satisfies w ≪ ψ[V ,f ] , whereas w ≫ ψ[V ,f ] for any strict supersolution w. T (b) In case 0 V < 0, any strict subsolution w of (2.4) satisfies w ≫ ψ[V ,f ] , whereas w ≪ ψ[V ,f ] for any strict supersolution w. T P ROOF. Suppose 0 V > 0 and w is a strict subsolution of (2.4). Then, the auxiliary function p defined by p :=

d + V (ψ[V ,f ] − w) dt

satisfies p > 0 and, due to (2.11), ψ[V ,f ] − w = RV (p) ≫ 0. Similarly, when w is a strict supersolution of (2.4), q :=

d + V (w − ψ[V ,f ] ) > 0 dt

and (2.11) implies w − ψ[V ,f ] = RV (q) ≫ 0, which concludes the proof of part (a). The proof of part (b) follows the same scheme, though one should use (2.12), instead of (2.11).

2.2. The single logistic equation The following result characterizes the existence of positive solutions of (2.1).

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P ROPOSITION 2.4. Suppose α, β ∈ CT satisfy (2.2). Then, (2.1) possesses a positive T periodic solution if, and only if, ρ > 0. Moreover, it is unique if it exists and if we denote it by θ[ρα,β] , then, θ[ρα,β] =

1 , ψ[ρα,β]

(2.13)

where ψ[ρα,β] stands for the unique positive solution of z′ + ραz = β,

z ∈ CT1 .

(2.14)

P ROOF. Note that any positive solution w ∈ CT1 of (2.1) must satisfy w ≫ 0, since w ′ = (ρα − βw)w. Moreover, the change of variable w = z−1 transforms (2.1) into the linear equation (2.14). Thus, the positive T -periodic solutions of (2.1) are in one-to-one correspondence with the positive solutions of problem (2.14). Suppose ρ = 0. Then, (2.2) implies ρ αˆ = 0 and, hence, thanks to Proposition 2.1(a), (2.14) possesses a unique solution, ψ[ρα,β] . Moreover, thanks to Proposition 2.1(b)–(c), ψ[ρα,β] ≫ 0 if ρ > 0, while ψ[ρα,β] ≪ 0 if ρ < 0. Finally, note that if ρ = 0, then, due to Proposition 2.1(d), (2.14) cannot admit a positive solution, since

T

e

0

ρ

s 0

α

β(s) ds =

T

β(s) ds > 0.

0

Combining these features concludes the proof.

We now analyze some important comparison properties between subsolutions, supersolutions and solutions of (2.1). First, we will introduce some basic concepts. D EFINITION 2.5. Let ρ ∈ R and α, β ∈ CT . Then, (1) a function w ∈ CT1 is said to be a subsolution (resp. strict subsolution) of (2.1) if w ′ ραw − βw 2 (resp. w ′ < ραw − βw 2 ); (2) a function w ∈ CT1 is said to be a supersolution (resp. strict supersolution) of (2.1) if w ′ ραw − βw 2 (resp. w ′ > ραw − βw 2 ). P ROPOSITION 2.6. Suppose ρ > 0 and α, β ∈ CT satisfy αˆ > 0 and β > 0. Then, any strict subsolution w ≫ 0 of (2.1) satisfies w ≪ θ[ρα,β] , while any strict supersolution w ≫ 0 satisfies w ≫ θ[ρα,β] . P ROOF. Suppose w ≫ 0 is a strict subsolution of (2.1). Then, the function z := 1/w is a strict supersolution of (2.14) and, hence, it follows from Proposition 2.3(a) that z ≫ ψ[ρα,β] . Therefore, w≪

1 = θ[ρα,β] . ψ[ρα,β]


369

Similarly, if w ≫ 0 is a strict supersolution of (2.1), then z¯ := 1/w is a strict subsolution of (2.14) and, hence, z¯ ≪ ψ[ρα,β] . Consequently, w ≫ θ[ρα,β] . C OROLLARY 2.7. Let, for each j ∈ {1, 2}, ρj > 0 and αj , βj ∈ CT satisfying αj > 0 and βj > 0. Suppose ρ1 ρ2 ,

α1 α2 ,

(ρ1 , α1 , β1 ) = (ρ2 , α2 , β2 ).

β1 β2 ,

(2.15)

Then, θ[ρ1 ,α1 ,β1 ] ≪ θ[ρ2 ,α2 ,β2 ] . P ROOF. Under conditions (2.15), θ[ρ1 ,α1 ,β1 ] ≫ 0 is a strict subsolution of w ′ = ρ2 α2 w − β2 w 2

and the conclusion follows from Proposition 2.6.

2.3. Point-wise behaviour of the map ρ → θ[ρα,β] In this section we regard to the unique positive solution of (2.1), θ[ρα,β] , as a map depending on the parameter ρ > 0 in order to analyze some sharp properties of the global bifurcation diagram of non-negative solutions of (2.1). Our main result reads as follows. T HEOREM 2.8. Suppose αˆ > 0 and β > 0, and set Θ(ρ) := θ[ρα,β] ∈ CT1 ,

ρ > 0.

(2.16)

Then, the map (0, ∞) → CT1 , ρ → Θ(ρ), is real analytic and it possesses the following asymptotic expansion at ρ = 0 Θ(ρ) =

αˆ ρ + ρ 2 I2 + O ρ 3 βˆ

as ρ ↓ 0,

(2.17)

where I2 stands for the function defined by I2 (t) :=

t 0

α−

αˆ βˆ

0

t

β−

1 T

T 0

0

t

α−

αˆ βˆ

T 0

0

t

β ,

t ∈ R.

In particular, lim Θ(ρ)C = 0. ρ↓0

T

(2.18)

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If, in addition, α > 0, then the map (0, ∞) → CT , ρ → Θ(ρ), is strongly increasing in the sense that Θ(ρ) ≫ Θ(ρ) ˜ if ρ > ρ. ˜ Further, if α ≫ 0 and β ≫ 0, then, for each ρ > 0, αL αM ρ Θ(ρ) ρ βM βL

(2.19)

Θ(ρ) α = ρ↑∞ ρ β

(2.20)

and lim

in CT .

P ROOF. Note that the solutions of (2.1) are the zeroes of the non-linear operator F : R × CT1 → CT defined by F(ρ, w) := w ′ − ραw + βw 2 ,

(2.21)

which is real analytic. Fix ρ0 > 0. Then, F ρ0 , Θ(ρ0 ) = 0

and Du F(ρ0 , Θ(ρ0 )) ∈ L(CT1 ; CT ) is given through d + 2βΘ(ρ0 ) − ρ0 α. Du F ρ0 , Θ(ρ0 ) := dt

(2.22)

Since Θ(ρ0 ) ≫ 0 satisfies

2 dΘ(ρ0 ) = ρ0 αΘ(ρ0 ) − β Θ(ρ0 ) , dt

division by Θ(ρ0 ) and integration in [0, T ] gives Θ(ρ0 )(T ) 0 = Log = Θ(ρ0 )(0)

T

0

ρ0 α − βΘ(ρ0 ) = 0

and, hence,

0

T

2βΘ(ρ0 ) − ρ0 α =

T

β(t)Θ(ρ0 )(t) dt > 0, 0

since β > 0. Thus, thanks to Proposition 2.1, Du F(ρ0 , Θ(ρ0 )) is a linear isomorphism between CT1 and CT . Therefore, thanks to the implicit function theorem, there exist ε ∈ (0, ρ0 ), δ > 0, and a unique real analytic map W : (ρ0 − ε, ρ0 + ε) → w ∈ CT1 : w − Θ(ρ0 )C 1 < δ T


371

such that W (ρ0 ) = Θ(ρ0 ), F(ρ, W (ρ)) = 0 if |ρ − ρ0 | < ε, and w = W (ρ) if F(ρ, w) = 0 with |ρ − ρ0 | < ε and w − Θ(ρ0 ) C 1 < δ. As W (ρ0 ) = Θ(ρ0 ) ≫ 0, necessarily W (ρ) ≫ T 0 for ρ ∼ ρ0 , and, therefore, W (ρ) = Θ(ρ), by the uniqueness of the positive solution of (2.1). This shows that ρ → Θ(ρ) is real analytic. Although the fact that the map (0, ∞) → CT , ρ → Θ(ρ), is strictly increasing if α > 0 is a consequence from Corollary 2.7, it should be noted that implicit differentiation in F ρ, Θ(ρ) = 0

gives rise to

d dΘ + 2βΘ(ρ) − ρα (ρ) = αΘ(ρ) > 0 dt dρ

and, hence, dΘ (ρ) = dρ

d + 2βΘ(ρ) − ρα dt

−1

αΘ(ρ) ≫ 0,

because of (2.11). To prove (2.17) we will use a celebrated device introduced by M.G. Crandall and P.H. Rabinowitz [6]. Note that Du F(0, 0) =

d 1 : C → CT dt T

and, hence, N Du F(0, 0) = span [1].

Moreover,

CT1

= N Du F(0, 0) ⊕ Y,

Y := y ∈ CT1 :

0

T

y=0 .

Indeed, any w ∈ CT1 admits a unique decomposition as w = x + y,

x ∈ R, y ∈ Y.

Actually, x = w, ˆ

y = w − w. ˆ

Now, consider the auxiliary operator G : R2 × Y → CT defined by G(s, ρ, y) := y ′ − ρα(1 + y) + βs(1 + y)2 ,

(s, ρ, y) ∈ R2 × Y.

(2.23)

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J. López-Gómez

It should be noted that G(s, ρ, y) = 0 implies F(ρ, s(1 + y)) = 0. It is rather clear that G is a real analytic operator such that G(0, 0, 0) = 0. Moreover, the operator D(ρ,y) G(0, 0, 0) : R × Y → CT is given by D(ρ,y) G(0, 0, 0)(ρ, y) = y ′ − ρα,

(ρ, y) ∈ R × Y,

and, so, it is a linear isomorphism. Indeed, if for some (ρ, y) ∈ R × Y one has that y ′ = ρα, then integrating in [0, T ] gives ρ αˆ = 0 and, hence, ρ = 0, since αˆ > 0. Thus, y ′ = 0 and, therefore, y is constant. Consequently, as it has zero average, we obtain that y = 0, which concludes the proof of the injectivity. Now, fix f ∈ CT . Then, it is straightforward to check that ˆ T t t T t f fˆ t 1 − y(t) := − α+ α+ f− f , αˆ 0 T αˆ 0 0 0 0 0

t ∈ R,

provides us with the unique element of Y solving fˆ ρ := − . αˆ

D(ρ,y) G(0, 0, 0)(ρ, y) = f,

Therefore, thanks to the implicit function theorem, there exist s0 > 0, δ > 0, and a unique real analytic map (ρ, y) : (−s0 , s0 ) → (−δ, δ) × y ∈ Y : y C 1 < δ T

such that (ρ(0), y(0)) = (0, 0), G(s, ρ(s), y(s)) = 0 for each s ∈ (−s0 , s0 ), and (ρ, y) = (ρ(s), y(s)) if G(s, ρ, y) = 0 with |s| < s0 , |ρ| < δ, and y C 1 < δ. In particular, T

F ρ(s), s 1 + y(s) = 0,

|s| < s0 ,

and, so, for sufficiently small s > 0,

(ρ, w) := ρ(s), s 1 + y(s)

provides us with a positive T -periodic solution of (2.1). Necessarily, for sufficiently small s > 0, we have that s 1 + y(s) = Θ ρ(s)

(2.24)

because of the uniqueness of the positive solution of (2.1). Now, in order to find the lowest order terms of the local developments ρ(s) =

∞ n=1

n

ρn s ,

y(s) =

∞ n=1

s n yn ,

yn ∈ Y, n 1,

(2.25)


373

we substitute (2.25) into the equation of the zeroes of G. Then, we get ∞ n=1

4

s n yn′ = α

∞ n=1

8

ρn s n − sβ 1 +

∞ n=1

s n yn

958

1+

∞

s n yn

n=1

9

and identifying terms of order one in both members gives y1′ = ρ1 α − β. Thus, βˆ ρ1 = , αˆ

y1 (t) = ρ1

0

t

α−

0

t

T t T t 1 ρ1 β α− β− T 0 0 0 0

and, therefore, (2.24) shows that ρ(s) = ρ1 s + O s 2 and Θ ρ(s) = s 1 + s y1 (t) + O s 2

(2.26)

as s ↓ 0. Thanks again to the implicit function theorem, one can eliminate s as a function of ρ at ρ = 0 from the identity

Actually,

ρ1 s + O s 2 = ρ.

s=

αˆ 1 ρ + O ρ2 = ρ + O ρ2 , ˆ ρ1 β

and, so, substituting this expansion into the second identity of (2.26) shows that Θ(ρ) =

αˆ αˆ ρ + y1 ρ 2 + O ρ 3 βˆ βˆ

as ρ ↓ 0, which provides us with the asymptotic expansion (2.17). Subsequently, we suppose that α ≫ 0 and β ≫ 0. The global estimates (2.19) and (2.20) are consequences from Proposition 2.6. Indeed, setting Θ := Θ(ρ), we have that ραL Θ − βM Θ 2 Θ ′ = ραΘ − βΘ 2 ραM Θ − βL Θ 2 , and, hence, for each ρ > 0, Θ(ρ) is a positive subsolution of w ′ = ραM w − βL w 2 and a positive supersolution of w ′ = ραL w − βM w 2 . Therefore, (2.19) follows from Proposition 2.6 by taking into account that αβML ρ and βαML ρ provide us with the unique T -periodic positive solutions of each of these autonomous equations.

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J. López-Gómez

Now, fix δ > 0 sufficiently small so that that α α δ −δ 0, say ρ ρ0 , we have that

δ α ¯ − θ < − ρ 2 β θ¯ ρ θ¯ ′ = w ′ , β 2

δ α − θ > ρ 2 βθ ρθ ′ = w′ . β 2

ραw − βw = ρ β θ¯ 2

2

and ραw − βw2 = ρ 2 βθ

Consequently, for each ρ ρ0 , w and w provide with a strict subsolution and a strict supersolution of (2.1), respectively, and, hence, thanks to Proposition 2.6, w = ρ θ ≪ Θ(ρ) ≪ w = ρ θ¯ . Thus, it follows from (2.27) that, for each ρ ρ0 , α Θ(ρ) α −δ≪ ≪ + δ. β ρ β Therefore, passing to the limit as ρ ↑ ∞, shows that Θ(ρ) α Θ(ρ) α − δ lim inf lim sup + δ. ρ↑∞ β ρ ρ β ρ↑∞ As these inequalities are valid for any δ > 0, the proof of (2.20) is concluded, as well as the proof of the theorem. It should be noted that the strong monotonicity of Θ(ρ) is lost when α changes of sign. Indeed, suppose that, for some sufficiently small δ > 0, β(t) = 0 and α(t) < 0 for each t ∈ [0, δ]. Then, for each t ∈ [0, δ] we have that θ[ρα,β] (t) = eρ Since

t 0

t 0

α

θ[ρα,β] (0).

α < 0, the map ρ → θ[ρα,β] (t) is decreasing for each t ∈ (0, δ].


375

Fig. 1. Graph of ρ → Θ(ρ)(t) in case α ≫ 0 and β ≫ 0.

In Fig. 1 we have represented the bifurcation diagram (ρ, Θ(ρ)(t)) for some t ∈ R in the (ρ, Θ)-plane in the special, though important, case when α ≫ 0 and β ≫ 0. Thanks to (2.19) the curve ρ → Θ(ρ)(t) must be confined in between the straight lines Θ = βαML ρ and Θ = αβML ρ, and, due to (2.17) and (2.20), its tangents at ρ = 0 and ρ = ∞ are αˆ ρ βˆ

Θ=

and Θ =

α(t) ρ, β(t)

respectively.

2.4. Attractiveness of θ[ρα,β] Note that the linearized equations of (2.1) at w = 0 and w = Θ(ρ) are given by w ′ = ραw

and w ′ = ρα − 2βΘ(ρ) w,

respectively, whose Floquet multipliers are eρ

T 0

α

and e

T 0

[ρα−2βΘ(ρ)]

.

As a result, w = 0 is linearly stable if ρ < 0, linearly neutrally stable if ρ = 0 and linearly unstable if ρ > 0. Moreover, in the proof of Theorem 2.8 we have seen that, for each ρ > 0,

0

T

ρα − βΘ(ρ) = 0,

(2.28)

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J. López-Gómez

and, hence, e

T 0

[ρα−2βΘ(ρ)]

= e−

T 0

[βΘ(ρ)]

< 1.

Therefore, Θ(ρ) is linearly stable. Actually, it is easy to see that 0 is a global attractor of (2.1) if ρ 0, whereas Θ(ρ) attracts to all positive solutions of (2.1) if ρ > 0.

3. Linearized stability of the semi-trivial solutions Thanks to Proposition 2.4, (1.2) possesses a semi-trivial state—throughout the remaining of the chapter, positive—of the form (u, 0) if and only if λ > 0. Moreover, in such case, (θ[λℓ,a] , 0) is the unique semi-trivial state of this form. Similarly, (0, θ[µm,d] ) provides us with the unique semi-trivial state of (2.1) of the form (0, v), and it exists if and only if µ > 0. The following result characterizes the stability of these states and the stability of the trivial state (0, 0). P ROPOSITION 3.1. The following assertions are true: (a) (0, 0) is linearly stable if λ < 0 and µ < 0, and it is linearly unstable if either λ > 0 or µ > 0. (b) Suppose λ > 0. Then, (θ[λℓ,a] , 0) is linearly unstable if and only if µ>

1 T

T

c(t)θ[λℓ,a] (t) dt,

0

(3.1)

and linearly stable if and only if µ
0. Then, (0, θ[µm,d] ) is linearly unstable if and only if λ>

1 T

T

b(t)θ[µm,d] (t) dt,

0

(3.4)

and linearly stable if and only if 1 λ< T

0

T

b(t)θ[µm,d] (t) dt.

(3.5)


377

Consequently, the curve of change of stability of (0, θ[µm,d] ) in the (λ, µ)-plane is given through its curve of neutral stability λ = g(µ) :=

1 T

T


0

(3.6)

P ROOF. The linearization of (1.2) at any solution (u0 , v0 ) ∈ CT1 × CT1 is given by

u′ = (λ ℓ − 2au0 − bv0 )u − bu0 v, v ′ = −cv0 u + (µ m − 2dv0 − cu0 )v.

(3.7)

When (u0 , v0 ) = (0, 0), (3.7) becomes into

u′ = λℓu, v ′ = µmv,

whose Poincaré map is given by P(x, y) =

eλT 0

0 eµT

x , y

(x, y) ∈ R2 ,

since ℓˆ = m ˆ = 1. Thus, its Floquet multipliers, eλT and eµT , are less than one if λ < 0 and µ < 0, while some of them is greater than one if either λ > 0 or µ > 0, which concludes the proof of part (a). When (u0 , v0 ) = (θ[λℓ,a] , 0), (3.7) becomes into

u′ = (λ ℓ − 2aθ[λℓ,a] )u − bθ[λℓ,a] v, v ′ = (µ m − cθ[λℓ,a] )v,

(3.8)

and its associated Poincaré map is given by P(x, y) =

8

e

T 0

(λℓ−2aθ[λℓ,a] )

0

9 x T , (µm−cθ ) y [λℓ,a] e0 E

(x, y) ∈ R2 ,

for some constant E ∈ R whose explicit knowledge is not important here. Thanks to (2.28),

0

T

(λℓ − aθ[λℓ,a] ) = 0

and, hence, 0<e

T 0

(λℓ−2aθ[λℓ,a] )

= e−

T 0

a(t)θ[λℓ,a] (t) dt

< 1.

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J. López-Gómez

Consequently, the attractive character of (θ[λℓ,a] , 0) is given by the remaining Floquet multiplier ν := e

T 0

(µm−cθ[λℓ,a] )

T

= eµT −

0

c(t)θ[λℓ,a] (t) dt

.

As ν > 1 when (3.1) is satisfied, ν = 1 if (3.3) is satisfied, and 0 < ν < 1 under condition (3.2), the proof of part (b) is concluded. Part (c) follows by symmetry. This ends the proof.

4. The curves of change of stability of the semi-trivial positive solutions In this section we shall study some global properties of the curves of neutral stability (3.3) and (3.6) of the semi-trivial solutions of (1.2). Such analysis is imperative in order to ascertain the shape of each of the following regions within the parameter space (λ, µ): Ruu := (λ, µ) ∈ (0, ∞)2 : (θ[λℓ,a] , 0) and (0, θ[µm,d] ) are l.u. , Rss := (λ, µ) ∈ (0, ∞)2 : (θ[λℓ,a] , 0) and (0, θ[µm,d] ) are l.s. , Rsu := (λ, µ) ∈ (0, ∞)2 : (θ[λℓ,a] , 0) is l.s., (0, θ[µm,d] ) is l.u. , Rus := (λ, µ) ∈ (0, ∞)2 : (θ[λℓ,a] , 0) is l.u., (0, θ[µm,d] ) is l.s. , Ru⋆ := (λ, µ) ∈ (0, ∞) × (−∞, 0]: (θ[λℓ,a] , 0) is l.u. , Rs⋆ := (λ, µ) ∈ (0, ∞) × (−∞, 0]: (θ[λℓ,a] , 0) is l.s. , R⋆u := (λ, µ) ∈ (−∞, 0] × (0, ∞): (0, θ[µm,d] ) is l.u. , R⋆s := (λ, µ) ∈ (−∞, 0] × (0, ∞): (0, θ[µm,d] ) is l.s. ,

(4.1)

(4.2)

(4.3)

(4.4)

where l.u. stands for linearly unstable and l.s. for linearly stable. As the global behaviour of the curves of neutral stability of the semi-trivial states is strongly based upon the nature of the model under study, i.e., under the sign properties of the interaction coefficient functions b(t) and c(t), in the subsequent discussion we will have to distinguish several different cases. We begin the section by giving a general result which is a straightforward consequence from Theorem 2.8. T HEOREM 4.1. Suppose α, β, γ ∈ CT satisfy α ≫ 0,

β ≫ 0,

αˆ = βˆ = 1,

(4.5)

and consider the function 1 N (ρ) := T

0

T

γ (t)θ[ρα,β] (t) dt,

ρ > 0.

(4.6)


379

Then, 1 N (ρ) = γˆ ρ + T

T

0

γ (t)I2 (t) dt ρ 2 + O ρ 3

as ρ ↓ 0,

(4.7)

where I2 (t) :=

0

t

1 (α − β) − T

T 0

t 0

t ∈ R,

(α − β),

(4.8)

and 1 N (ρ) = ρ↑∞ ρ T lim

0

T

γ (t)

α(t) dt. β(t)

(4.9)

Moreover, ρ → N (ρ) is increasing if γ > 0, decreasing if γ < 0, and, in general, is far from monotone if γ changes of sign. In such case, (4.9) can be either negative, or positive, or zero, according to the value of the average on its right-hand side. P ROOF. By (4.5), it follows from Theorem 2.8 that

Thus,

θ[ρα,β] = ρ + I2 ρ 2 + O ρ 3 as ρ ↓ 0. N (ρ) :=

1 T

0

T

γ (t)θ[ρα,β] (t) dt = γˆ ρ +

1 T

0

T

γ (t)I2 (t) dtρ 2 + O ρ 3 ,

which is (4.7). The validity of (4.9) is an immediate consequence from (2.20). The re maining assertions of the theorem are obvious, since θ[ρα,β] ≫ 0. It should be noted that, in general, nothing can be said about the concavity of N (ρ) at ρ = 0. Indeed, since I2 changes of sign if I2 = 0, because Iˆ2 = 0, the average of the function γ I2 can have any sign we wish by choosing and adequate γ that may be taken either positive, or negative, or changing of sign, in strong contrast with the autonomous case, where N (ρ) = γρ for every ρ > 0. 4.1. The species u and v compete (b > 0 and c > 0) Besides (1.7), throughout this section we assume that ℓ ≫ 0,

m ≫ 0,

a ≫ 0,

d ≫ 0,

b > 0,

c > 0,

(4.10)

though most of our discussion can be easily adapted to cover much weaker requirements. Under assumptions (4.10), the curves of neutral stability of the semi-trivial states

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J. López-Gómez

(θ[λℓ,a] , 0) and (0, θ[µm,d] ), (3.3) and (3.6), are increasing in λ and µ, respectively, and satisfy f (λ) > 0,

(λ, µ) ∈ (0, ∞)2 .

g(µ) > 0,

(4.11)

It should be noted that these are the curves delimiting the regions defined by (4.1) and (4.2). Thanks to Theorem 4.1, the tangents of these curves at (λ, µ) = (0, 0) are given by ˆ µ = cλ ˆ and λ = bµ,

(4.12)

respectively, as for the autonomous counterpart of (1.2)—where these are the curves of neutral stability of (λ, 0) and (0, µ)—and their tangents at infinity are given by 1 T

µ = αλ,

α :=

λ = βµ,

1 β := T

T

c(t)

0

T 0

ℓ(t) dt, a(t)

(4.13)

m(t) dt, b(t) d(t)

respectively. In strong contrast with the autonomous case—where (4.12) and (4.13) are the same straight lines—as a consequence from the non-autonomous character of (1.2), the relative positions of the straight lines (4.12) and (4.13) can be inter-exchanged at (λ, µ) = (0, 0) and at infinity, so entailing the existence of a crossing point between the curves of change of stability of the semi-trivial states; a feature of great significance from the point of view of the applications, as it might allow us designing environments where none of the competitors is driven to extinction by the other. Most precisely, there are admissible choices of the function coefficients a, b, c, d, ℓ and m, for which either T 1 T ℓ(t) m(t) ˆbcˆ < 1 and αβ = 1 dt · dt > 1, (4.14) c(t) b(t) T 0 a(t) T 0 d(t) or else 1 bˆ cˆ > 1 and αβ = T

0

T

c(t)

1 ℓ(t) dt · a(t) T

0

T

b(t)

m(t) dt < 1. d(t)

(4.15)

In such circumstances, as the curves µ = f (λ), λ > 0, and λ = g(µ), µ > 0, are real analytic, they must cross at most at a finite number of points—at least one—whose total sum of contact orders must be an odd integer number. To construct examples satisfying any of these requirements one can make the following choices: 2π 2π a = d = 1, ℓ := 1 + ℓ1 sin · , m := 1 + m1 sin · , (4.16) T T for some constants ℓ1 , m1 ∈ (−1, 1), and 2π 2π · , c := c0 + c1 sin · , b := b0 + b1 sin T T

(4.17)


381

for some constants b0 > 0,

c0 > 0,

b1 ∈ (−b0 , b0 ),

c1 ∈ (−c0 , c0 ).

For these choices, we have that bˆ = b0 ,

cˆ = c0 ,

and α=

1 T

0

T

c(t)

ℓ(t) 1 dt = c0 + c1 ℓ1 , a(t) 2

β=

1 T

T

b(t) 0

m(t) 1 dt = b0 + b1 m1 . d(t) 2

Thus, (4.14) and (4.15) are equivalent to 1 1 b0 c0 < 1 and c0 + c1 ℓ1 b0 + b1 m1 > 1, 2 2

(4.18)

and 1 1 b0 c0 > 1 and c0 + c1 ℓ1 b0 + b1 m1 < 1, 2 2

(4.19)

respectively. We now show that any of these conditions can be reached by an adequate choice of the several constants involved in their settings. Take, for sufficiently small ε > 0, b0 = c0 = 1 − ε,

b1 = c1 = 1 − 2ε.

Then, the function p(ε) defined by 1 1 p(ε) := 1 − ε + (1 − 2ε)ℓ1 1 − ε + (1 − 2ε)m1 , 2 2

ε > 0,

satisfies 1 1 p(0) = 1 + (ℓ1 + m1 ) + ℓ1 m1 2 4 and, hence, p(0) > 1 if ℓ1 > 0 and m1 > 0. Thus, if we choose ℓ1 , m1 ∈ (0, 1), then, for sufficiently small ε > 0, we have that p(ε) > 1, by continuity, and, consequently, (4.18) is satisfied. On the contrary, choosing b0 = c0 = 1 + ε,

b1 = c1 = 1,

the auxiliary function n(ε) defined by 1 1 n(ε) := 1 + ε + ℓ1 1 + ε + m1 , 2 2

ε > 0,

382

J. López-Gómez

Fig. 2. The curves µ = f (λ) and λ = g(µ) in case (4.18).

satisfies 1 1 n(0) = 1 + (ℓ1 + m1 ) + ℓ1 m1 2 4 and, hence, n(0) < 1 if ℓ1 < 0 and m1 < 0. Thus, if we choose ℓ1 , m1 ∈ (−1, 0), then, for sufficiently small ε > 0, we have that n(ε) < 1, by continuity, and, consequently, (4.19) holds. In Fig. 2 we have represented the curves of neutral stability of the semi-trivial states in an admissible situation satisfying (4.18). It should be noted that, for the previous choice, we have that, for each sufficiently small ε > 0, −1 −1 1 1 1 = b0 + b1 m1 = 1 − ε + (1 − 2ε)m1 < c0 = 1 − ε < 1 β 2 2 and 1 1 1 1 α = c0 + c1 ℓ1 = 1 − ε + (1 − 2ε)ℓ1 > >1 = 2 2 b0 1 − ε since ℓ1 > 0 and m1 > 0. As illustrated by Fig. 2, the curves of change of stability of the semi-trivial states must cross at least once, and at most at a finite number of points whose total sum of contact orders must be odd. In the situations described by Fig. 2, one among all admissible ones, these curves divide the first quadrant into four different regions: the two regions enclosed by these curves, and the two exterior regions. In general,


383

Fig. 3. The curves µ = f (λ) and λ = g(µ) in case (4.19).

the region enclosed between them consists of a finite number of components—one unbounded, and the remaining bounded. Within the bounded components both semi-trivial states are—alternatively—either linearly unstable, or linearly stable. In Fig. 2, both are linearly unstable, because µ > f (λ) and λ > g(µ). Hence, this is the region Ruu defined in (4.1). Independently of the number of bounded components enclosed by the curves of neutral stability of the semi-trivial states, the unbounded component is always a subset of the region Rss defined in (4.1), where both semi-trivial states are linearly stable. The remaining regions correspond with the regions Rsu and Rus defined in (4.2), where one of the semi-trivial states is linearly stable and the other linearly unstable. As in all competing species models, in this example we have that Rs∗ = (0, ∞) × (−∞, 0],

Ru∗ = ∅,

R∗s = (−∞, 0] × (0, ∞),

R∗u = ∅.

In Fig. 3 we have represented an admissible situation adjusted to (4.19) for the choices previously analyzed. Now, for each sufficiently small ε > 0, we have that 1 1 1 1 c0 = 1 + ε > 1, β 2 2

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J. López-Gómez

since ℓ1 < 0 and m1 < 0. As the relative positions between the curves of neutral stability of the semi-trivial states suffered a drastic change between the cases sketched in Figs. 2 and 3, in the latest case, within the bounded component enclosed by µ = f (λ) and λ = g(µ) both semi-trivial states must be linearly stable, while in the unbounded component both are linearly unstable. As it is easily realized, this inter-exchange between the relative positions of the curves of neutral stability of the semi-trivial states entails dramatic changes from the point of view of applications. Although the previous examples exhibit a reminiscent behaviour from the autonomous model for (λ, µ) in a neighborhood of (0, 0), in the sense that, for such range of (λ, µ) low intensity competition occurs if bˆ cˆ < 1, while high intensity competition occurs if bˆ cˆ > 1, these simple examples illustrate very well how temporal heterogeneities can affect the dynamics of (1.1), as for (λ, µ) sufficiently large the intensity of the competition is measured ˆ Actually, for (λ, µ) large, low intensity competition by α, instead of c, ˆ and β, instead of b. occurs if αβ < 1 (cf. Fig. 3), while high intensity competition occurs if αβ > 1 (cf. Fig. 2). The observation of this phenomenology goes back to [12]. In the previous examples, a further crossing point, perturbing from (0, 0), might occur if b0 c0 = 1, as a result of the nature of the second order terms of the asymptotic expansion of (3.3) and (3.6) at (0, 0), but we refrain of performing this sharper analysis here (cf. [13] for the corresponding analysis in the autonomous competing species model with diffusion). It should be noted that most of the examples treated in the literature did not cover the previous two cases, but, instead, covered some very special situations where the function coefficients were chosen so that the curves of neutral stability of the semi-trivial states cannot meet in the interior of the first quadrant, as in those cases the method of sub- and supersolutions gives the existence of coexistence states in a rather simple way. Most precisely, let tL , tM ∈ [0, T ] such that (θ[λℓ,a] )j = θ[λℓ,a] (tj ), Then, since

dθ[λℓ,a] dt (tj ) = 0,

θ[λℓ,a] (tj ) =

j ∈ {L; M}.

we have that

ℓ(tj ) λ, a(tj )

j ∈ {L, M},

and, hence, ℓ ℓ λ θ[λℓ,a] λ, a L a M

λ > 0.

(4.20)

By symmetry,

m d

L

µ θ[µm,d]

m d

µ, M

µ > 0.

(4.21)


385

Thus, for each λ > 0, cˆ

ℓ 1 T ℓ λ f (λ) = λ, c(t)θ[λℓ,a] (t) dt cˆ a L T 0 a M

(4.22)

and, for each µ > 0, 1 T m m µ g(µ) = µ. bˆ b(t)θ[µm,d] (t) dt bˆ d L T 0 d M

(4.23)

Consequently, the curves of neutral stability (3.3) and (3.6) cannot meet at a point (λ, µ) = (0, 0) if either m ˆbcˆ ℓ < 1, a M d M

(4.24)

ℓ m > 1. bˆ cˆ a L d L

(4.25)

or

Actually, in any of these cases the curves µ = f (λ) and λ = g(µ) divide the first quadrant into three regions and, necessarily, either Rss = ∅ or Ruu = ∅ (cf. Fig. 4). As in the autonomous model, low intensity competition occurs under (4.24), while high intensity competition occurs if (4.25) is satisfied. It should be noted that (4.24) and (4.25) become into bˆ cˆ < 1 and bˆ cˆ > 1, respectively, if ℓ = a and m = d. These are the unique two possible situations exhibited by the autonomous model.

Fig. 4. Curves of neutral stability in cases (4.24) (a) and (4.25) (b).

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4.2. The species v preys on u (b > 0 and c < 0) Then, the curves of neutral stability of the semi-trivial states cannot meet at a point (λ, µ) = (0, 0), since 1 T

1 g(µ) = T

f (λ) =

T

c(t)θ[λℓ,a] (t) dt < 0

0

for each λ > 0,

and

0

T

b(t)θ[µm,d] (t) dt > 0

for each µ > 0.

Note that, as a consequence from Theorem 2.8, λ → f (λ) is decreasing and µ → g(µ) is increasing, since ℓ > 0 and m > 0 (cf. Fig. 5). If we further assume that ℓ ≫ 0, m ≫ 0, a ≫ 0 and d ≫ 0, then, besides the fact that f (λ) and g(µ) are monotone, the tangents to µ = f (λ) and λ = g(µ) at (0, 0) and at infinity are given by the straight lines (4.12) and (4.13), respectively. Now, the half-plane λ > 0 is divided into four supplementary regions according to the existence and character of each of the semi-trivial states. The interior of the first quadrant is divided into the two regions Rus and Ruu (cf. (4.1) and (4.2)), and the quadrant λ > 0, µ 0, where (1.2) exclusively admits the semi-trivial state (θ[λℓ,a] , 0), is divided into the region µ > f (λ) Ru∗ , where (θ[λℓ,a] , 0) is linearly unstable, and the region µ < f (λ) Rs∗ , where (θ[λℓ,a] , 0) is linearly stable. Moreover, R∗s = (−∞, 0] × (0, ∞),

R∗u = ∅,

Rss = ∅.

Fig. 5. Curves of neutral stability in the predator-prey model.


387

The configuration shown by Fig. 5 is reminiscent of the classical one for the autonomous model, where the curves of change of stability of the semi-trivial states (λ, 0) and (0, µ) are ˆ µ = cλ and λ = bµ, respectively. Actually, if ℓ = a and m = d, then µ = cλ ˆ and λ = bµ provide us with the tangents at (0, 0) and at infinity to the curves µ = f (λ) and λ = g(µ).

4.3. The species u and v cooperate (b < 0 and c < 0) In this case, λ → f (λ) and µ → g(µ) are decreasing and, in general, they look like shows Fig. 6. Now, the regions defined in (4.1)–(4.4) are given by the following identities: Ruu = (0, ∞) × (0, ∞), Rss = ∅, Rus = ∅, Rsu = ∅, Ru∗ = (λ, µ): λ > 0, f (λ) < µ 0 , Rs∗ = (λ, µ): λ > 0, µ < f (λ) , R∗u = (λ, µ): µ > 0, g(µ) < λ 0}, R∗s = {(λ, µ): µ > 0, λ < g(µ)}.

As in the predator-prey model, if we further assume ℓ ≫ 0, m ≫ 0, a ≫ 0 and d ≫ 0, then, besides the fact that f (λ) and g(µ) are monotone, the tangents to the curves of neutral stability µ = f (λ) and λ = g(µ) at (0, 0) and at infinity are given by the straight lines (4.12) and (4.13), respectively. Similarly, the configuration shown by Fig. 6 is reminiscent of the classical one for the autonomous model, where the curves of change of stability of the semi-trivial states (λ, 0) and (0, µ) are µ = cλ and λ = bµ, respectively. Actually, if ℓ = a ˆ provide us with the tangents at (0, 0) and at infinity to and m = d, then µ = cλ ˆ and λ = bλ the curves µ = f (λ) and λ = g(µ).

Fig. 6. Curves of neutral stability for the symbiotic model.

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4.4. The general case when b and c change of sign As for the competing species model, in order to simplify our analysis, besides (1.7) in this section we assume that a ≫ 0,

d ≫ 0,

ℓ ≫ 0,

m ≫ 0.

(4.26)

Then, as in Section 4.1, (4.12) and (4.13) provide us with the tangents at (0, 0) and at infinity of the curves of neutral stability of the semi-trivial states. As we are assuming that b and c change of sign in [0, T ], we have I+b := Int supp b+ = ∅, I−b := Int supp b− = ∅, I+c := Int supp c+ = ∅, I−c := Int supp c− = ∅, and, hence, f (λ) and g(µ) fail to be monotone. Nevertheless, since 1 lim f (λ) = − T (c )M ↓0 1 lim g(µ) = − T (b )M ↓0

T

0

c+ (t)θ[λℓ,a] (t) dt, (4.27)

T

0

b+ (t)θ[µm,d] (t) dt,

uniformly on compact subsets of (λ, µ), the curves of change of stability of the semi-trivial states approximate the corresponding curves of the competition model with interaction function coefficients b+ and c+ , as b− ↓ 0 and c− ↓ 0. Therefore, on compact subsets of (λ, µ), the regions defined by (4.1) and (4.2) approximate the corresponding regions of the associated competition model. Similarly, since lim f (λ) = −

(c+ )M ↓0

1 T

1 lim g(µ) = − T (b+ )M ↓0

T

0

0

c− (t)θ[λℓ,a] (t) dt, (4.28)

T

−

b (t)θ[µm,d] (t) dt,

uniformly on compact subsets of (λ, µ), the curves of change of stability of the semitrivial states approximate the corresponding curves of the symbiotic model with interaction function coefficients −b− and −c− as b+ ↓ 0 and c+ ↓ 0. Consequently, for (λ, µ) varying in any compact subset of (0, ∞)2 , the regions defined by (4.1) and (4.2) approximate the corresponding regions of the symbiotic model with interactions −b− and −c− . Therefore, the general case when b and c change of sign can be regarded as a sort of intermediate situation between a competitive and a symbiotic model. Actually, the map (B, C) : [0, 1] → CT × CT defined, for each ε ∈ [0, 1], by B(ε) := εb+ − (1 − ε)b− + 2ε(1 − ε) b+ − b− , C(ε) := εc+ − (1 − ε)c− + 2ε(1 − ε) c+ − c− ,


389

establishes a homotopy between (b+ , c+ ), (−b− , −c− ) and (b, c). Indeed, B(0), C(0) = − b− , −c− , B(1), C(1) = b+ , c+ , and

B(1/2), C(1/2) = (b, c).

Consequently, (1.2) should exhibit an intermediate behavior between those exhibited by a competition and a symbiotic model. In Fig. 7, we have represented two admissible curves µ = f (λ) and λ = g(µ) in the special case when conditions bˆ > 0,

cˆ > 0,

bˆ cˆ < 1,

(4.29)

and 1 α := T

0

T

ℓ(t) dt < 0, c(t) a(t)

1 β := T

T

b(t) 0

m(t) dt < 0 d(t)

(4.30)

are satisfied. Conditions (4.29) can be reached by taking b+ and c+ with bˆ + cˆ+ < 1 and choosing sufficiently small b− and c− . In order to get (4.30) it suffices to choose ℓ sufficiently small in I+c and m sufficiently small in I+b . This entails the birth rate of each of the species must be relatively slow during the time periods where the intensity of its aggressions on the other species reaches its highest level. Consequently, although the species compete, the model exhibits some sort of cooperative behaviour. Nevertheless, one should be very careful in choosing the adequate ranges of values of the parameters where this phenomenology occurs. For the situation illustrated in Fig. 7, the first quadrant is divided into there regions: the region Ruu , where both semi-trivial states are linearly unstable, which is the region where µ > f (λ) and λ > g(µ), the region Rsu , where (θ[λℓ,a] , 0) is linearly stable and (0, θ[µm,d] ) is linearly unstable, which is the region where λ > 0 and 0 < µ < f (λ), and the region Rus , where (θ[λℓ,a] , 0) is linearly unstable and (0, θ[µm,d] ) is linearly stable, which is given by µ > 0 and 0 < λ < g(µ). In the second quadrant (λ 0 and µ > 0), (0, θ[µm,d] ) is the unique semi-trivial state; it is linearly stable if λ < g(µ) and linearly unstable if λ > g(µ). In the fourth quadrant (λ > 0 and µ 0), (θ[λℓ,a] ) is the unique semi-trivial state; it is linearly stable if µ < f (λ) and linearly unstable if µ > f (λ). It should be noted that under conditions (4.29) and (4.30) the curves µ = f (λ) and λ = g(µ) might cross. In such case, their total number of crossing points, counting contact orders, must be even, because µ = f (λ) and λ = g(µ) are real analytic. Also, note that Fig. 7 shows a low-competitiveintensity behaviour around (λ, µ) = (0, 0) and a symbiotic type of behavior for sufficiently large λ and µ. Now, by choosing b+ and c+ such that bˆ + cˆ+ > 1, b− ∼ 0, c− ∼ 0, ℓ ∼ 0 in I+c and m ∼ 0 in I+b , one gets bˆ > 0,

cˆ > 0,

bˆ cˆ > 1,

α < 0,

β < 0.

(4.31)

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Fig. 7. Curves of neutral stability under conditions (4.29) and (4.30).

Fig. 8. Curves of neutral stability under condition (4.31).

Fig. 8 shows two admissible curves of neutral stability of semi-trivial states adjusted to (4.31). Now, these curves must cross at an odd number of points, counting contact orders, in such a way that both semi-trivial states are linearly unstable in the unbounded component of the enclosed region between them. Rather naturally, the model exhibits a high-intensity-competition behavior around (0, 0), while it exhibits a genuine cooperative behavior for sufficiently large λ and µ; as far as to the structure of the regions defined in (4.1) and (4.2) concerns. It seems the first occasion that such a kind of behaviour has been observed had been in [22] within the context of reaction diffusion models.


391


Now, by choosing sufficiently small b+ and c+ , ℓ ∼ 0 in I−c and sufficiently large in I+c , and m ∼ 0 in I−b and sufficiently large in I+b , the following conditions can be reached bˆ < 0,

cˆ < 0,

α > 0,

β > 0,

αβ > 1.

(4.32)

Fig. 9 shows two admissible curves of neutral stability according to (4.32). As in case (4.31), the total number of crossing points between µ = f (λ) and λ = g(µ) must be odd, though, in case (4.32), Rss includes the unbounded component enclosed by the two curves, while the bounded component containing (0, 0) is a subset of Ruu , in strong contrast with the situation described by Fig. 8. Actually, in case (4.32), the model exhibits a genuine symbiotic behavior around (0, 0), while it possesses a high-intensity-competitive behavior for sufficiently large values of λ and µ. Finally, by choosing sufficiently small b− and c+ , one can easily reach bˆ > 0,

cˆ < 0,

α < 0,

β > 0,

(4.33)

for instance, by taking ℓ = m = a = d = 1. In such cases the curves µ = g(λ) and λ = g(µ) exhibit a behaviour quite reminiscent of the case when v preys on u (cf. Fig. 10); rather naturally, since these models can be regarded as perturbations from the case when b− = 0 and c+ = 0, where b > 0 and c < 0—v preys on u—though the symbiotic effects of the interaction might play a significant role for large values of λ and µ. In Fig. 10 we have represented the curves of change of stability of the semi-trivial states of (1.2) in one of the several admissible situation cases.

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5. The existence of coexistence states In this section we are going to give a very general result about the existence of coexistence states of (1.2) for the general case where b and c change of sign. As a matter of fact, our result covers all admissible situations, as we are not imposing any sign restriction on b and c. The general methodology adopted in this section goes back to the pioneering chapter by J.M. Cushing [7], where one of the parameters, λ or µ, was fixed while the other was considered as a bifurcation parameter in order to get the coexistence states as emanating from one of the semi-trivial states in the context of competing species models. This idea has been extremely fruitful in a number of different contexts [19, Chapter 7]. Most precisely, in Section 5.1 we use the abstract unilateral theorem of [19, Chapter 6] to get an abstract global unilateral theorem for systems, which is the basic abstract result to get—as an easy consequence—our theorem about the existence of coexistence states, which will be given in Section 5.2. Our abstract result admits a number of applications in rather different contexts, but we refrain of giving more details here in. It should be noted that the well known, and very celebrated, unilateral theorems of P.H. Rabinowitz [31] are wrong as they are stated. Actually, there is an available—very recent—counterexample by E.N. Dancer [9]. In the subsequent subsections we shall consider each of the possible interactions separately, as in each special circumstance one can obtain sharper consequences from our abstract theorem.

5.1. Abstract unilateral bifurcation from semi-trivial states Let X be an ordered Banach space whose positive cone P is normal and it has nonempty interior, and consider a nonlinear abstract equation of the form F(ρ, x, y) := L(ρ)(x − x0 , y) + R(ρ, x, y) = 0,

(ρ, x, y) ∈ R × X 2 ,

(5.1)


393

for some x0 ∈ P \ {0}, where (HL) K(ρ) := IX2 − L(ρ) ∈ L(X 2 ), ρ ∈ R, is a compact and continuous operator pencil with a discrete set of singular values, denoted by Σ . Since L(ρ) is Fredlhom of index zero, σ ∈ Σ if, and only if, σ is an eigenvalue of L(ρ), i.e., if dim N[L(σ )] 1. (HR) R ∈ C(R × X 2 ; X 2 ) is compact on bounded sets and R(ρ, x, y) =0 (x,y)→(x0 ,0) (x − x0 , y)

lim

uniformly on compact intervals of R . (HP) The solutions of (5.1) satisfy the strong maximum principle in the sense that (ρ, x, y) ∈ R × P \ {0} × X

and F(ρ, x, y) = 0 imply x ∈ Int P ,

and

(ρ, x, y) ∈ R × X × P \ {0} and F(ρ, x, y) = 0 imply y ∈ Int P ,

where Int P stands for the interior of the cone P . Subsequently, the space X 2 is viewed as an ordered Banach space with positive cone P 2 , and, given any ordered Banach space E with positive cone W , and e1 , e2 ∈ E, we write e1 > e2 if e1 − e2 ∈ W \ {0}, and e1 ≫ e2 if e1 − e2 ∈ Int W . As Int P 2 = Int P × Int P , it is said that (ρ, x, y) is a positive solution of (5.1), if (ρ, x, y) is a solution of (5.1) with (x, y) > 0 (x 0, y 0 and (x, y) = (0, 0)). Thanks to Hypothesis (HP), any positive solution (ρ, x, y) of (5.1) must have one of the following forms: either x ≫ 0 and y ≫ 0— strongly positive, or x ≫ 0 and y = 0, or x = 0 and y ≫ 0—semi-trivial positive solutions. Under Hypotheses (HL) and (HR), F(ρ, x0 , 0) = 0 for each ρ ∈ R,

(5.2)

and, due to Hypothesis (HP), x0 ≫ 0, since x0 > 0. Moreover, since L(ρ) is a linear isomorphism for any ρ ∈ R \ Σ, the fixed point index Ind 0, K(ρ)

is well defined—the topological degree of L(ρ) in any bounded open set containing 0. Thus, the following crossing number C : Σ → {−1, 0, 1} can be introduced C(σ ) :=

1 lim Ind 0, K(σ + ε) − Ind 0, K(σ − ε) , 2 ε↓0

σ ∈ Σ.

(5.3)

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Note that C(σ ) = 0 if, and only if, Ind (0, K(ρ)) changes as ρ crosses σ , and that this occurs if, and only if, Ind ((x0 , 0), F(ρ, ·, ·)) changes as ρ crosses σ . Our main result concerns the bounded components of strongly positive solutions of (5.1) emanating from the curve (ρ, x, y) = (ρ, x0 , 0) at a singular value ρ0 ∈ Σ with— classical—geometric multiplicity one and C(ρ0 ) ∈ {−1, 1}. By a component of strongly positive solutions of (5.1) it is meant a maximal (for the inclusion) relatively closed and connected subset of the set of strongly positive solutions of (5.1)—in R × Int P 2 . Thanks to [19, Theorem 6.2.1], Eq. (5.1) possesses a component emanating from (ρ, x, y) = (ρ, x0 , 0) at ρ0 if C(ρ0 ) ∈ {−1, 1}. Such a component will be subsequently denoted by C0 . Throughout the remaining of this section, we shall denote by Px and Py the projection operators Px (x, y) = x,

Py (x, y) = y,

(x, y) ∈ X 2 .

(5.4)

The main abstract result of this section can now be stated as follows. T HEOREM 5.1. Suppose ρ0 ∈ Σ satisfies C(ρ0 ) = 0, N L(ρ0 ) = span (ϕ0x , ϕ0y ) ,

ϕ0y ∈ P \ {0},

(5.5)

and, for each x ∈ X, Py K(ρ0 )(x, ·) is strongly positive, in the sense that

Then,

Py K(ρ0 )(x, ·) P \ {0} ⊂ Int P . spr Py K(ρ0 )(ϕ0x , ·) = 1

(5.6)

(5.7)

and there exists a component CP0 of C0 ∩ [R × (Int P )2 ] such that (ρ0 , x0 , 0) ∈ C¯ P0 . Suppose, in addition, that CP0 is bounded in R × X 2 and that spr Py K(ρ0 )(x, ·) = 1 for each x ∈ X.

(5.8)

Then, some of the following alternatives occurs: A1. There exists (ρ1 , x1 ) ∈ (R × P ) \ {(ρ0 , x0 )} such that (ρ1 , x1 , 0) ∈ C¯ P0 . In such case, thanks to (HP), x1 ≫ 0 if x1 > 0. A2. There exists (ρ1 , y1 ) ∈ R × P such that (ρ1 , 0, y1 ) ∈ C¯ P0 . In such case, thanks to (HP), y1 ≫ 0 if y1 > 0. Furthermore, alternative A2 occurs if (ρ, x, 0) ∈ F−1 (0) implies x = x0 , and ρ0 is the unique value of ρ for which one is an eigenvalue of Py K(ρ)(x0 , ·) to a positive eigenvector.


P ROOF. The set of non-trivial solutions of (5.1) is defined through S := F−1 (0, 0) \ (R \ Σ) × (x0 , 0) .

395

(5.9)

Note that (ρ, x, y) ∈ S if F(ρ, x, y) = 0 with (x, y) = (x0 , 0), or (ρ, x, y) = (ρ, x0 , 0) with ρ ∈ Σ. Since C(ρ0 ) = 0, thanks to [19, Theorem 6.2.1] there exists a component of S, denoted by C0 , such that (ρ0 , x0 , 0) ∈ C0 . Subsequently, we suppose that ϕ0 := (ϕ0x , ϕ0y ) ∈ X × Int P has been normalized so that

ϕ0 X2 = 1. It should be noted that, thanks to (HL), K(ρ0 )ϕ0 = ϕ0 and, hence, Py K(ρ0 )(ϕ0x , ϕ0y ) = ϕ0y . Thus, it follows from (5.5) and (5.6) that ϕ0y ≫ 0. Moreover, thanks to (5.6), (5.7) is a consequence from Krein–Rutman theorem, since the spectral radius is the unique real eigenvalue associated with it there is a positive eigenvector. Now, let Z be a closed subspace of X 2 such that X 2 = N L(ρ0 ) ⊕ Z.

Thanks to Hahn–Banach’s theorem, there exists ∗ ∗ ϕ0∗ := ϕ0x , ϕ0y ∈ X ′ × X ′ for which

$ % Z = (x, y) ∈ X 2 : ϕ0∗ , (x, y) = 0 ,

$ ∗ % ϕ0 , ϕ0 = 1,

where ·, · stands for the duality between X 2 and X ′ × X ′ . Now, adapting the theory developed by P.H. Rabinowitz [31], for each η ∈ (0, 1) and sufficiently small ε > 0 we set Qε,η := (ρ, x, y) ∈ R × X 2 : |ρ − ρ0 | < ε, $ ∗ % ϕ , (x − x0 , y) > η(x − x0 , y) . 0

Since the mapping

$ % (x, y) → ϕ0∗ , (x − x0 , y) − η(x − x0 , y)

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is continuous, Qε,η is an open subset of R × X 2 consisting of the two disjoint components − Q+ ε,η and Qε,η defined through 2 Q+ ε,η := (ρ, x, y) ∈ R × X : |ρ − ρ0 | < ε, $ ∗ % ϕ0 , (x − x0 , y) > η(x − x0 , y) , 2 Q− ε,η := (ρ, x, y) ∈ R × X : |ρ − ρ0 | < ε, $ ∗ % ϕ0 , (x − x0 , y) < −η(x − x0 , y) .

The following result collects the main consequences from [19, Theorem 6.2.1, Lemma 6.4.1, Proposition 6.4.2]; it is entirely attributable to P.H. Rabinowitz [31]. T HEOREM 5.2. For each sufficiently small δ > 0, C0 ∩ Bδ (ρ0 , x0 , 0) ⊂ Qε,η ∪ (ρ0 , x0 , 0)

and each of the sets

S \ Q− and S \ Q+ ε,η ∩ Bδ (ρ0 , x0 , 0) ε,η ∩ Bδ (ρ0 , x0 , 0)

− contains a component, denoted by C+ 0 and C0 , respectively, such that − (ρ0 , x0 , 0) ∈ C+ 0 ∩ C0

and − C0 ∩ Bδ (ρ0 , x0 , 0) = C+ 0 ∪ C0 ∩ Bδ (ρ0 , x0 , 0).

(5.10)

Moreover, for each

(ρ, x, y) ∈ C0 \ (ρ0 , x0 , 0) ∩ Bδ (ρ0 , x0 , 0),

there exists a unique (s, x, ˜ y) ˜ ∈ R × Z such that ρ = ρ(s) and

(x, y) = (x0 , 0) + sϕ0 + x, ˜ y˜ = x0 + sϕ0x + x, ˜ sϕ0y + y˜

(5.11)

with |s| > η (x − x0 , y) . Actually, ρ = ρ0 + o(1) and Note that if

x, ˜ y˜ = o(s),

(ρ, x, y) ∈ C+ 0 ∩ Bδ (ρ0 , x0 , 0),

as s → 0.

(x, y) = (x0 , 0),

(5.12)


397

then (5.11) holds with s > η (x − x0 , y) > 0 and, hence, ˜ s −1 y = ϕ0y + s −1 y. Thus, due to (5.12), for sufficiently small s > 0 we have that s −1 y ∈ Int P , since ϕ0y ≫ 0, and, hence, y ≫ 0. The fact that x ≫ 0 is an easy consequence from (5.12) and the fact that x0 ≫ 0. Therefore, for any sufficiently small δ > 0 we have that + C0 \ (ρ0 , x0 , 0) ∩ Bδ (ρ0 , x0 , 0) ⊂ R × Int P 2 .

(5.13)

This shows the existence of the component CP0 . Actually, CP0 is the maximal sub-continuum 2 of C+ 0 in R × Int P such that (ρ0 , x0 , 0) ∈ C¯ P0 . If CP0 is unbounded in R × X 2 the proof is concluded. So, for the remaining of the proof we will assume that CP0 is bounded. The following result, which is [19, Theorem 6.4.3], provides us with an updated version of the very celebrated unilateral theorem of P.H. Rabinowitz [31, Theorem 1.27] which is necessary to conclude the proof of Theorem 5.1. It should be noted that [31, Theorem 1.27] is wrong as originally stated (cf. the detailed discussion carried out in [19, p. 180] and the counterexample of E.N. Dancer [9]). T HEOREM 5.3. The component C+ 0 satisfies some of the following alternatives: 2. 1. C+ is unbounded in R × X 0 2. There exists ρ1 ∈ Σ \ {ρ0 } such that (ρ1 , x0 , 0) ∈ C+ 0. 3. There exists (ρ, x, y) ∈ C+ such that 0 (ρ, x − x0 , y) ∈ R × Z \ {0} .

Now, we shall prove that

X 2 = N L(ρ0 ) ⊕ R L(ρ0 ) .

(5.14)

/ Since L(ρ0 ) is Fredholm of index zero, to show (5.14) it suffices to prove that ϕ0 ∈ R[L(ρ0 )]. This will be accomplished by contradiction. Suppose, there exists (x, y) ∈ X 2 such that L(ρ0 )(x, y) = (x, y) − K(ρ0 )(x, y) = ϕ0 = (ϕ0x , ϕ0y ). Then, y − Py K(ρ0 )(x, y) = ϕ0y ≫ 0.

(5.15)

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Note that, thanks to (HL) and (5.6), the map y → Py K(ρ0 )(x, y) defines a linear compact strongly order preserving operator. Moreover, by construction, Py K(ρ0 )(ϕ0x , ϕ0y ) = ϕ0y and, due to (5.8), spr Py K(ρ0 )(x, ·) = 1. Let ψx ≫ 0 denote the principal eigenfunction associated to Py K(ρ0 )(x, ·). Then, thanks to (5.15), for each β > 0 we have that y + βψx − Py K(ρ0 )(x, y + βψx ) = ϕ0y . On the other hand, since lim β −1 y + ψx = ψx ≫ 0,

β↑∞

it is apparent that, for each sufficiently large β > 0, one has that y + βψx ≫ 0 provides us with a positive solution of (5.15). Thanks to H. Amann [4, Theorem 3.2], this is impossible. This contradiction concludes the proof of (5.14). Consequently, in order to apply Theorem 5.3, we can make the special choice Z = R L(ρ0 ) ,

(5.16)

which will be maintained throughout the rest of the proof. Since CP0 ⊂ C+ 0 , some of the following alternatives occurs: either

or

CP0 = C+ 0 \ (ρ0 , x0 , 0) ,

CP0 is a proper subset of C+ 0 \ (ρ0 , x0 , 0) .

(5.17)

(5.18)

Suppose (5.17). Then, C¯ P0 = C+ 0 satisfies some of the alternatives of Theorem 5.3. Alternative 1 cannot be satisfied, since C¯ P0 is compact. Suppose alternative 3 occurs. Then, thanks to the choice (5.16), there exists 2 ¯P (ρ, x, y) ∈ C+ 0 = C0 ⊂ R × P


399

such that (ρ, x − x0 , y) ∈ R × R L(ρ0 ) ,

y = 0.

Since (ρ, x, y) ∈ R × P 2 with y = 0, necessarily y > 0 and, consequently, y ≫ 0, by (HP). Thus, there exists (x, ˜ y) ˜ ∈ X 2 such that L(ρ0 )(x, ˜ y) ˜ = (x, ˜ y) ˜ − K(ρ0 )(x, ˜ y) ˜ = (x − x0 , y) and, taking projections, y˜ − Py K(ρ0 ) x, ˜ y˜ = y ≫ 0.

Arguing as above, this is impossible, because, due to (5.8), spr Py K(ρ0 )(x, ˜ ·) = 1. Thus, alternative 2 of Theorem 5.3 must be satisfied. Consequently, there exists ρ1 ∈ Σ \ {ρ0 } such that ¯P (ρ1 , x0 , 0) ∈ C+ 0 = C0 and, therefore, alternative A1 of the theorem is satisfied. Now, suppose (5.18), instead of (5.17). Then, since P C+ 0 ∩ Bδ (ρ0 , x0 , 0) = C0 ∩ Bδ (ρ0 , x0 , 0) ∪ (ρ0 , x0 , 0)

for each sufficiently small δ > 0, fixing one of these δ’s, there exists (ρ1 , x1 , y1 ) ∈ / Bδ (ρ0 , x0 , 0)

(5.19)

such that 2 (ρ1 , x1 , y1 ) ∈ C+ ∩ ∂CP0 , 0 ∩ R × ∂P

where, given any set U , ∂U stands for the boundary of U . Then, F(ρ1 , x1 , y1 ) = 0

and (x1 , y1 ) ∈ P 2 .

If x1 > 0 and y1 > 0, then, due to (HP), x1 ≫ 0 and y1 ≫ 0, which is impossible, since (x1 , y1 ) ∈ ∂P 2 . Thus, either x1 = 0, or y1 = 0. Suppose y1 = 0. Then, thanks to (5.19), (ρ1 , x1 ) = (ρ0 , x0 ), and, therefore, alternative A1 is satisfied again. Obviously, if x1 = 0, then the alternative A2 is satisfied. Finally, suppose that (ρ, x, 0) ∈ F−1 (0) implies x = x0 , and ρ0 is the unique value of ρ for which one is an eigenvalue of Py K(ρ)(x0 , ·) to a positive eigenvector. To conclude

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J. López-Gómez

the proof of the theorem we proceed by contradiction. Assume alternative A1 is satisfied. Then, there exists (ρ1 , x1 ) ∈ (R × P ) \ {(ρ0 , x0 )} such that (ρ1 , x1 , 0) ∈ C¯ P0 . Thus, x1 = x0 , since (ρ1 , x1 , 0) ∈ F−1 (0), and, hence, ρ1 = ρ0 .

(5.20)

Let {(γn , un , vn )}n1 be any subsequence of CP0 such that lim (γn , un , vn ) = (ρ1 , x0 , 0).

n→∞

(5.21)

Then, for each n 1, vn ≫ 0, and, setting, ψn :=

vn ,

vn

we find from F(γn , un , vn ) = 0 that Py R(γn , un , vn )

vn

Py R(γn , un , vn ) . = Py K(ρ1 )(un , ψn ) + Py K(γn ) − K(ρ1 ) (un , ψn ) −

vn

ψn = Py K(γn )(un , ψn ) −

As {(un , ψn )}n1 is bounded, since we are assuming that CP0 is bounded, we have lim Py K(γn ) − K(ρ1 ) (un , ψn ) = 0, n→∞

by the continuity of K(ρ) in ρ. Moreover, thanks to (5.21), it follows from (HR) that Py R(γn , un , vn ) = 0. n→∞

vn

lim

Thus, for each n 1, there exists wn ∈ X such that ψn = Py K(ρ1 )(x0 , ψn ) + wn with limn→∞ wn = 0. Consequently, by compactness, there exists a subsequence of {ψn }n1 , again labeled by n, for which the limit Ψ := lim ψn ∈ X n→∞

exists and it satisfies Ψ = Py K(ρ1 )(x0 , Ψ ).

(5.22)

Necessarily Ψ ∈ P and Ψ = 1. Thus, Ψ > 0 and, hence, Ψ provides us with a positive eigenvector of Py K(ρ1 )(x0 , ·) associated with the eigenvalue 1. By our assumptions, this is impossible, unless ρ1 = ρ0 , which contradicts (5.20). This concludes the proof.


401

5.2. The existence of coexistence states in the general case Subsequently, we fix λ > 0 and consider µ as the main bifurcation parameter. Also, X := CT will be regarded as an ordered Banach space by its cone of non-negative functions, P . Note that P is normal, since every order interval is bounded. Also, note that, given any constant M > 0—to be chosen later—(u, v) ∈ CT1 × CT1 is a solution of (1.2) if and only if, (u, v) ∈ CT × CT

and F(µ, u, v) = 0,

(5.23)

where F : R × CT × CT → CT × CT is the operator defined by F(µ, u, v) :=

8

9 u − RM (λℓ + M)u − au2 − buv v − RM (µm + M)v − dv 2 − cuv

(5.24)

and RM stands for the operator introduced in (2.10), RM

d +M := J dt

−1

: CT → CT .

Thanks to Proposition 2.1, RM is compact and strongly order preserving. Moreover, for each µ ∈ R we have that F(µ, θ[λℓ,a] , 0) = 0 and, hence, since F is real analytic, the general assumptions (HL) and (HR) of Section 5.1 are satisfied by choosing (ρ, x0 , 0) := (µ, θ[λℓ,a] , 0),

µ ∈ R.

(5.25)

Moreover, if F(µ, u, v) = 0 with u(t0 ) > 0 for some t0 ∈ R, then u(t) = e

t

t0 (λℓ−au−bv)

u(t0 ) > 0

for each t ∈ R, since u′ = (λℓ − au − bv)u, and, hence, u ≫ 0. Similarly, v ≫ 0 if it is somewhere positive. Therefore, F satisfies Hypothesis (HP) as well.

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Maintaining the notations introduced in Section 5.1, for the choice (5.25) we have that the linearization L(µ) := D(u,v) F(µ, θ[λℓ,a] , 0) is given, for each (u, v) ∈ CT × CT , through

9 8 u − R (λℓ + M − 2aθ M [λℓ,a] )u − bθ[λℓ,a] v u L(µ) := v v − RM (µm + M − cθ[λℓ,a] )v

(5.26)

and, therefore,

9 8 R (λℓ + M − 2aθ M [λℓ,a] )u − bθ[λℓ,a] v u K(µ) . := v RM (µm + M − cθ[λℓ,a] )v

Suppose (u, v) ∈ N[L(µ)] for some µ ∈ R and (u, v) = (0, 0). Then, u, v ∈ CT1 , and

u′ = (λℓ − 2aθ[λℓ,a] )u − bθ[λℓ,a] v, v ′ = (µm − cθ[λℓ,a] )v.

(5.27)

Suppose v = 0. Then, u = 0 and the second equation of (5.27) holds true. Moreover, the first one reduces to u′ = (λℓ − 2aθ[λℓ,a] )u.

(5.28)

Thanks to (2.28), we have that

T

(λℓ − aθ[λℓ,a] ) = 0

0

and, hence,

0

T

(λℓ − 2aθ[λℓ,a] ) = −

0

T

a(t)θ[λℓ,a] (t) dt < 0.

(5.29)

Therefore, (5.28) cannot admit a non-trivial T -periodic solution. This contradiction shows that, necessarily, v = 0, which implies µ = µ0 :=

1 T

0

T


(5.30)

since m ˆ = 1. Actually, in this case, there exists a constant A = 0 such that v = Aϕv ,

ϕv (t) := e

t

0 (µ0 m−cθ[λℓ,a] )

, t ∈ R.

(5.31)


403

Thanks to (5.29), it follows from Proposition 2.1 that the problem u′ = (λℓ − 2aθ[λℓ,a] )u − bθ[λℓ,a] ϕv ,

u ∈ CT1 ,

(5.32)

possesses a unique solution. Namely, ϕu := −R2aθ[λℓ,a] −λℓ (bθ[λℓ,a] ϕv ).

(5.33)

Consequently, L(µ) is an isomorphism if µ = µ0 , whereas N L(µ0 ) = span (ϕu , ϕv ) .

(5.34)

In particular, using the notations introduced in Section 5.1, this entails Σ = {µ0 }. Note that, since ϕv ≫ 0, condition (5.5) is satisfied. Also, for each u, v ∈ X = CT , we have that Pv K(µ0 )(u, v) = RM (µ0 m + M − cθ[λℓ,a] )v ,

(5.35)

which is independent of u. Now, choosing M sufficiently large so that µ0 m + M − cθ[λℓ,a] ≫ 0, it follows from Proposition 2.1 that Pv K(µ0 )(u, v) ≫ 0 if v > 0. Therefore, (5.6) and (5.7) are satisfied. Actually, since Pv K(µ0 )(u, ·) is constant in u, condition (5.8) is as well satisfied. Furthermore, since (θ[λℓ,a] , 0) is the unique semi-trivial solution of (1.2) for each µ ∈ R and 1 cannot be an eigenvalue of Pv K(µ)(0, ·), unless µ = µ0 —we have already seen it in the proof of (5.34)—to show that all assumptions of Theorem 5.1 are satisfied it remains to prove that C(µ0 ) = 0. To prove it, one can argue as follows. Note that L(µ) is analytic in µ and that, for each u, v ∈ CT , we have dL (µ)(u, v) = 0, −RM (mv) . dµ We now show that the following holds: dL (µ0 )(ϕu , ϕv ) = 0, −RM (mϕv ) ∈ / R L(µ0 ) . dµ

(5.36)

Indeed, if (5.36) is not true, then there exists v ∈ CT such that −RM (mϕv ) = v − RM (µ0 m + M − cθ[λℓ,a] )v .

Equivalently,

v ′ = (µ0 m − θ[λℓ,a] )v − mϕv ,

v ∈ CT .

(5.37)

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J. López-Gómez

Thanks to (5.30), it follows from Proposition 2.1(d) that (5.37) does not admit a solution, since mϕv > 0. This contradiction shows (5.36). It should be noted that (5.36) is the classical transversality condition of M.G. Crandall and P.H. Rabinowitz [6]. Since L(µ0 ) is Fredholm of index zero, because it is a compact perturbation of the identity, it is apparent from (5.36) that dL (µ0 ) N L(µ0 ) ⊕ R L(µ0 ) = CT × CT . dµ

(5.38)

Thus, µ0 is a 1-transversal eigenvalue of the analytic family L(µ), µ ∈ R, in the sense of [19, Definition 4.2.1]. Hence, the algebraic multiplicity defined there in equals one, i.e., χ L(µ); µ0 = 1,

and, therefore, thanks to [19, Theorem 5.3.1], µ0 is a pole of order one of the resolvent operator L−1 (µ), µ = µ0 . Consequently, thanks to [19, Theorem 5.6.2], the crossing number C(µ0 ) defined in (5.3) satisfies C(µ0 ) ∈ {−1, 1}. Therefore, Theorem 5.1 provides us with the following existence result. T HEOREM 5.4. Fix λ > 0 and consider µ as the main bifurcation parameter. Then, Problem (1.2) possesses a component of coexistence states Cλµ ⊂ R × Int P × Int P such that (µ0 , θ[λℓ,a] , 0) ∈ C¯ λµ ,

(5.39)

where µ0 is defined through (5.30). Moreover, if Cλµ is bounded, then there exists µ∗ > 0 such that λ=

1 T

0

T

b(t)θ[µ∗ m,d] (t) dt

(5.40)

and (µ∗ , 0, θ[µ∗ m,d] ) ∈ C¯ λµ .

(5.41)

Therefore, Cλµ links the semi-trivial states (µ0 , θ[λℓ,a] , 0) and (µ∗ , 0, θ[µ∗ m,d] ) if it is bounded.


405

P ROOF. The existence of Cλµ bifurcating from the curve (µ, u, v) = (µ, θ[λℓ,a] , 0) at µ = µ0 is an immediate consequence from Theorem 5.1. Suppose Cλµ is bounded. Then, it satisfies alternative A2 of Theorem 5.1 and, hence, there exists (µ∗ , v∗ ) ∈ R × P such that (µ∗ , 0, v∗ ) ∈ C¯ λµ . Thus, there exists a sequence of coexistence states of (1.2), say {(µn , un , vn )}n1 , such that lim (µn , un , vn ) = (µ∗ , 0, v∗ ).

n→∞

For each n 1, we have that un = RM (λℓ + M)un − au2n − bun vn .

Thus, setting

Un :=

un ,

un CT

n 1,

gives Un = RM (λℓ + M)Un − aun Un − bvn Un ,

n 1.

(5.42)

Since {(λℓ + M)Un − aun Un − bvn Un }n1 is bounded in CT and RM is compact, there exists a subsequence of Un , labeled again by n, such that lim Un = Φ.

n→∞

Necessarily, Φ CT = 1, and, hence, Φ > 0, since un ≫ 0, n 1. Moreover, passing to the limit as n → ∞ in (5.42), we find that Φ = RM (λℓ + M − bv∗ )Φ .

Thus, Φ ∈ CT1 , Φ > 0, and

Φ ′ = (λℓ − bv∗ )Φ.

(5.43)

Suppose v∗ = 0, then, we find from (5.43) that λℓˆ = λ = 0, which is impossible, since we are assuming λ > 0. Thus, v∗ > 0. Actually, since (µ∗ , 0, v∗ ) solves (1.2), necessarily µ∗ > 0

and v∗ = θ[µ∗ m,d] ≫ 0.

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J. López-Gómez

Consequently, (5.43) becomes into Φ ′ = (λℓ − bθ[µ∗ m,d] )Φ,

(5.44)

and, therefore, 1 λ= T

T

b(t)θ[µ∗ m,d] (t) dt,

0

which concludes the proof of the theorem.

By symmetry, if µ > 0 is fixed and λ ∈ R is regarded as the main bifurcation parameter, then the following result is satisfied. T HEOREM 5.5. Fix µ > 0 and consider λ as the main bifurcation parameter. Then, Problem (1.2) possesses a component of coexistence states µ

Cλ ⊂ R × Int P × Int P such that µ (λ0 , 0, θ[µm,d] ) ∈ C¯ λ ,

1 λ0 := T

T 0


(5.45)

µ

Moreover, if Cλ is bounded, then there exists λ∗ > 0 such that µ=

1 T

0

T

c(t)θ[λ∗ ℓ,a] (t) dt

(5.46)

and µ (λ∗ , θ[λ∗ ℓ,a] , 0) ∈ C¯ λ .

(5.47)

µ

Therefore, Cλ links the semi-trivial states (λ0 , 0, θ[µm,d] ) and (λ∗ , θ[λ∗ ℓ,a] , 0) if it is bounded.

µ

5.3. Local structure of Cλµ and Cλ at (µ0 , θ[λℓ,a] , 0) and (λ0 , 0, θ[µm,d] ) The following result shows that, for each λ > 0, Cλµ consists of a real analytic curve of coexistence states of (1.2) in a neighborhood of (µ, u, v) = (µ0 , θ[λℓ,a] , 0).


407

Although this is a consequence from the celebrated theorem of M.G. Crandall and P.H. Rabinowitz [6], we shall give a self-contained proof—whose uniqueness part is based on Theorem 5.2—in order to calculate the bifurcation direction of the curve of coexistence states. Throughout this section, all notation introduced in Section 5.2 will be maintained. T HEOREM 5.6. Fix λ > 0 and regard to µ ∈ R as the main bifurcation parameter. Then, there exist ε > 0 and two real analytic maps (u1 , v1 ) : (−ε, ε) → R L(µ0 ) × R L(µ0 ) ,

µ : (−ε, ε) → R, such that 1 T

µ(0) = µ0 =

T 0

c(t) θ[λℓ,a] (t) dt,

and, for each s ∈ (−ε, ε),

u1 (0), v1 (0) = (0, 0),

(5.48)

(5.49)

F µ(s), θ[λℓ,a] + s ϕu + u1 (s) , s ϕv + v1 (s) = 0,

(5.50)

where ϕv and ϕu are the functions defined by (5.31) and (5.33), respectively. Moreover, there exists δ > 0 such that, if Bδ0 stands for the ball of radius δ centered at (µ0 , θ[λℓ,a] , 0) ∈ R × CT × CT and, for each s ∈ (−ε, ε), we set

then

u(s), v(s) := θ[λℓ,a] + s ϕu + u1 (s) , s ϕv + v1 (s) , Cλµ ∩ Bδ0 =

Furthermore, 1 dµ (0) = ds T

(5.51)

µ(s), u(s), v(s) : 0 < s < ε ∩ Bδ0 .

0

T

(5.52)

c(t)ϕu (t) + d(t)ϕv (t) dt.

(5.53)

P ROOF. Consider the operator

G : R2 × R L(µ0 ) → CT × CT

defined, for each (s, µ, u1 , v1 ) ∈ R2 × R[L(µ0 )], by s −1 F µ, θ[λℓ,a] + s(ϕu + u1 ), s(ϕv + v1 ) , G(s, µ, u1 , v1 ) := D(u,v) F(µ, θ[λℓ,a] , 0)(ϕu + u1 , ϕv + v1 ),

if s = 0, if s = 0.

The operator G is real analytic and it satisfies G(0, µ0 , 0, 0) = D(u,v) F(µ0 , θ[λℓ,a] , 0)(ϕu , ϕv ) = L(µ0 )(ϕu , ϕv ) = (0, 0).

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J. López-Gómez

Moreover, for each (µ, u1 , v1 ) ∈ R × R[L(µ0 )],

D(µ,u1 ,v1 ) G(0, µ0 , 0, 0)(µ, u1 , v1 ) = lim h−1 G(0, µ0 + hµ, hu1 , hv1 ) h→0

= lim h−1 D(u,v) F(µ0 + hµ, θ[λℓ,a] , 0)(ϕu + hu1 , ϕv + hv1 ) h→0

= lim h−1 L(µ0 + hµ)(ϕu + hu1 , ϕv + hv1 ) h→0

= L(µ0 )(u1 , v1 ) + µ

dL (µ0 )(ϕu , ϕv ). dµ

Thanks to the proof of Theorem 5.1, we already know that N L(µ0 ) ⊕ R L(µ0 ) = CT × CT ,

though this easily follows from the fact that (ϕu , ϕv ) ∈ / R[L(µ0 )]. Therefore, L(µ0 )|R[L(µ0 )] : R L(µ0 ) → R L(µ0 )

is a linear isomorphism and, hence, it follows from (5.36) that D(µ,u1 ,v1 ) G(0, µ0 , 0, 0) : R × R L(µ0 ) → CT × CT

is a linear isomorphism as well. Consequently, thanks to the implicit function theorem, there exist ε > 0 and the real analytic maps (5.48), satisfying (5.49), such that, for each s ∈ (−ε, ε), G s, µ(s), u1 (s), v1 (s) = 0.

Moreover, if

G(s, µ, u1 , v1 ) = 0 for some (s, µ, u1 , v1 ) sufficiently close to (0, µ0 , 0, 0), then (s, µ, u1 , v1 ) = s, µ(s), u1 (s), v1 (s) .

It should be noted that, by the definition of G itself, for each s ∈ (−ε, ε), (5.50) is satisfied. Now, we will prove the uniqueness result. Thanks to Theorem 5.2, there exists δ > 0 such that, for each (µ, u, v) ∈ Cλµ \ (µ0 , θ[λℓ,a] , 0) ∩ Bδ ,

there exists a unique (s, u, ˜ v) ˜ ∈ R × R[L(µ0 )] such that µ = µ(s),

(u, v) = (θ[λℓ,a] , 0) + s(ϕu , ϕv ) + u, ˜ v˜ ,

(5.54)


with s > η (u − θ[λℓ,a] , v) > 0. Moreover, µ = µ0 + o(1) and u, ˜ v˜ = o(s)

as s → 0.

409

(5.55)

So, setting

U (s) := s −1 u(s) ˜ = o(1),

V (s) := s −1 v(s) ˜ = o(1),

we have that (U (s), V (s)) ∈ R[L(µ0 )] and F µ(s), θ[λℓ,a] + s ϕu + U (s) , s ϕs + V (s) = 0. Thus,

G s, µ(s), U (s), V (s) = 0

and, therefore, by the uniqueness obtained as an application of the implicit function theorem to G, if δ is taken sufficiently small, we have that U (s), V (s) = u1 (s), v1 (s) and, consequently,

(µ, u, v) = µ(s), u(s), v(s) ,

which concludes the proof of (5.52). To prove (5.53), consider the second equation of (5.50). Then, after division by s, gives dv1 (0) + O s 2 ds 2 2 dv1 dµ µ0 + s (0) + O s = RM (0) + O s m + M ϕv + s ds ds 2 2 dv1 (0) + O s − c θ[λℓ,a] + sϕu + O s 2 − ds ϕv + s ds 2 dv1 (0) + O s × ϕv + s . ds

ϕv + s

By definition,

ϕv = RM (µ0 m + M − cθ[λℓ,a] )ϕv .

Thus, dividing by s the previous identity, passing to the limit as s → 0, and rearranging terms yields to dv1 dµ dv1 2 (0) = RM (µ0 m + M − cθ[λℓ,a] ) (0) + (0)mϕv − dϕv − cϕu ϕv , ds ds ds

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J. López-Gómez

or, equivalently, dv1 dµ d dv1 (0) = (µ0 m − cθ[λℓ,a] ) (0) + (0)mϕv − dϕv2 − cϕu ϕv . dt ds ds ds Thus, thanks to Proposition 2.1(d),

T

e−

0

t

0 (µ0 m−cθ[λℓ,a] )

dµ (0)m(t)ϕv (t) − d(t)ϕv2 (t) − c(t)ϕu (t)ϕv (t) dt = 0, ds

and, hence, (5.31) entails

0

T

dµ (0)m(t) − d(t)ϕv (t) − c(t)ϕu (t) dt = 0. ds

Therefore,

1 dµ (0) = ds T

T

0

c(t)ϕu (t) + d(t)ϕv (t) dt,

since m ˆ = 1. This concludes the proof.

µ

By symmetry, for each µ > 0, Cλ consists of a real analytic curve of coexistence states of (1.2) in a neighborhood of (λ, u, v) = (λ0 , 0, θ[µm,d] ). Actually, setting λ0 :=

1 T

0

T

b(t)θ[µm,d] (t) dt,

ϕ˜u (t) := e

t

0 (λ0 ℓ−bθ[µm,d] )

,

t ∈ R,

(5.56)

and ϕ˜ v := −R2dθ[µm,d] −µm (cθ[µm,d] ϕ˜ u ),

(5.57)

there exists δ > 0 such that in the ball of radius δ > 0 centered at (λ0 , 0, θ[µm,d] ) the comµ ponent Cλ consists of a real analytic curve of the form (λ, u, v) = λ(s), s ϕ˜u + O(s) , θ[µm,d] + s ϕ˜ v + O(s) ,

s ∼ 0, s > 0,

where λ(0) = λ0 and

dλ 1 (0) = ds T

0

T

b(t)ϕ˜v (t) + a(t)ϕ˜ u (t) dt.

(5.58)


411

6. The symbiotic model (b < 0 and c < 0) In this section we analyze the structure of the set of coexistence states of (1.2) in the special case when b < 0 and c < 0. Our main result shows that, for each λ > 0 and µ > 0, µ the components of coexistence states of (1.2) constructed in Section 5, Cλ and Cλµ , are real analytic curves. These curves fiber a real analytic surface entirely formed by coexistence states and linking the corresponding surfaces of semi-trivial solutions along their curves of neutral stability. Also, the stability of the coexistence states along these curves is completely ascertained. It turns out that the stability of the coexistence states along these curves changes at any turning point along the curve, while it remains unchanged when an hysteresis point is passed by. Some of the results of this section are substantial improvements of some results of M.A. Krasnosel’skii [16]. The theory developed in this section can be viewed as a development of many ideas and results going back to [17].

6.1. Periodic systems of cooperative type In this section we study the linear periodic system u′ = αu + βv, v ′ = γ u + ρv,

(6.1)

where α, β, γ , ρ ∈ CT satisfy

0

T

α < 0,

T

ρ < 0,

β > 0,

γ > 0,

(6.2)

0

as well as its associated Cauchy problem  ′   u = αu + βv, v ′ = γ u + ρv,   u(0) = u0 , v(0) = v0 .

(6.3)

The next result is the key theorem from which most of the results of this section will follow. T HEOREM 6.1. Suppose (6.1) possesses a solution (u, v) ∈ CT1 × CT1 \ {(0, 0)}. Then, either u ≫ 0 and v ≫ 0, or else u ≪ 0 and v ≪ 0. Therefore, all the coexistence states of (1.2) must be ordered, in the sense that, for any pair of coexistence states, (u1 , v1 ) = (u2 , v2 ), either u1 ≫ u2 and v1 ≫ v2 , or u1 ≪ u2 and v1 ≪ v2 .

P ROOF. If u = 0, then v ′ = ρv, and it follows from Proposition 2.1 that v = 0. Thus, u = 0, since (u, v) = (0, 0). As the system is linear, without lost of generality we can assume that u(t) > 0 for some t ∈ R . If u ≫ 0, then γ u > 0 and, therefore, v = R−ρ (γ u) ≫ 0,

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J. López-Gómez

which concludes the proof of the first thesis of the theorem. To show that u ≫ 0 we will argue by contradiction. Suppose there are t0 < t1 such that u(t0 ) = u(t1 ) = 0 and u(t) > 0 for each t ∈ (t0 , t1 ).

(6.4)

Then, for each t ∈ R, we have that u(t) =

t t

e

α

τ

β(τ )v(τ ) dτ

(6.5)

t0

and v(t) = e

t

t0

ρ

v(t0 ) +

t t

e

τ

ρ

γ (τ )u(τ ) dτ.

(6.6)

t0

Suppose v(t0 ) 0. Then, thanks to (6.4) and (6.6), we find that, for each t ∈ [t0 , t1 ], v(t) e

t

t0

ρ

v(t0 ) 0,

since γ u 0. Thus, (6.4) and (6.5) imply 0 = u(t1 ) =

t1 t

e

τ

1

α

β(τ )v(τ ) dτ

t0

t0 +t1 2

e

t0

t τ

1

α

β(τ )v(τ ) dτ

t1 = exp t +t α 0

2

1

t0 +t1 2

t0

exp

t0 +t1 2

τ

t1 t0 + t1 > 0, = exp t +t α u 0 1 2 2

α β(τ )v(τ ) dτ

which is impossible. Hence, v(t0 ) < 0. So, there is δ > 0 such that t0 < t0 + δ < t1 , for which v(t) < 0 if t ∈ [t0 , t0 + δ]. Thus, we find from (6.5) that u(t) 0 for each t ∈ [t0 , t0 + δ], which contradicts (6.4). Therefore, necessarily u ≫ 0, which concludes the proof of the first statement. Now, suppose (u1 , v1 ) = (u2 , v2 ) are two coexistence states of (1.2). Then, (u2 − u1 )′ = λℓ(u2 − u1 ) − a(u2 + u1 )(u2 − u1 ) − bu2 v2 + bu1 v1 = λℓ − a(u2 + u1 ) − bv2 (u2 − u1 ) − bu1 (v2 − v1 ).

By symmetry,

(v2 − v1 )′ = µm − d(v2 + v1 ) − cu2 (v2 − v1 ) − cv1 (u2 − u1 ).


413

Thus, the pair (U, V ) := (u2 − u1 , v2 − v1 ) ∈ CT1 × CT1 satisfies

U ′ = λℓ − a(u2 + u1 ) − bv2 U − bu1 V , V ′ = µm − d(v2 + v1 ) − cu2 V − cv1 U.

Since u1 ≫ 0, v1 ≫ 0, b < 0 and c < 0, necessarily −bu1 > 0 and −cv1 > 0. Moreover, since u2 ≫ 0 and v2 ≫ 0 satisfy u′2 = λℓ − au2 − bv2 , u2 integrating in [0, T ] gives

T

(λℓ − au2 − bv2 ) = 0,

0

v2′ = µm − dv2 − cu2 , v2

T

(µm − dv2 − cu2 ) = 0.

0

(6.7)

Thus,

T

0

and

0

T

λℓ − a(u2 + u1 ) − bv2 = −

µm − d(v2 + v1 ) − cu2 = −

T

a(t)u1 (t) dt < 0

0

T

d(t)v1 (t) dt < 0.

0

Therefore, by the first part of the theorem, either U ≫ 0 and V ≫ 0, or U ≪ 0 and V ≪ 0, which concludes the proof. P ROPOSITION 6.2. Suppose (u, ¯ v) ¯ ∈ C 1 (R+ ) × C 1 (R+ ), R+ := [0, ∞), satisfy  ′ ¯   u¯ α u¯ + β v, ′ v¯ γ u¯ + ρ v, ¯   u(0) ¯ > 0, v(0) ¯ > 0.

(6.8)

Then, u(t) ¯ > 0 and v(t) ¯ > 0 for each t 0. If u0 + v0 > 0 and u0 v0 = 0, then there exists t0 > 0 such that the solution (u, v) of (6.3) satisfies u(t) > 0 and v(t) > 0 for each t t0 . P ROOF. Setting d := u¯ ′ − α u¯ − β v¯ 0,

δ := v¯ ′ − γ u¯ − ρ v¯ 0,

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and integrating the resulting system show that, for each t ∈ R+ , t t t α 0 u(t) ¯ = e u(0) e τ α β(τ )v(τ ¯ + ¯ ) + d(τ ) dτ

(6.9)

0

and

v(t) ¯ =e

t 0

ρ

v(0) ¯ +

0

t t

e

τ

ρ

γ (τ )u(τ ¯ ) + δ(τ ) dτ.

(6.10)

Now, suppose u(0) ¯ > 0 and v(0) ¯ > 0. Then, either u(t) ¯ > 0 for each t ∈ R+ , or there exists t ∗ such that u¯ t ∗ = 0 and u(t) ¯ > 0 for each t ∈ 0, t ∗ . (6.11) Suppose (6.11) occurs. Then, since u(0) ¯ > 0, v(0) ¯ > 0, β > 0 and d 0, it follows from (6.9) that there exists t˜ ∈ (0, t ∗ ) such that ¯ > 0 for each t ∈ 0, t˜ , v¯ t˜ = 0 and v(t)

which contradicts (6.10), since v(0) ¯ > 0 and γ 0, δ 0 and u¯ 0 in [0, t˜]. Therefore, u(t) ¯ > 0 for each t ∈ R+ and, thanks to (6.10), v(t) ¯ > 0 for each t ∈ R+ . This concludes the proof of the first part of the proposition. Now, suppose u0 > 0 and v0 = 0, and let (u, v) denote the unique solution of (6.3). Thanks to the first part of the proposition, for each ε > 0 the solution (uε , vε ) of (6.1) with initial data (uε (0), vε (0)) = (u0 , v0 + ε) satisfies uε (t) > 0 and vε (t) > 0 for each t 0. Thus, by continuous dependence with respect to the initial data, passing to the limit as ε ↓ 0 we find that u > 0 and v 0. Hence, for each t 0, t t t t α 0 u(t) = e u0 + e τ α β(τ )v(τ ) dτ e 0 α u0 > 0. 0

If v = 0 in R+ , then we find from the v-equation that γ u = 0 in R+ , which is impossible since γ > 0 and u ≫ 0. Thus, there exists t0 > 0 such that v(t0 ) > 0. Therefore, since u(t0 ) > 0, by applying the first part of this theorem, we find that u(t) > 0 and v(t) > 0 for each t t0 , which concludes the proof. Subsequently, we denote by U (t) the fundamental matrix of solutions of (6.1) such that U (0) = I := IR2 . Then, U (T ) provides us with the Poincaré map associated to (6.1). Thanks to Liouville’s formula, 0 < det U (T ) = e

T 0

(α+ρ)

< 1,

T since 0 (α + ρ) < 0. Thus, if we denote by ν1 and ν2 the two eigenvalues of U (T ), counting algebraic multiplicities, then 0 < ν1 ν2 < 1. Actually, the following result is satisfied.

(6.12)


415

T HEOREM 6.3. The characteristic multipliers of (6.1), ν1 and ν2 , are real and distinct, and satisfy (6.12). Moreover, if we order them so that 0 < ν1 < ν2 , then, 0 < ν1 < 1,

and

N U (T ) − ν1 I = span (x0 , y0 )

with x0 < 0 and y0 > 0,

N U (T ) − ν2 I = span (x0 , y0 )

with x0 > 0 and y0 > 0.

In particular, (6.1) is asymptotically stable if ν2 < 1, neutrally stable if ν2 = 1, and unstable if ν2 > 1. Furthermore, λ0 := −

1 Log ν2 T

provides us with the unique value of λ ∈ R for which the eigenvalue problem u′ = αu + βv + λu, v ′ = γ u + ρv + λv,

(6.13)

(6.14)

admits a solution (u, v) ∈ CT1 × CT1 with u ≫ 0 and v ≫ 0. P ROOF. Suppose u0 > 0, v0 > 0, and let (u(t), v(t)) denote the unique solution of (6.3). Then, thanks to Proposition 6.2, u(T ) > 0 and v(T ) > 0, and, hence, U (T ) sends the interior of the first quadrant of the plane into itself. Setting U (T ) =

u11 u21

u12 , u22

the invariance of the first quadrant entails uij 0 for each i, j ∈ {1, 2}. On the other hand, the eigenvalues of U (T ) (ν1 and ν2 ) are the roots of z2 − (u11 + u22 )z + u11 u22 − u12 u21 = 0, which are given through

where

√ 1 u11 + u22 ± - , 2 - := (u11 + u22 )2 − 4(u11 u22 − u12 u21 ) = (u11 − u22 )2 + 4u12 u21 0.

Thus, both are real. Moreover, since det U (T ) = u11 u22 − u12 u21 = ν1 ν2 > 0,

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necessarily u11 > 0,

u22 > 0,

ν1 + ν2 = u11 + u22 .

We now show that u12 > 0 and u21 > 0. Indeed, if u12 = 0, then {ν1 , ν2 } = {u11 , u22 } and, hence, N U (T ) − u22 I = span (0, 1) .

Consequently, the solution of (6.3) with initial data (0, 1), say (u, v), satisfies u(nT ) = 0 for each n 1, which contradicts the second part of Proposition 6.2. This contradiction shows that u12 > 0. Similarly, u21 > 0 follows. Thus, - > 0 and, therefore, ν1 = ν2 , say 0 < ν1 < ν2 . Now, note that min{u11 , u22 } < ν2 =

√ 1 u11 + u22 + - . 2

In case u11 = min{u11 , u22 }, (u12 /(ν2 − u11 ), 1) provides us with an eigenvector of U (T ) associated to ν2 , while, in case u22 = min{u11 , u22 }, (1, u21 /(ν2 − u22 )) provides us with an eigenvector of U (T ) associated to ν2 . In both situations the two components of the eigenvector are positive. Similarly, in case u11 = min{u11 , u22 }, (1, u21 /(ν1 − u22 )) is an eigenvector of U (T ) associated to ν1 whose second component is negative, since ν1 = u11 + u22 − ν2 < u22 . By symmetry, in case u22 = min{u11 , u22 }, (u12 /(ν1 − u11 ), 1) is an eigenvector of U (T ) associated to ν1 whose second component is negative. Therefore, the eigenvector of U (T ) associated to ν2 can be chosen in the interior of the first quadrant, while the eigenvector associated to ν1 can be chosen in the interior of the second quadrant. Now, note that the change of variable (u, v) = eλt (x, y) transforms (6.14) into

x ′ = αx + βy, y ′ = γ x + ρy.

Thus, for any (u0 , v0 ) ∈ R2 , the unique solution of (6.14) satisfying u(0), v(0) = (u0 , v0 )


417

is given through u(t), v(t) = eλt U (t)(u0 , v0 ).

Therefore, the Poincaré map of (6.14) is given by PT := eλT U (T ) and, consequently, the multipliers of (6.14) are eλT νj , j ∈ {1, 2}. Thus, the eigenvalue problem (6.14) possesses a T -periodic solution if, and only, if 1 1 λ ∈ − Log ν1 , − Log ν2 . T T By the analysis already done, the unique value of λ providing us with a T -periodic solution having both components positive is the one given by (6.13), as the other eigenvalue provides us with a T -periodic solution whose components have contrary sign. This concludes the proof. Subsequently, the value λ0 defined by (6.13) will be called the principal eigenvalue of (6.14). It should be noted that (6.1) is asymptotically stable if, and only if λ0 > 0, whereas it is unstable if, and only if, λ0 < 0. The following result provides us with an extremely useful criterion for ascertaining the stability of (6.1). T HEOREM 6.4. The following properties are satisfied: ¯ v) ¯ ∈ CT1 × CT1 with (a) System (6.1) is stable (ν2 < 1) if, and only if, there exists (u, u¯ ≫ 0 and v¯ ≫ 0 such that ¯ u¯ ′ α u¯ + β v, (6.15) ′ v¯ γ u¯ + ρ v, ¯ with some of these inequalities strict. (b) System (6.1) is unstable (ν2 > 1) if, and only if, there exits (u, v) ∈ CT1 × CT1 with u ≫ 0 and v ≫ 0 such that

u′ αu + βv, v ′ γ u + ρv,

(6.16)

with some of these inequalities strict. P ROOF. First we will prove part (a). If ν2 < 1, then the principal eigenvalue of (6.14) is positive. Indeed, 1 λ0 = − Log ν2 > 0 T

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and, hence, any T -periodic strongly positive solution associated to λ0 provides us with a strict supersolution of (6.1). This shows the necessity of the existence of the supersolution. To show the sufficiency of this condition, suppose there exists (u, ¯ v) ¯ ∈ CT1 × CT1 with u¯ ≫ 0 and v¯ ≫ 0 satisfying (6.15) with some of the inequalities strict. Now, pick (u0 , v0 ) ∈ N U (T ) − ν2 I with u0 > 0 and v0 > 0, and let (u(t), v(t)) denote the unique solution of (6.3). Then, u(nT ), v(nT ) = ν2n (u0 , v0 ), n 0. Now, pick R > 0 satisfying 0 < u0 < R u(0), ¯

0 < v0 < R v(0), ¯

and consider the auxiliary function x := R u¯ − u,

y := R v¯ − v.

Then, by construction,  ′   x αx + βy, y ′ γ x + ρy,   x(0) > 0, y(0) > 0,

(6.17)

and, hence, thanks to Proposition 6.2, x(t) > 0 and y(t) > 0 for each t ∈ R+ . Equivalently, 0 < u(t) < R u(t) ¯

and 0 < v(t) < R v(t) ¯ for each t ∈ R+ ,

since u0 > 0 and v0 > 0. In particular, the sequence u(nT ), v(nT ) = ν2n (u0 , v0 ), n 0,

is bounded above and, therefore, ν2 1. Suppose ν2 = 1. Then, λ0 = 0 and, thanks to Theorem 6.3, (6.1) possesses a T -solution (p, q) with p ≫ 0 and q ≫ 0. On the other hand, setting d := u¯ ′ − α u¯ − β v, ¯

δ := v¯ ′ − γ u¯ − ρ v, ¯

we have that d 0, δ 0, d + δ > 0, and u¯ ′ = α u¯ + β v¯ + d, v¯ ′ = γ u¯ + ρ v¯ + δ.


419

Consequently, for each ξ ∈ R, the pair (uξ , vξ ) := (u¯ − ξp, v¯ − ξ q) provides us with a T -periodic solution of u′ = αu + βv + d, v ′ = γ u + ρv + δ.

(6.18)

Since u¯ ≫ 0 and v¯ ≫ 0, we have that uξ ≫ 0 and vξ ≫ 0 for sufficiently small ξ > 0. Moreover, since p ≫ 0 and q ≫ 0, we have that uξ ≪ 0 and vξ ≪ 0 for sufficiently large ξ > 0. Thus, there exists ξ > 0 such that uξ 0, vξ 0 and, for some t0 ∈ R, either uξ (t0 ) = 0, or vξ (t0 ) = 0. Without lost of generality we can assume that uξ (t0 ) = 0. Then, for each t t0 , we have that t t uξ (t) = (6.19) e τ α βvξ (τ ) + d(τ ) dτ. t0

If βvξ + d > 0, then, we find from (6.19) that uξ (t0 + nT ) > 0 for each n 2, which contradicts the periodicity of uξ , since uξ (t0 ) = 0. Thus, βvξ = d = 0,

(6.20)

and, thanks again to (6.19), uξ = 0. Thus, substituting into the v-equation of (6.18) shows that vξ′ = ρvξ + δ. Necessarily, vξ = R−ρ (δ) ≫ 0, since δ > 0, and, therefore, βvξ > 0, which contradicts (6.20) and shows ν2 < 1. This concludes the proof of part (a). Now, we will prove part (b). Suppose ν2 > 1. Then, 1 λ0 = − Log ν2 < 0 T and, hence, any T -periodic strongly positive solution of (6.14) associated to λ0 provides us with a strict subsolution of (6.1). To show the converse, let (u, v) ∈ CT1 × CT1 with u ≫ 0 and v ≫ 0 satisfying (6.16) with some of the inequalities strict. Pick (u0 , v0 ) ∈ N U (T ) − ν2 I

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with u0 > 0 and v0 > 0, and let (u(t), v(t)) denote the unique solution of (6.3). Then, u(nT ), v(nT ) = ν2n (u0 , v0 ),

n 0.

(6.21)

Now, for each ε > 0 we consider the auxiliary function (Uε , Vε ) := (u − εu, v − εv). For any ε > 0, (Uε , Vε ) is a strict supersolution of (6.1). Moreover, for sufficiently small ε > 0 we have that Uε (0) = u0 − εu(0) > 0

and Vε (0) = v0 − εv(0) > 0.

Choose one of these ε’s. Then, thanks to Proposition 6.2, Uε (t) > 0 and Vε (t) > 0 for each t 0. In particular, for each n 0, εu(0) = εu(nT ) < u(nT ) = ν2n u0 and, therefore, ν2 1. Suppose ν2 = 1. Then, λ0 = 0 and, thanks to Theorem 6.3, (6.1) possesses a T -solution (p, q) with p ≫ 0 and q ≫ 0. On the other hand, setting d := u′ − αu − βv,

δ := v ′ − γ u − ρv,

we have that d 0, δ 0, d + δ < 0, and u′ = αu + βv + d, v ′ = γ u + ρv + δ. Consequently, for each ξ ∈ R, the pair (uξ , vξ ) := (p − ξ u, q − ξ v) provides us with a T -periodic solution of

u′ = αu + βv − d, v ′ = γ u + ρv − δ.

(6.22)

Since p ≫ 0 and q ≫ 0, we have that uξ ≫ 0 and vξ ≫ 0 for sufficiently small ξ > 0. Moreover, since u ≫ 0 and v ≫ 0, we have that uξ ≪ 0 and vξ ≪ 0 for sufficiently large ξ > 0. Thus, there exists ξ > 0 such that uξ 0, vξ 0 and, for some t0 ∈ R, either uξ (t0 ) = 0, or vξ (t0 ) = 0. The result obtained in ending the proof of part (a) shows that this is impossible. It should be noted that −d 0, −δ 0 and −(δ + d) > 0. Therefore, ν2 > 1, which concludes the proof of the theorem.


421

6.2. Structure of the set of coexistence states In this section, the coexistence states of (1.2) will be regarded as zeroes of the operator F : R2 × CT × CT → CT × CT defined by F(λ, µ, u, v) :=

8

9 u − RM (λℓ + M)u − au2 − buv v − RM (µm + M)v − dv 2 − cuv

(6.23)

where M > 0 is fixed. The following result will provide us with the sharp structure of the whole surface, in terms of the parameters (λ, µ), of the coexistence states of (1.2) linking the surfaces of semi-trivial states of (1.2) along their curves of neutral stability. P ROPOSITION 6.5. Suppose (u0 , v0 ) ∈ CT × CT satisfies u0 ≫ 0, v0 ≫ 0, and F(λ, µ, u0 , v0 ) = 0. Then, each of the operators D(λ,u,v) F(λ, µ, u0 , v0 ) : R × CT × CT → CT × CT and D(µ,u,v) F(λ, µ, u0 , v0 ) : R × CT × CT → CT × CT is surjective. In other words, (0, 0) is a regular value of F with respect to R2 ×Int P ×Int P . P ROOF. By differentiating, we have that D(u,v) F(λ, µ, u0 , v0 ) = ICT ×CT − RM Dλ F(λ, µ, u0 , v0 ) = −RM

ℓu0 , 0

Dµ F(λ, µ, u0 , v0 ) = −RM

0 , mv0

αM −cv0

−bu0 , βM

(6.24) (6.25)

and (6.26)

where, for any ξ 0, we are denoting αξ := λℓ + ξ − 2au0 − bv0 ,

βξ := µm + ξ − 2dv0 − cu0 .

(6.27)

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Subsequently, it will be said that (λ, µ, u0 , v0 ) is a non-degenerate coexistence state of (1.2) if D(u,v) F(λ, µ, u0 , v0 ) is an isomorphism. In the contrary case, it will be said that (λ, µ, u0 , v0 ) is degenerate. Obviously, D(λ,u,v) F(λ, µ, u0 , v0 ) and D(µ,u,v) F(λ, µ, u0 , v0 ) are surjective if (λ, µ, u0 , v0 ) is non-degenerate. So, suppose (λ, µ, u0 , v0 ) is degenerate. Then, since D(u,v) F(λ, µ, u0 , v0 ) is a compact perturbation of the identity, it is Fredholm of index zero and, hence, N := dim N D(u,v) F(λ, µ, u0 , v0 ) = codim R D(u,v) F(λ, µ, u0 , v0 ) 1.

Now, note that N[D(u,v) F(λ, µ, u0 , v0 )] is the set of T -periodic solutions (u, v) of the linear system

u′ = α0 u − bu0 v, v ′ = −cv0 u + β0 v.

(6.28)

Since b < 0 and c < 0, we have that −bu0 > 0 and −cv0 > 0. Moreover, since (λ, µ, u0 , v0 ) is a coexistence state of (1.2), relations (6.7) hold with (u2 , v2 ) = (u0 , v0 ) and, hence,

T

0

α0 = −

T

a(t)u0 (t) dt < 0

0

and

0

T

β0 = −

T

d(t)v0 (t) dt < 0.

0

Therefore, (6.28) fits into the abstract setting of Section 6.1. Consequently, thanks to Theorems 6.1 and 6.3, the biggest multiplier of (6.28), denoted by ν2 , equals one and any T periodic solution of (6.28) must be a multiple of a fixed T -periodic solution (ϕ, ψ) such that ϕ ≫ 0 and ψ ≫ 0. In particular, N = 1. So, thanks to (6.25) and (6.26), to conclude the proof it suffices to show the following: −RM (ℓu0 , 0) ∈ / R D(u,v) F(λ, µ, u0 , v0 ) , −RM (0, mv0 ) ∈ / R D(u,v) F(λ, µ, u0 , v0 ) .

(6.29)

On the contrary, suppose that, e.g.,

−RM (ℓu0 , 0) ∈ R D(u,v) F(λ, µ, u0 , v0 ) .

Then, the system

u′ = α0 u − bu0 v + ℓu0 , v ′ = −cv0 u + β0 v,

(6.30)


423

possesses a T -periodic solution, say (u, v). Actually, for each R > 0, the pair (uR , vR ) := (u + Rϕ, v + Rψ) provides us with a T -periodic solution of (6.30). Since ℓu0 > 0, for sufficiently large R > 0, (uR , vR ) provides us with a T -periodic strongly positive strict supersolution of (6.28) and, therefore, thanks to Theorem 6.4(a), ν2 < 1, which is a contradiction, since ν2 = 1. Similarly, the second relation of (6.29) holds. This concludes the proof. The following result, which is an easy consequence from Proposition 6.5, ascertains the µ global structure of the components of coexistence states Cλµ and Cλ of (1.2) constructed in Theorems 5.4 and 5.5. T HEOREM 6.6. The following properties are satisfied: (a) For each λ > 0, the component of coexistence states Cλµ is unbounded in R×CT ×CT and it consists of a real analytic curve. More precisely, there exits a real analytic map (µ, u, v) : [0, ∞) → R × Int P × Int P such that µ(0), u(0), v(0) = (µ0 , θ[λℓ,a] , 0)

and

Cλµ =

µ(s), u(s), v(s) : s ∈ (0, ∞) .

µ

(b) For each µ > 0, the component of coexistence states Cλ is unbounded in R × CT × CT and it consists of a real analytic curve. More precisely, there exists a real analytic map (λ, u, v) : [0, ∞) → R × Int P × Int P such that λ(0), u(0), v(0) = (λ0 , 0, θ[µm,d] )

and

µ

Cλ =

λ(s), u(s), v(s) : s ∈ (0, ∞) .

(c) The set of coexistence states of (1.2) (λ, µ, u, v) ∈ R2 ×Int P ×Int P such that λ > 0 µ and, for some µ ∈ R, (µ, u, v) ∈ Cλµ , or µ > 0 and, for some λ ∈ R, (λ, u, v) ∈ Cλ is a real analytic surface linking the surfaces of semi-trivial states (λ, µ, θ[λℓ,a] , 0): λ > 0, µ ∈ R

and

(λ, µ, 0, θ[µm,d] ): λ ∈ R, µ > 0

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along their respective curves of neutral stability 1 µ= T

T

0


1 and λ = T

T 0


P ROOF. Suppose (λ, µ, u0 , v0 ) is a coexistence state of (1.2) with, e.g., λ > 0. Subsequently, we fix λ and regard to µ as the main path-following parameter. Suppose (λ, µ, u0 , v0 ) is non-degenerate. Then, the implicit function theorem shows that (µ, u0 , v0 ) lies in an analytic curve through it that can be locally parameterized by µ, or . . . by some length, or pseudo-length of arc of curve, as it is usual in numerical analysis of bifurcation problems. Now, suppose that (λ, µ, u0 , v0 ) is degenerate and let ω0 ∈ R × CT × CT such that N D(µ,u,v) F(λ, µ, u0 , v0 ) = span [ω0 ].

Let Z be any closed supplement of ω0 in R × CT × CT , i.e., R × CT × CT = span [ω0 ] ⊕ Z. Then, any element (µ, u, v) ∈ R × CT × CT admits a unique decomposition as (µ, u, v) = sω0 + z,

(s, z) ∈ R × Z.

So, the problem of solving F(λ, µ, u, v) = 0, with λ fixed, around (µ, u0 , v0 ) is equivalent to the problem of solving 0 = G(s, z) := F λ, (µ, u0 , v0 ) + sω0 + z

around (s, z) = (0, 0). The map G : R × Z → CT × CT is real analytic and it satisfies G(0, 0) = 0. Moreover, thanks to Proposition 6.5, the linearized operator Dz G(0, 0) = D(µ,u,v) F(µ, u0 , v0 )|Z is a linear isomorphism. Therefore, thanks to the implicit function, the set of coexistence states of (1.2) around (λ, µ, u0 , v0 ) consists of an analytic curve. Actually, the curve can be parameterized by the projection of the coexistence states on ω0 . Now, fix λ > 0. Since b < 0, for each µ > 0 we have that λ>0>

1 T

0

T

b(t)θ[µm,d] (t) dt

and, therefore, thanks to Theorem 5.4, Cλµ is unbounded. Moreover, thanks to Theorem 5.6, there exists L > 0 and a real analytic map (µ, u, v) : [0, L] → R × Int P × Int P


425

such that µ(0), u(0), v(0) = (µ0 , θ[λℓ,a] , 0)

and, in a neighborhood of (µ0 , θ[λℓ,a] , 0), Cλµ consists of µ(s), u(s), v(s) : 0 < s L .

By a global continuation argument based on the implicit function theorem, the local curve (µ(s), u(s), v(s)), s ∈ (0, L], admits a maximal continuation (non-prolonging) to a real analytic curve, (µ(s), u(s), v(s)), s ∈ (0, ∞), of coexistence states of (1.2). Actually, the parameter s can be taken as the length of arc of curve. Clearly, Γ :=

µ(s), u(s), v(s) : s > 0 ⊂ Cλµ ,

since Cλµ is connected. Moreover, the uniqueness obtained as an application of the implicit function theorem shows that there exists an open subset O ⊂ R × CT × CT such that Γ ⊂O

and F−1 (0) ∩ (R × Int P × Int P ) ∩ O = Γ.

Therefore, Cλµ = Γ , since Cλµ is connected. Part (b) follows from the symmetry of the problem. part (c) is a two-parameter re-interpretation of parts (a) and (b) that can be easily obtained from the fact that F is real analytic in all its arguments. This concludes the proof. For the autonomous counterpart of (1.2) with bc = 1, is very simple to check that, for each λ > 0, the curve µ(s), u(s), v(s) = (cλ, λ − bs, s),

s 0,

provides us with the component Cλµ bifurcating from the semi-trivial solution (λ, 0) at µ = cλ. As this simple example shows, in general, condition µ′ = 0 cannot be avoided unless some additional assumptions are made, as, e.g., having a priori bounds for the coexistence states of the model at µ = µ0 . Note that in case µ′ = 0, one necessarily has µ(s) = µ0 for each s 0 and lim sup u(s), v(s) C

T ×CT

s↑∞

= ∞,

since Cλµ is unbounded. Actually, as an immediate consequence from the analysis carried ˙ ≫ 0 and v(s) ˙ ≫ 0, out in the next section, in case µ′ = 0 one has that, for each s 0, u(s) d where · := ds . Therefore, lim u(s), v(s) C

s↑∞

T ×CT

= ∞.

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J. López-Gómez µ

6.3. Stability of the coexistence states along Cλµ and Cλ

Fix λ > 0 and let (µ(s), u(s), v(s)), s 0, be the real analytic map constructed in Theorem 6.6, where s is assumed to be the length of arc of curve. Subsequently, we shall denote d . Since · := ds F λ, µ(s), u(s), v(s) = 0,

s 0,

differentiating with respect to s gives ˙ u(s), ˙ v(s) ˙ = 0, D(µ,u,v) F λ, µ(s), u(s), v(s) µ(s),

s > 0,

(6.31)

and, hence,

˙ u(s), ˙ v(s) ˙ , N D(µ,u,v) F λ, µ(s), u(s), v(s) = span µ(s),

s > 0.

Moreover, since s has been taken as the length of arc of curve, µ(s), ˙ u(s), ˙ v(s) ˙ = 1, s > 0. R×C ×C T

T

(6.32)

On the other hand, since

µ(0), u(0), v(0) = (µ0 , θ[λℓ,a] , 0),

it follows from Theorem 5.6 that v(s) ˙ = ϕv + O(s) = e

·

0 (µ0 m−cθ[λℓ,a] )

+ O(s) ≫ 0,

s ↓ 0.

(6.33)

Now, set ˙ v(s) ˙ , (ps , qs ) := u(s),

s > 0,

and note that (6.31) can be equivalently rewritten in the form (ps )′ = λℓ − 2au(s) − bv(s) ps − bu(s)qs , (qs )′ = −cv(s)ps + µ(s)m − 2dv(s) − cu(s) qs + µ(s)mv(s). ˙ Note that, since −bu(s) > 0, −cv(s) > 0,

T

0

and

0

T

λℓ − 2au(s) − bv(s) = −2

T

0

µ(s)m − 2dv(s) − cu(s) = −2

au(s) < 0,

0

T

dv(s) < 0,

(6.34)

(6.35)

(6.36)


427

the linear system (6.34) fits within the general setting of Section 6.1. In particular, thanks to Proposition 2.1, we find from the first equation of (6.34) that, for each s > 0 sufficiently small, ps = R−[λℓ−2au(s)−bv(s)] −bu(s)qs ≫ 0.

Therefore, there exists ε > 0 such that

ps ≫ 0 and qs ≫ 0 for each s ∈ [0, ε].

(6.37)

Suppose µ = µ0 for each s 0. Then, (6.34) becomes into

(ps )′ = λℓ − 2au(s) − bv(s) ps − bu(s)qs , (qs )′ = −cv(s)ps + µ(s)m − 2dv(s) − cu(s) qs .

(6.38)

Thanks to (6.32), (ps , qs ) = (0, 0) and, hence, thanks to Theorem 6.1, for each s 0, either ps ≫ 0 and qs ≫ 0, or ps ≪ 0 and qs ≪ 0. Thanks to (6.37), necessarily ps ≫ 0 and qs ≫ 0 for each s ∈ [0, ∞).

(6.39)

Indeed, since s → (ps , qs ) is real analytic, if (6.39) is not satisfied, then, due to (6.37), there is some value of s, say s˜ > 0, where ps˜ > 0, qs˜ > 0, and, e.g., ps˜ ≫ 0 fails. Thanks to Theorem 6.1, this would imply ps˜ ≫ 0 and qs˜ ≫ 0, which is a contradiction. Thus, (6.39) is satisfied, as it was claimed in the last paragraph of Section 6.2, and, consequently, thanks to Theorem 6.3, the principal characteristic multiplier of (µ(s), u(s), v(s)), which will be subsequently denoted by ν2 (s), satisfies ν2 (s) = 1 for each s 0. Therefore, if µ˙ = 0, then ν˙ 2 = 0 and, hence, all the coexistence states of Cλµ are neutrally stable. When µ˙ = 0, then the following result is satisfied. T HEOREM 6.7. Suppose µ˙ = 0 in [0, ∞). Then, the set S := s ∈ (0, ∞): µ(s) ˙ =0

(6.40)

is discrete, each s ∈ S is a zero of finite order of µ, ˙ and S = s ∈ (0, ∞): ν2 (s) = 1 .

(6.41)

Moreover,

and

µ(s) ˙ 1 − ν2 (s) > 0,

s ∈ (0, ∞) \ S,

ps ≫ 0 and qs ≫ 0 if

µ(s) ˙ 0.

(6.42)

(6.43)

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P ROOF. The fact that S is discrete and that each s ∈ S has finite order, as a zero of µ, ˙ are consequences from the fact that µ˙ is real analytic. Now, we shall prove (6.41). Pick s ∈ S. Then, (ps , qs ) satisfies (6.38) and, due to (6.32), (ps , qs ) = (0, 0). Thus, thanks to Theorem 6.1, ps ≫ 0 and qs ≫ 0, or ps ≪ 0 and qs ≪ 0. In any of these cases, it follows from Theorem 6.3 that λ = 0 is the principal characteristic exponent of (µ(s), u(s), v(s)) and, hence, ν2 (s) = 1. To prove the converse inclusion, let s ∈ (0, ∞) such that ν2 (s) = 1. Then, thanks to Theorem 6.3, there exists a T -periodic pair (P , Q) with P ≫ 0 and Q ≫ 0 such that P ′ = λℓ − 2au(s) − bv(s) P − bu(s)Q, (6.44) Q′ = −cv(s)P + µ(s)m − 2dv(s) − cu(s) P . Now, choose a sufficiently small ε > 0 so that the auxiliary pair (U, V ) := (P − εps , Q − εqs ), satisfy U ≫ 0 and V ≫ 0. Thanks to (6.34) and (6.44) we have that

U ′ = λℓ − 2au(s) − bv(s) U − bu(s)V , V ′ = −cv(s)U + µ(s)m − 2dv(s) − cu(s) V − ε µ(s)mv(s). ˙

Assume µ(s) ˙ > 0. Then, since εmv(s) > 0, (U, V ) is a strict subsolution of

x ′ = λℓ − 2au(s) − bv(s) x − bu(s)y, y ′ = −cv(s)x + µ(s)m − 2dv(s) − cu(s) y,

(6.45)

and, hence, thanks to Theorem 6.4(b), ν2 (s) > 1, which is a contradiction. Assume µ(s) ˙ < 0. Then, (U, V ) is a strict supersolution of (6.45) and, due to Theorem 6.4(a), ν2 (s) < 1, which is a contradiction again. Consequently, µ(s) ˙ = 0 and, therefore, (6.41) holds. Now, pick s˜ ∈ S. Thanks to (6.32), it follows from Theorem 6.1 that some of the following alternatives occurs: 1. ps˜ ≫ 0 and qs˜ ≫ 0. 2. ps˜ ≪ 0 and qs˜ ≪ 0. Assume alternative 1 occurs. As s˜ is an isolated zero of µ(s), ˙ there exists ε > 0 such that ˙ ≫ 0 and qs = v(s) ˙ ≫ 0 for each s ∈ (˜s − ε, s˜ + ε), and ps = u(s) µ˙ −1 (0) ∩ s˜ − ε, s˜ + ε ∩ (0, ∞) = s˜ .

Thus, for each

s ∈ J := (0, ∞) ∩ s˜ − ε, s˜ + ε \ s˜ ,

either µ(s) ˙ > 0, or µ(s) ˙ < 0. Suppose µ(s) ˙ > 0. Then, (ps , qs ) provides us with a strongly positive strict supersolution of (6.45) and it follows from Theorem 6.4(a) that ν2 (s) < 1.


429

Hence, µ(s)(1 ˙ − ν2 (s)) > 0. Now, suppose µ(s) ˙ < 0. Then, (ps , qs ) provides us with a strongly positive strict subsolution of (6.45) and it follows from Theorem 6.4(b) that ˙ − ν2 (s)) > 0. Therefore, condition (6.42) is satisfied for each ν2 (s) > 1. Hence, µ(s)(1 s˜ ∈ S satisfying alternative 1. Now, suppose s˜ ∈ S satisfies alternative 2. As s˜ is an isolated zero of µ(s), ˙ there exists ˙ ≪ 0 and qs = v(s) ˙ ≪ 0 for each s ∈ (˜s − ε, s˜ + ε), and ε > 0 such that ps = u(s) µ˙ −1 (0) ∩ s˜ − ε, s˜ + ε ∩ (0, ∞) = s˜ .

Thus, for each

s ∈ J := (0, ∞) ∩ s˜ − ε, s˜ + ε \ s˜ ,

either µ(s) ˙ > 0, or µ(s) ˙ < 0. Suppose µ(s) ˙ > 0. Then, (−ps , −qs ) provides us with a strongly positive strict subsolution of (6.45) and it follows from Theorem 6.4(b) that ˙ − ν2 (s)) < 0. Similarly, if µ(s) ˙ < 0, then, (−ps , −qs ) proν2 (s) > 1. Hence, µ(s)(1 vides us with a strongly positive strict supersolution of (6.45) and Theorem 6.4(a) implies ν2 (s) < 1. Therefore, the following condition is satisfied µ(s) ˙ 1 − ν2 (s) < 0,

s ∈ (0, ∞) ∩ s˜ − ε, s˜ + ε \ s˜ ,

(6.46)

for each s˜ ∈ S satisfying alternative 2. Now, suppose S = {sn : n 1},

0 < s1 < sn < sn+1 , n 2;

the subsequent argument can be easily adapted to cover the case when S is finite, possibly empty. Thanks to (6.37), for sufficiently small s > 0, ps ≫ 0 and qs ≫ 0. Moreover, either ˙ < 0 for each s ∈ (0, s1 ). µ(s) ˙ > 0 for each s ∈ (0, s1 ), or µ(s) Suppose µ(s) ˙ > 0 for each s ∈ (0, s1 ). Then, for sufficiently small s > 0, (ps , qs ) provides us with a strongly positive strict supersolution of (6.45) and, hence, thanks to Theorem 6.4(a), ν2 (s) < 1. Actually, this is the inter-exchange stability principle between the semi-trivial state (µ, θ[λℓ,a] , 0) and the bifurcating coexistence state (µ(s), u(s), v(s)) as µ crosses µ0 . Thanks to (6.41), necessarily ν2 (s) < 1 for every s ∈ (0, s1 ) and, therefore, µ(s) ˙ 1 − ν2 (s) > 0,

s ∈ (0, s1 ).

µ(s) ˙ 1 − ν2 (s) > 0,

s ∈ (0, s2 ) \ {s2 }.

(6.47)

Necessarily ps1 ≫ 0 and qs1 ≫ 0. Indeed, if ps1 ≪ 0 and qs1 ≪ 0, then (6.46) holds, which contradicts (6.47). Therefore, (6.48)

Reiterating this argument, (6.42) holds readily. Now, suppose µ(s) ˙ < 0 for each s ∈ (0, s1 ). Then, (ps , qs ) provides us with a strongly positive strict subsolution of (6.45) and, hence, thanks to Theorem 6.4(b), ν2 (s) > 1. As

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J. López-Gómez

in the previous case, this provides us with the inter-exchange stability principle between the semi-trivial state (µ, θ[λℓ,a] , 0) and the bifurcating coexistence state (µ(s), u(s), v(s)). Thanks to (6.41), ν2 (s) > 1 for every s ∈ (0, s1 ) and, therefore, (6.47) is as well satisfied. Arguing as above, the proof of (6.42) is concluded. Note that, as a result from the previous analysis, we have that ps˜ ≫ 0 and qs˜ ≫ 0 for each s˜ ∈ S ∪ {0}.

(6.49)

Let s1∗ , s2∗ ∈ S ∪ {0} such that µ(s) ˙ > 0,

s ∈ s1∗ , s2∗ .

Thanks to (6.49), ps ≫ 0 and qs ≫ 0 for each s > s1∗ sufficiently close to s1∗ . Thus, either ps ≫ 0 and qs ≫ 0 for each s ∈ (s1∗ , s2∗ ), or there exist s0 ∈ (s1∗ , s2∗ ) and t ∈ R such that ps0 0 and qs0 0 and either ps0 (t) = 0, or qs0 (t) = 0. Since −cv(s0 )ps0 + µ(s ˙ 0 )mv(s0 ) > 0, thanks to Proposition 2.1, it follows from the second equation of (6.34) that qs0 ≫ 0. Thus, −bu(s0 )qs0 > 0 and, thanks again to Proposition 2.1, the first equation of (6.34) gives ps0 ≫ 0, which is impossible. Therefore, for each s ∈ (s1∗ , s2∗ ), ps ≫ 0 and qs ≫ 0, which concludes the proof of (6.43). The proof is completed. It should be noted that, since the dependence of the Poincaré map of (6.45) on s is analytic, the map s → ν2 (s) is as well real analytic. Moreover, ν2 (0) = 1, because this is the critical value of the parameter where the stability of the semi-trivial state changes. As far as to µ(0) ˙ concerns, it might take any real value, according with the value of the integral of (5.53). Subsequently, we shall assume µ˙ = 0 in order to use Theorem 6.7 for ascertaining the attractive character of all the coexistence states along the curve Cλµ . In this case, setting s1 = min S, some of the following alternatives occurs. Either µ(s) ˙ > 0,

s ∈ (0, s1 )

(6.50)


431

Fig. 11. An admissible graph of µ(s) ˙ in case (6.50).

or µ(s) ˙ < 0,

s ∈ (0, s1 ).

(6.51)

If S = ∅, then either µ(s) ˙ > 0 for each s > 0, or µ(s) ˙ < 0 for each s > 0. The bifurcation of Cλµ from (µ0 , θ[λℓ,a] , 0) is said to be super-critical if (6.50) occurs, while it is said to be sub-critical if (6.51) is satisfied. The following concepts will be extremely useful in the forthcoming discussion. Given s˜ ∈ S, we shall denote by ord (˜s ) the order of s˜ as a zero of µ(s). ˙ • A value s˜ ∈ S is said to be a hysteresis point of Cλµ if ord (˜s ) is even. • A value s˜ ∈ S is said to be a super-critical turning point of Cλµ if ord (˜s ) is odd and µ(s) > µ(˜s ) in a perforated neighborhood of s˜ . • A value s˜ ∈ S is said to be a sub-critical turning point of Cλµ if ord (˜s ) is odd and µ(s) < µ(˜s ) in a perforated neighborhood of s˜ . Suppose (6.50) and, e.g., the graph of µ(s) ˙ is of the type sketched in Fig. 11. Although ˙ > 0 for each far from necessary we shall assume that S = {s1 , s2 , s3 , s4 , s5 }. Hence, µ(s) s > s5 . For this special configuration, s1 , s3 and s4 are hysteresis points, while s2 is a sub-critical turning point and s5 is a super-critical turning point. Thanks to Theorem 6.7, the principal characteristic multiplier ν2 (s) of the coexistence state (µ(s), u(s), v(s)) must adjust to the pattern shown in Fig. 12. Therefore, the coexistence state (µ(s), u(s), v(s)) is asymptotically stable if s ∈ (0, s1 ) ∪ (s1 , s2 ) ∪ (s5 , ∞), whereas it is unstable if s ∈ (s2 , s5 ) \ {s3 , s4 }. In Fig. 13 we have represented the corresponding bifurcation diagram of coexistence states, where we are representing the value of u(t) for a given time t ∈ R versus the parameter µ, not s. Except for (µ, 0, 0), continuous lines represent stable solutions, while dashed lines represent unstable solutions. The horizontal lines represent the curves of states (µ, 0, 0) and (µ, θ[λℓ,0] , 0). The curve Cλµ bifurcates from (µ, θ[λℓ,a] , 0) at µ = µ0 =

1 T

T 0

c(t)θ[λℓ,a] (t) dt < 0,

since c < 0. The wiggled thick line represent Cλµ , whose bifurcation from the semi-trivial state is super-critical. At the sub-critical turning point (µ(s2 ), u(s2 ), v(s2 )) the stability of

432

J. López-Gómez

Fig. 12. The corresponding principal characteristic multiplier ν2 (s).

Fig. 13. The corresponding bifurcation diagram.

the solutions along the lower arc of curve of Cλµ is lost. Then, the solutions stay unstable until the second turning point, (µ(s5 ), u(s5 ), v(s5 )), which is super-critical, is passed by. Once crossed the super-critical turning point, all remaining solutions for further values of s stay stable. It should be noted that, thanks to Theorem 6.7, u(s) and v(s) are strongly increasing along the pieces of the curve Cλµ where µ(s) ˙ 0. Now, suppose (6.51), instead of (6.50), and, e.g., the graph of µ(s) ˙ adjust to the profile shown in Fig. 14. According to Theorem 6.7, the principal characteristic multiplier ν2 (s) of the coexistence state (µ(s), u(s), v(s)) must adjust to the pattern shown in Fig. 15. In Fig. 16 we have represented an admissible bifurcation diagram corresponding to the graph of µ(s) ˙ shown in Fig. 14. Now the bifurcation of Cλµ from (µ, θ[λℓ,a] , 0) at µ0 is sub-critical, the solutions along the lower curve being unstable until they reach the supercritical turning point (µ(s2 ), u(s2 ), v(s2 )), where they become stable until reaching the second turning point, (µ(s5 ), u(s5 ), v(s5 )), where they become unstable and stay unstable for any further value of s, s > s5 .


433

Fig. 14. An admissible graph for µ(s) ˙ in case (6.51).

Fig. 15. The corresponding principal characteristic multiplier ν2 (s).

Fig. 16. The corresponding bifurcation diagram.

As in the previous example, as a result of Theorem 6.7, s → (u(s), v(s)) is strongly increasing along any arc of curve filled in by stable solutions, though some of the components might decrease along some pieces of the arcs of curve where the coexistence states are unstable.

434

J. López-Gómez

Generically, when some additional parameter of the model is varied, each hysteresis point will either disappear, or it will generate an even number of turning points; half among them sub-critical and the other half super-critical. This might provide with a mechanism to generate models with an arbitrarily large number of coexistence states. It should be noted that (1.2) might possess some additional coexistence state not lying / Cλµ , then in Cλµ . If this is the case, i.e., if (1.2) possesses a coexistence state (µ, u0 , v0 ) ∈ the global continuation argument used to ascertain the analytic structure of Cλµ also shows that there is an analytic curve (µ, u, v) : (−∞, ∞) → R × CT × CT of coexistence states of (1.2) such that µ(0), u(0), v(0) = (µ, u0 , v0 )

and µ˙ = 0. Indeed, if µ˙ = 0, then µ(s) = µ for each s, and s → (u(s), v(s)) must be strongly monotone, and, as a result, it should bifurcate from (µ0 , θ[λℓ,a] , 0), which is not / Cλµ . Theorem 6.7 also applies along these curves, showing possible, because (µ, u0 , v0 ) ∈ that ν2 (s) − 1 must change of sign at any turning point along them. The corresponding curves should be either isolated bounded components, or unbounded components, but a sharper analysis of this and other related problems escapes from the general scope of this chapter. By symmetry, all the results that we have obtained for Cλµ are also valid for the compoµ nents Cλ obtained by fixing µ > 0 and using λ as the main bifurcation parameter. 6.4. Low and strong symbiosis effects Throughout this section we will assume that ℓ ≫ 0,

m ≫ 0,

a ≫ 0,

d ≫ 0,

−b ≫ 0,

−c ≫ 0.

(6.52)

Then, it is said that (1.2) is lowly symbiotic if

−b a

M

−c d

< 1,

(6.53)

M

while it is said that (1.2) is highly symbiotic if

−b a

L

−c d

> 1.

(6.54)

L

Although in the intermediate situation cases where conditions (6.53) and (6.54) fail, the µ curves of coexistence states Cλµ and Cλ might exhibit a bounded µ projection and a bounded λ projection, respectively, because of the lost of uniform priori bounds in CT ×CT ,


435

in the cases when some of these conditions is satisfied, the µ and λ-projections are unbounded. Actually, the following result is satisfied for the case of low symbiosis. T HEOREM 6.8. Assume (6.52), (6.53), and (1.2) possesses a coexistence state, say (λ, µ, u, v). Then, λ −(−b/ℓ)M (m/d)M µ if µ > 0, µ −(−c/m)M (ℓ/a)M λ if λ > 0.

(6.55)

Moreover,

u CT

(ℓ/a)M |λ| + (−b/a)M (m/d)M |µ| , 1 − (−b/a)M (−c/d)M

(m/d)M |µ| + (−c/d)M (ℓ/a)M |λ|

v CT , 1 − (−b/a)M (−c/d)M

(6.56)

and, therefore, for each λ > 0 and µ > 0 there exist µ1 = µ1 (λ) ∈ (−∞, µ0 ] and λ1 = λ1 (µ) ∈ (−∞, λ0 ] such that Pµ Cλµ ∈ [µ1 , ∞), (µ0 , ∞)

µ and Pλ Cλ ∈ [λ1 , ∞), (λ0 , ∞) ,

where Pγ stands for the γ -projection operator, γ ∈ {λ, µ}. P ROOF. Pick t0 , t1 ∈ R such that u(t0 ) = u CT

and v(t1 ) = v CT .

Then, u′ (t0 ) = v ′ (t1 ) = 0 and, hence, λℓ(t0 ) − a(t0 )u(t0 ) − b(t0 )v(t0 ) = 0,

µm(t1 ) − d(t1 )v(t1 ) − c(t1 )u(t1 ) = 0.

Thus, u(t0 ) = λ

ℓ(t0 ) b(t0 ) − v(t0 ), a(t0 ) a(t0 )

v(t1 ) = µ

m(t1 ) c(t1 ) − u(t1 ). d(t1 ) d(t1 )

Now, since v(t0 ) v(t1 ) = µ

m(t1 ) c(t1 ) m(t1 ) c(t1 ) − u(t1 ) µ − u(t0 ), d(t1 ) d(t1 ) d(t1 ) d(t1 )

(6.57)

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J. López-Gómez

the first identity of (6.57) implies u(t0 )

b(t0 ) m(t1 ) b(t0 ) c(t1 ) ℓ(t0 ) λ− µ+ u(t0 ) a(t0 ) a(t0 ) d(t1 ) a(t0 ) d(t1 )

and, hence, b(t0 ) c(t1 ) b(t0 ) m(t1 ) ℓ(t0 ) 1− u(t0 ) λ− µ. a(t0 ) d(t1 ) a(t0 ) a(t0 ) d(t1 )

(6.58)

b(t0 ) c(t1 ) c(t1 ) ℓ(t0 ) m(t1 ) 1− v(t1 ) µ− λ. a(t0 ) d(t1 ) d(t1 ) d(t1 ) a(t0 )

(6.59)

Similarly,

Moreover, thanks to (6.53),

−b 0 0 and consider the analytic curve Cλµ . Thanks to Theorem 6.6(a), Cλµ is unbounded in R × CT × CT . Thus, thanks to the uniform a priori estimates (6.56), Pµ Cλµ must be unbounded. Note that it is connected, since Cλµ is a curve. Therefore, the conclusion follows from the second necessary condition of (6.55). Similarly, one can obtain the µ corresponding assertion for Cλ . As a consequence from Theorem 6.8, for each λ > 0, the curve Cλµ looks like the one shown in Fig. 13, whereas, for the case of strong symbiosis, the following result shows that Cλµ looks like shows Fig. 16. T HEOREM 6.9. Assume (6.52), (6.54), −1 (a/d)L (d/a)L > (−b/a)L (−c/d)L ,

(6.61)

and (1.2) possesses a coexistence state, say (λ, µ, u, v). Then, λ −(−b/a)L (a/d)L µ,

µ −(−c/d)L (d/a)L λ,

(6.62)


437

and

T

−T (λ + (−b/a)L (a/d)L µ) , aL [(−b/a)L (−c/d)L (a/d)L (d/a)L − 1]

u

0

T

0

(6.63)

−T (µ + (−c/d)L (d/a)L λ) . v dL [(−b/a)L (−c/d)L (a/d)L (d/a)L − 1]

Therefore, for each λ > 0 and µ > 0 there exist µ1 = µ1 (λ) ∈ [µ0 , 0) and λ1 = λ1 (µ) ∈ [λ0 , 0) such that Pµ Cλµ ∈ (−∞, µ1 ], (−∞, µ0 )

µ and Pλ Cλ ∈ (−∞, λ1 ], (−∞, λ0 ) .

P ROOF. Dividing by u the u-equation, by v the v-equation, and integrating in [0, T ] gives 1 λ= T

T

0

(au + bv),

1 µ= T

T

(dv + cu).

0

(6.64)

Thus,

0

T

(au) = λT −

0

T

(bv) λT + (−b/a)L

λT + (−b/a)L (a/d)L

T

(av) 0

T

(dv)

0

= T λ + (−b/a)L (a/d)L T µ + (−b/a)L (a/d)L T λ + (−b/a)L (a/d)L T µ + (−b/a)L (−c/d)L (a/d)L (d/a)L

T

(−cu)

0

T

(au) 0

and, hence, 1 − (−b/a)L (−c/d)L (a/d)L (d/a)L

T

(au) T λ + (−b/a)L (a/d)L µ .

T

(dv) T µ + (−c/d)L (d/a)L λ .

0

Similarly, 1 − (−b/a)L (−c/d)L (a/d)L (d/a)L

0

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J. López-Gómez

On the other hand, thanks to (6.61), we have that (−b/a)L (−c/d)L (a/d)L (d/a)L > 1, and, hence, (6.62) holds true. Therefore, aL

T

u

0

dL

T

v

0

T

(au) −T

0 T 0

λ + (−b/a)L (a/d)L µ , (−b/a)L (−c/d)L (a/d)L (d/a)L − 1

(6.65)

µ + (−c/d)L (d/a)L λ (dv) −T , (−b/a)L (−c/d)L (a/d)L (d/a)L − 1

and, consequently, (6.63) is as well true. Now, fix λ > 0 and consider Cλµ . Thanks to Theorem 6.6(a), Cλµ is unbounded in R × CT × CT . Moreover, due to second estimate of (6.62), Pµ Cλµ ∩ [0, ∞) = ∅. On the other hand, thanks to (6.63), u and v possess uniform a priori bounds in CT on compact subsets of (λ, µ). Indeed, it is rather clear that (6.63) shows that uL and vL are uniformly bounded. Now, pick tu , tv ∈ R such that uL = u(tu ),

vL = v(tv ).

Then, u(t) = e

t

tu (λℓ−au−bv)

u(tu ),

v(t) = e

t

tv (µm−dv−cu)

must be uniformly bounded, as well. This concludes the proof.

v(tv ),

Even in the case when the model possesses a stable coexistence state, the solutions of (1.1) might blow up in finite time for sufficiently large initial data. In the case of high symbiosis, where according to Theorem 6.9 Problem (1.2) does not admit a coexistence state if λ > 0 and µ > 0, all solutions of (1.1) will blow-up in finite time independently of the size of the initial populations. Actually, this is the reason why (1.2) cannot admit a coexistence state. We refrain of giving more details here in, though we send to the interested reader to [11] for further technical details concerning the elliptic counterpart of the model studied here in.

7. The competing species model (b > 0 and c > 0) Undoubtedly, this is the case that has attracted more attention in the mathematical literature. Perhaps, because in a certainly pioneer chapter, P. de Mottoni and A. Schiaffino [29] showed that any solution of (1.1) converges in the large to a T -periodic component-wise


439

non-negative solution of (1.2), which extraordinary facilitates the analysis of the dynamics of (1.1). Among the most important works related to this model one should include the most pioneering chapter of J.M. Cushing [7], where the average of the birth rates, λ and µ, were used by the first time as the main bifurcation parameters to show the existence of a continuum, not necessarily a curve, of coexistence states of (1.2) linking the two semi-trivial states of the model. Then, a huge industry grew from these pioneering chapters. Among the most important posterior works one should quote those of S. Ahmad [1], S. Ahmad and A.C. Lazer [2], C. Alvárez and A.C. Lazer [3], J.C. Eilbeck and J. López-Gómez [12], J.K. Hale and A. Somolinos [14], P. Hess and A.C. Lazer [15], J. López-Gómez [17], R. Ortega and A. Tineo [30], H. Smith [32,33], A. Tineo [34,35], and F. Zanolin [36], among many others that are omitted here; many of them authorized by the previous authors. Rather naturally, in this section we will focus our attention into the results obtained µ in [17] and [12], where it was proved that the components Cλµ and Cλ are real analytic curves consisting of coexistence states whose attractive character changes when a turning point is crossed. This theorem is a very sharp improvement of a previous result by R. Ortega and A. Tineo [30], were it was shown that either the model possess a segment of coexistence states, or it exhibits a finite number of coexistence states. Although in the previous references some uniqueness results were given, the problem of the uniqueness remains, in its wide amplitude, entirely open, and it will be treated elsewhere.

7.1. Periodic systems of quasi-cooperative type In this section we study the periodic linear system u′ = αu − βv, v ′ = −γ u + ρv,

(7.1)

where α, β, γ , ρ ∈ CT satisfy

0

T

α < 0,

T

ρ < 0,

β > 0,

γ > 0,

(7.2)

0

and its associated Cauchy problem  ′   u = αu − βv, v ′ = −γ u + ρv,   u(0) = u0 , v(0) = v0 .

(7.3)

As an immediate consequence from Theorem 6.1, it follows the next result. T HEOREM 7.1. Suppose (7.1) possesses a solution (u, v) ∈ CT1 × CT1 \ {(0, 0)}. Then, either u ≫ 0 and v ≪ 0, or else u ≪ 0 and v ≫ 0. Therefore, all the coexistence states

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J. López-Gómez

of (1.2) must be ordered, in the sense that for any pair of coexistence states, (u1 , v1 ) = (u2 , v2 ), either u1 ≫ u2 and v1 ≪ v2 , or u1 ≪ u2 and v1 ≫ v2 . P ROOF. The change of variable (x, y) = (u, −v)

(7.4)

transforms (7.1) into

x ′ = αx + βy,

y ′ = γ x + ρy,

(7.5)

which is of the same type as (6.1). Therefore, the result is a corollary of Theorem 6.1. Similarly, the following quasi-cooperative counterpart of Proposition 6.2 holds. P ROPOSITION 7.2. Suppose (u, ¯ v) ¯ ∈ C 1 (R+ ) × C 1 (R+ ), R+ := [0, ∞), satisfy  ′ ¯  u¯ α u¯ − β v, ′ v¯ −γ u¯ + ρ v, ¯  u(0) ¯ > 0, v(0) ¯ < 0.

(7.6)

Then, u(t) ¯ > 0 and v(t) ¯ < 0 for each t 0. If u0 − v0 > 0 and u0 v0 = 0, then there exists t0 > 0 such that the unique solution (u, v) of (7.3) satisfies u(t) > 0 and v(t) < 0 for each t t0 . P ROOF. The auxiliary pair (x, ¯ y) ¯ := (u, ¯ −v) ¯ satisfies  ′ ¯   x¯ α x¯ + β y, y¯ ′ γ x¯ + ρ y, ¯   x(0) ¯ > 0, y(0) ¯ > 0,

and, hence, thanks to Proposition 6.2, x(t) ¯ > 0 and y(t) ¯ > 0 for each t 0, which concludes the proof of the first claim. Now, suppose u0 − v0 > 0 and u0 v0 = 0, and let (u(t), v(t)) denote the unique solution of (7.3). Then, (x, y) := (u, −v)


441

satisfies

and

 ′   x = αx + βy, y ′ = γ x + ρy,   x(0) = u0 , y(0) = −v0 , x(0) + y(0) = u0 − v0 > 0,

x(0)y(0) = 0.

Thus, it follows from Proposition 6.2 that there exists t0 > 0 such that x(t) > 0 and y(t) > 0 for each t t0 . Therefore, u(t) > 0 and v(t) < 0 for each t t0 , which concludes the proof. Also, the following counterpart of Theorem 6.3 holds. Subsequently, we shall denote by Φ(T ) the Poincaré map of (7.1). T HEOREM 7.3. The characteristic multipliers of (7.1), ν1 and ν2 , are real and distinct, and satisfy 0 < ν1 ν2 < 1. Moreover, if we order them so that 0 < ν1 < ν2 , then, 0 < ν1 < 1,

and

N Φ(T ) − ν1 I = span (x0 , y0 )

with x0 > 0 and y0 > 0,

N Φ(T ) − ν2 I = span (x0 , y0 )

with x0 > 0 and y0 < 0.

In particular, (7.1) is asymptotically stable if ν2 < 1, neutrally stable if ν2 = 1, and unstable if ν2 > 1. Furthermore, the value 1 λ0 := − Log ν2 T

(7.7)

provides us with the unique value of λ ∈ R for which the eigenvalue problem

u′ = αu − βv + λu, v ′ = −γ u + ρv + λv

admits a solution (u, v) ∈ CT1 × CT1 such that u ≫ 0 and v ≪ 0. P ROOF. As the change of variable (7.4) transforms (7.1) into (7.5), if U (T ) =

u11 u21

u12 u22

(7.8)

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J. López-Gómez

denotes the Poincaré map of (7.5), necessarily u11 −u12 . Φ(T ) = −u21 u22

(7.9)

Indeed, if we denote by (u(t), v(t)) the unique solution of (7.3) and (x(t), y(t)) stands for the unique solution of (7.5) satisfying (x(0), y(0)) = (u0 , −v0 ), then u11 −u12 x(T ) u x(0) u(T ) = = = Φ(T ) 0 . v0 −u21 u22 −y(T ) v(T ) −y(0) Clearly, the eigenvalues of U (T ) and Φ(T ) are the same. Moreover, thanks to Theorem 6.3, N U (T ) − ν1 I = span (x˜0 , y˜0 ) N U (T ) − ν2 I = span (x˜0 , y˜0 )

with x˜0 < 0 and y˜0 > 0, with x˜0 > 0 and y˜0 > 0,

and a direct calculation shows that, for each j ∈ {1, 2}, (x, y) is an eigenvector of U (T ) associated to the eigenvalue νj if, and only if, (x, −y) is an eigenvector of Φ(T ) associated to νj . Therefore,

and

N Φ(T ) − ν1 I = span (x0 , y0 )

with x0 > 0 and y0 > 0,

N Φ(T ) − ν2 I = span (x0 , y0 )

with x0 > 0 and y0 < 0,

which concludes the proof of the first block of statements. Finally, note that the change of variable (7.4) transforms (7.8) into the equivalent system x ′ = αx + βy + λx, y ′ = γ x + ρy + λy,

for which the last assertion of Theorem 6.3 is valid. This concludes the proof.

Finally, by performing the change of variable (7.4), it is easy to see that the following counterpart of Theorem 6.4 is satisfied. T HEOREM 7.4. The following properties are satisfied: ¯ v) ¯ ∈ CT1 × CT1 with (a) System (7.1) is stable (ν2 < 1) if, and only if, there exists (u, u¯ ≫ 0 and v¯ ≪ 0 such that u¯ ′ α u¯ − β v, ¯ (7.10) ′ v¯ −γ u¯ + ρ v, ¯ with some of these inequalities strict.


443

(b) System (6.1) is unstable (ν2 > 1) if, and only if, there exits (u, v) ∈ CT1 × CT1 with u ≫ 0 and v ≪ 0 such that

u′ αu − βv, v ′ −γ u + ρv,

(7.11)

with some of these inequalities strict. µ

7.2. Structure of the components Cλµ and Cλ

As in Section 6.2, the coexistence states of (1.2) will be regarded as zeroes of the operator F : R2 × CT × CT → CT × CT defined by (6.23), where M > 0 is fixed. The following counterpart of Proposition 6.5 is satisfied. P ROPOSITION 7.5. Suppose (u0 , v0 ) ∈ CT × CT satisfies u0 ≫ 0, v0 ≫ 0, and F(λ, µ, u0 , v0 ) = 0. Then, each of the operators D(λ,u,v) F(λ, µ, u0 , v0 ) : R × CT × CT → CT × CT and D(µ,u,v) F(λ, µ, u0 , v0 ) : R × CT × CT → CT × CT is surjective. In other words, (0, 0) is a regular value of F with respect to R2 ×Int P ×Int P . P ROOF. As in the proof of Proposition 6.5, differentiating gives (6.24), (6.25) and (6.26). Similarly, D(λ,u,v) F(λ, µ, u0 , v0 ) and D(µ,u,v) F(λ, µ, u0 , v0 ) are surjective if (λ, µ, u0 , v0 ) is non-degenerate. So, suppose (λ, µ, u0 , v0 ) is degenerate. Then, since D(u,v) F(λ, µ, u0 , v0 ) is a compact perturbation of the identity, N := dim N D(u,v) F(λ, µ, u0 , v0 ) = codim R D(u,v) F(λ, µ, u0 , v0 ) 1,

and N [D(u,v) F(λ, µ, u0 , v0 )] is the set of T -periodic solutions (u, v) of the linear system

u′ = α0 u − bu0 v,

v ′ = −cv0 u + β0 v.

Since b > 0 and c > 0, we have that −bu0 < 0

and −cv0 < 0.

(7.12)

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J. López-Gómez

Moreover, since (λ, µ, u0 , v0 ) is a coexistence state of (1.2),

T

0

α0 = −

T

a(t)u0 (t) dt < 0

and

0

0

T

β0 = −

T

d(t)v0 (t) dt < 0.

0

Therefore, (7.12) fits into the abstract setting of Section 7.1. Thus, thanks to Theorem 7.3, the biggest multiplier of (7.12), denoted by ν2 , equals one and any T -periodic solution of (7.12) must be a multiple of a fixed T -periodic solution (ϕ, ψ) such that ϕ ≫ 0 and ψ ≪ 0. In particular, N = 1. Now, due to (6.25) and (6.26), to conclude the proof it suffices to prove (6.29). On the contrary, suppose that, e.g., −RM (ℓu0 , 0) ∈ R D(u,v) F(λ, µ, u0 , v0 ) .

Then, the system

u′ = α0 u − bu0 v + ℓu0 , v ′ = −cv0 u + β0 v,

(7.13)

possesses a T -periodic solution (u, v). Actually, for each R > 0, the pair (uR , vR ) := (u + Rϕ, v + Rψ) provides us with a T -periodic solution of (7.13) such that, for sufficiently large R > 0, uR ≫ 0 and vR ≪ 0. Moreover, it follows from ℓu0 > 0 that u′R > α0 uR − bu0 vR , vR′ = −cv0 uR + β0 vR ,

and, therefore, thanks to Theorem 7.4(a), ν2 < 1, which is a contradiction, since ν2 = 1. Similarly, the second relation of (6.29) holds. This concludes the proof. The following result ascertains the global structure of the coexistence states of (1.2) for the competing species model. To reduce the complexity of the number of cases to be considered in our analysis we shall throughout assume that conditions (4.10) are satisfied, though most of the results are still valid in the absence of (4.10)—such restrictions are exclusively needed in order to get some non-existence results entailing the relative comµ pactness of the components Cλµ and Cλ . T HEOREM 7.6. Assume b > 0, c > 0, and (1.2) exhibits a coexistence state, say (λ, µ, u0 , v0 ). Then, λ > 0, µ > 0, and u0 ≪ θ[λℓ,a] ,

v0 ≪ θ[µm,d] .

(7.14)


445

Moreover, the following properties are satisfied: (a) For each λ > 0 there exists µ1 (λ) > 0 such that (1.2) does not admit a coexistence state if µ µ1 (λ). Moreover, the component of coexistence states Cλµ constructed in Theorem 5.4 is bounded in R × CT × CT and it consists of a real analytic curve. More precisely, there exits a real analytic map (µ, u, v) : [0, 1] → R × Int P × Int P such that µ(0), u(0), v(0) = (µ0 , θ[λℓ,a] , 0), µ(1), u(1), v(1) = (µ∗ , 0, θ[µ∗ m,d] ), and

Cλµ =

µ(s), u(s), v(s) : s ∈ (0, 1) ,

where µ∗ > 0 is the unique value of µ satisfying (5.40). (b) For each µ > 0 there exists λ1 (µ) > 0 such that (1.2) does not admit a coexistence µ state if λ λ1 (µ). Moreover, the component of coexistence states Cλ constructed in Theorem 5.5 is bounded in R × CT × CT and it consists of a real analytic curve. More precisely, there exists a real analytic map (λ, u, v) : [0, 1] → R × Int P × Int P such that λ(0), u(0), v(0) = (λ0 , 0, θ[µm,d] ), λ(1), u(1), v(1) = (λ∗ , θ[λ∗ ℓ,a] , 0), and

µ Cλ = (λ(s), u(s), v(s) : s ∈ (0, 1) ,

where λ∗ > 0 is the unique value of λ satisfying (5.46). (c) The set of coexistence states of (1.2) (λ, µ, u, v) ∈ R2 × Int P × Int P such that, for µ some µ ∈ R, (µ, u, v) ∈ Cλµ , or, for some λ ∈ R, (λ, u, v) ∈ Cλ , is a real analytic surface linking the surfaces of semi-trivial states (λ, µ, θ[λℓ,a] , 0) : λ > 0, µ ∈ R and (λ, µ, 0, θ[µm,d] ): λ ∈ R, µ > 0

along their respective curves of neutral stability µ=

1 T

T 0


and λ =

1 T

0

T


Therefore, (1.2) possesses a coexistence state if both semi-trivial states are, simultaneously, linearly unstable, or linearly stable.

446

J. López-Gómez µ

P ROOF. The fact that the components Cλµ and Cλ are real analytic curves follows from Proposition 7.5 adapting the argument of the proof of Theorem 6.6. Now, we shall show that both components are bounded. The remaining assertions of the theorem follow straight ahead from Theorems 5.4 and 5.5. Suppose (λ, µ, u0 , v0 ) is a coexistence state of (1.2). Then, dividing by u0 the uequation, by v0 the v-equation, and integrating in [0, T ] gives 1 λ= T

T

0

1 (au0 + bv0 ) > 0 and µ = T

T 0

(dv0 + cu0 ) > 0.

Thus, λ > 0 and µ > 0 are necessary for the existence of a coexistence state. So, throughout the remaining of the proof we will assume that λ > 0 and µ > 0. Fix λ > 0. Then, u0 ≫ 0 is a positive strict subsolution of the problem u′ = λℓ − au2 ,

u ∈ CT1 ,

since bu0 v0 > 0, and, hence, thanks to Proposition 2.6, u0 ≪ θ[λℓ,a] . Similarly, v0 ≪ θ[µm,d] . Thus, v0 = µmv0 − dv02 − cu0 v0 > (µm − cθ[λℓ,a] )v0 − dv02 . Hence, if µ>

1 T

T

0


then, thanks again to Proposition 2.6, we have that v0 ≫ θ[µm−cθ[λℓ,a] ,d] := Θµ , and, so, u0 < (λℓ − bΘµ )u0 − au20 . Consequently, dividing by u0 and integrating in [0, T ] gives 1 λ> T

T

b(t)Θµ (t) dt.

(7.15)

0

To show the existence of µ1 (λ) such that (1.2) cannot admit a coexistence state if µ µ1 it suffices to show that (7.15) cannot be satisfied for sufficiently large µ. To show this, note that the function Ψµ defined through Θµ := µΨµ satisfies 1 ′ cθ[λℓ,a] Ψµ − dΨµ2 . Ψ = m− µ µ µ


Adapting the argument of the proof of (2.20) it is apparent that limµ↑∞ Ψµ = in R, since

cθ limµ↑∞ [λℓ,a] µ

447 m d

uniformly

= 0. Therefore,

lim Θµ = ∞

µ↑∞

uniformly in [0, T ], and, consequently, (7.15) fails to be true for sufficiently large µ. By symmetry, for any µ > 0 there exists λ1 (µ) > 0 such that (1.2) does not admit a coexistence state if λ λ1 (µ). µ The previous bounds show that Cλµ and Cλ must be bounded for each λ > 0 and µ > 0. The remaining assertions of the theorem follow readily from Theorems 5.4, 5.5 and 5.6. For the autonomous counterpart of (1.2) with bc = 1, is easy to check that, for any λ > 0, the curve µ(s), u(s), v(s) = (cλ, λ − bs, s),

λ 0s , b

provides us with the component Cλµ bifurcating from the semi-trivial solution (λ, 0) at µ = cλ. As this simple example shows, condition µ˙ = 0 cannot be avoided in general, unless some additional assumptions are imposed; e.g., that the semi-trivial states cannot be simultaneously neutrally stable. As in the symbiotic model, fixing λ, or µ, and due to Proposition 7.5, any coexistence state of (1.2), say (λ, µ, u0 , v0 ), must lay into a real analytic curve of coexistence states of (1.2). Fix, e.g., λ and let Γ denote the trajectory of the µ–curve of coexistence states containing (λ, µ, u0 , v0 ). As a consequence from the existence of uniform a priori bounds in CT for the coexistence states of (1.2) (cf. Theorem 7.6), Γ must be bounded. If Γ ∩Cλµ = ∅, then Γ = Cλµ . Thus, if Γ = Cλµ , necessarily Γ ∩Cλµ = ∅, and, consequently, Γ must be an isolated component with respect of the surfaces of semi-trivial positive solutions of (1.2). Suppose such a component exists. Then, by varying an additional parameter of the model, e.g., the amplitude of b, or c, it is possible to show that when b, or c are sufficiently small, then (1.2) possesses a unique coexistence state, necessarily belonging to Cλµ . Therefore, at some intermediate value of the unfolding parameter, the isolated component Γ must reduce to a single point. Thanks to Proposition 7.5 this is impossible. Therefore, the only coexistence states of (1.2) are those contained in the components Cλµ . The technical details of this analysis will appear elsewhere. As an easy consequence from Theorem 7.6, except in the case when both semi-trivial states are neutrally stable, (1.2) possesses, at most, a finite number of coexistence states and, according to Theorem 7.1, all of them must be ordered, which provides us with the main result of R. Ortega and A. Tineo [30]. In the case when both semi-trivial states are neutrally stable, either there is an analytic curve of coexistence states linking both states, or the model possesses a finite number of coexistence states; its cardinal depending on the values of the several parameter functions involved in the setting of the model.

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J. López-Gómez µ

7.3. Stability of the coexistence states along Cλµ and Cλ

Fix λ > 0 and let (µ(s), u(s), v(s)), s 0, be the real analytic map constructed in Theorem 7.6, where s ∈ (0, L) is assumed to be the length of arc of curve. Subsequently, we d shall denote · := ds . Repeating the argument of Section 6.3, we have (6.31) and (6.32). Moreover, since µ(0), u(0), v(0) = (µ0 , θ[λℓ,a] , 0),

it follows from Theorem 5.6 that

˙ = ϕv + O(s) = e qs := v(s)

·

0 (µ0 m−cθ[λℓ,a] )

+ O(s) ≫ 0,

s ↓ 0.

(7.16)

Similarly, setting ˙ v(s) ˙ , (ps , qs ) := u(s),

s > 0,

(6.31) can be rewritten in the form (ps )′ = λℓ − 2au(s) − bv(s) ps − bu(s)qs , (qs )′ = −cv(s)ps + µ(s)m − 2dv(s) − cu(s) qs + µ(s)mv(s). ˙

(7.17)

In the competing species model, we have that −bu(s) < 0, −cv(s) < 0, (6.35) and (6.36). Thus, (7.17) fits within the general setting of Section 7.1. In particular, thanks to Proposition 2.1, we find from the first equation of (7.17) that, for each sufficiently small s > 0, ps = R−[λℓ−2au(s)−bv(s)] −bu(s)qs ≪ 0.

Therefore, there exists ε > 0 such that

ps ≪ 0 and qs ≫ 0 for each s ∈ [0, ε].

(7.18)

Suppose µ(s) = µ0 for each s ∈ [0, L]. Then, (7.17) becomes into (6.38) and, due to (6.32), (ps , qs ) = (0, 0). Thus, thanks to Theorem 7.1, for each s ∈ [0, L], either ps ≫ 0 and qs ≪ 0, or ps ≪ 0 and qs ≫ 0. Thanks to (7.18), necessarily ps ≪ 0 and qs ≫ 0 for each s ∈ [0, L].

(7.19)

Indeed, since s → (ps , qs ) is analytic, if (7.19) is not satisfied, then, due to (6.37), there is some value of s, say s˜ ∈ (0, L] where ps˜ < 0, qs˜ > 0, and, e.g., ps˜ ≪ 0 fails. Due to Theorem 7.1, this implies ps˜ ≪ 0 and qs˜ ≫ 0, which is a contradiction. Thus, (7.19) holds true. Consequently, thanks to Theorem 7.3, the principal characteristic multiplier of (µ(s), u(s), v(s)), ν2 (s), equals 1 for each s ∈ [0, L]. Therefore, if µ˙ = 0, then ν˙ 2 = 0 and, hence, all the coexistence states of Cλµ are neutrally stable. When µ˙ = 0, the following result is satisfied.


449

T HEOREM 7.7. Suppose µ˙ = 0 in [0, L]. Then, the set S := s ∈ (0, L): µ(s) ˙ =0

(7.20)

is finite (possibly empty), each s ∈ S is a zero of finite order of µ, ˙ and S = s ∈ (0, L): ν2 (s) = 1 .

(7.21)

Moreover,

and

µ(s) ˙ 1 − ν2 (s) > 0,

s ∈ (0, L) \ S,

ps ≪ 0 and qs ≫ 0 whenever µ(s) ˙ 0.

(7.22)

(7.23)

P ROOF. The fact that S is, at most, finite and that each s ∈ S has finite order—as a zero of µ—are ˙ consequences from the fact that µ˙ is real analytic. Now, we shall prove (7.21). Pick s ∈ S. Then, (ps , qs ) satisfies (6.38) and, due to (6.32), (ps , qs ) = (0, 0). Thus, thanks to Theorem 7.1, ps ≪ 0 and qs ≫ 0, or ps ≫ 0 and qs ≪ 0. In any of these cases, we find from Theorem 7.3 that λ = 0 is the principal characteristic exponent of (µ(s), u(s), v(s)) and, hence, ν2 (s) = 1. To prove the converse inclusion, let s ∈ (0, L) such that ν2 (s) = 1. Then, thanks to Theorem 7.3, there exists a T -periodic pair (P , Q) with P ≫ 0 and Q ≪ 0 such that

P ′ = λℓ − 2au(s) − bv(s) P − bu(s)Q, Q′ = −cv(s)P + µ(s)m − 2dv(s) − cu(s) P .

Now, choose a sufficiently small ε > 0 so that the auxiliary pair (U, V ) := (P − εps , Q − εqs ), satisfy U ≫ 0 and V ≪ 0. Thanks to (7.17) and (7.24) we have that

U ′ = λℓ − 2au(s) − bv(s) U − bu(s)V , V ′ = −cv(s)U + µ(s)m − 2dv(s) − cu(s) V − ε µ(s)mv(s). ˙

Assume µ(s) ˙ > 0. Then, since εmv(s) > 0, the pair (U, V ) satisfies

U ′ = λℓ − 2au(s) − bv(s) U − bu(s)V , V ′ < −cv(s)U + µ(s)m − 2dv(s) − cu(s) V ,

(7.24)

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J. López-Gómez

and, hence, thanks to Theorem 7.4(a), ν2 (s) < 1, which is a contradiction. Assume µ(s) ˙ < 0. Then, (U, V ) satisfies

U ′ = λℓ − 2au(s) − bv(s) U − bu(s)V , V ′ > −cv(s)U + µ(s)m − 2dv(s) − cu(s) V ,

and, due to Theorem 7.4(b), ν2 (s) > 1, which is a contradiction again. Consequently, µ(s) ˙ = 0 and, therefore, (7.21) holds true. Now, pick s˜ ∈ S. Thanks to (6.32), it follows from Theorem 7.1 that some of the following alternatives occurs: 1. ps˜ ≫ 0 and qs˜ ≪ 0. 2. ps˜ ≪ 0 and qs˜ ≫ 0. Assume alternative 1 occurs. As s˜ is an isolated zero of µ(s), ˙ there exists ε > 0 such that ps = u(s) ˙ ≫ 0 and qs = v(s) ˙ ≪ 0 for each s ∈ (˜s − ε, s˜ + ε), and µ˙ −1 (0) ∩ (˜s − ε, s˜ + ε) ∩ (0, L) = {˜s }. Thus, for each s ∈ J := (0, L) ∩ (˜s − ε, s˜ + ε) \ {˜s } ,

either µ(s) ˙ > 0, or µ(s) ˙ < 0. Suppose µ(s) ˙ > 0. Then,

(ps )′ = λℓ − 2au(s) − bv(s) ps − bu(s)qs , (qs )′ > −cv(s)ps + µ(s)m − 2dv(s) − cu(s) qs ,

(7.25)

and it follows from Theorem 7.4(b) that ν2 (s) > 1. Hence, µ(s)(1 ˙ − ν2 (s)) < 0. Now, suppose µ(s) ˙ < 0. Then,

(ps )′ = λℓ − 2au(s) − bv(s) ps − bu(s)qs , (qs )′ < −cv(s)ps + µ(s)m − 2dv(s) − cu(s) qs ,

(7.26)

and it follows from Theorem 7.4(a) that ν2 (s) < 1. Hence, µ(s)(1 ˙ − ν2 (s)) < 0. Therefore, the following condition is satisfied µ(s) ˙ 1 − ν2 (s) < 0,

s ∈ (0, L) ∩ (˜s − ε, s˜ + ε) \ {˜s } ,

(7.27)

for each s˜ ∈ S satisfying alternative 1. Now, suppose s˜ ∈ S satisfies alternative 2. As s˜ is an isolated zero of µ(s), ˙ there exists ε > 0 such that ps = u(s) ˙ ≪ 0 and qs = v(s) ˙ ≫ 0 for each s ∈ (˜s − ε, s˜ + ε), and µ˙ −1 (0) ∩ (˜s − ε, s˜ + ε) ∩ (0, L) = {˜s }.


451

Thus, for each s ∈ J := (0, L) ∩ (˜s − ε, s˜ + ε) \ {˜s } ,

either µ(s) ˙ > 0, or µ(s) ˙ < 0. Suppose µ(s) ˙ > 0. Then,

(−ps )′ = λℓ − 2au(s) − bv(s) (−ps ) − bu(s)(−qs ), (−qs )′ < −cv(s)(−ps ) + µ(s)m − 2dv(s) − cu(s) (−qs ),

(7.28)

with −ps ≫ 0 and −qs ≪ 0, and, hence, due to Theorem 7.4(a), ν2 (s) < 1. Thus, µ(s)(1 ˙ − ν2 (s)) > 0. Similarly, if µ(s) ˙ < 0, then, due to Theorem 7.4(b), ν2 (s) < 1. Therefore, condition (7.22) is satisfied for each s˜ ∈ S satisfying alternative 2. Now, suppose S = {sn : 1 n N},

0 < sn < sn+1 , 1 n N − 1;

the subsequent argument is easily adapted to cover the case when S is empty. Thanks to (7.19), for sufficiently small s > 0, ps ≪ 0 and qs ≫ 0. Moreover, either µ(s) ˙ > 0 for each s ∈ (0, s1 ), or µ(s) ˙ < 0 for each s ∈ (0, s1 ). Suppose µ(s) ˙ > 0 for each s ∈ (0, s1 ). Then, for sufficiently small s > 0, (−ps , −qs ) satisfies (7.28) and, hence, thanks to Theorem 7.4(a), ν2 (s) < 1. Actually, this is the interexchange stability principle between the semi-trivial state (µ, θ[λℓ,a] , 0) and the bifurcating coexistence state (µ(s), u(s), v(s)) as µ crosses the bifurcation value µ0 . Thanks to (7.21), necessarily ν2 (s) < 1 for each s ∈ (0, s1 ) and, therefore, µ(s) ˙ 1 − ν2 (s) > 0,

s ∈ (0, s1 ).

µ(s) ˙ 1 − ν2 (s) > 0,

s ∈ (0, s2 ) \ {s2 }.

(7.29)

Necessarily ps1 ≪ 0 and qs1 ≫ 0. Indeed, if ps1 ≫ 0 and qs1 ≪ 0, then (7.27) holds, which contradicts (7.29). Therefore, (7.30)

Reiterating this argument, (7.22) holds true. Now, suppose µ(s) ˙ < 0 for each s ∈ (0, s1 ). Then, (−ps , −qs ) satisfies

(−ps )′ = λℓ − 2au(s) − bv(s) (−ps ) − bu(s)(−qs ), (−qs )′ > −cv(s)(−ps ) + µ(s)m − 2dv(s) − cu(s) (−qs ),

(7.31)

and, hence, thanks to Theorem 7.4(b), ν2 (s) > 1. As in the previous case, this provides us with the inter-exchange stability principle between the semi-trivial state (µ, θ[λℓ,a] , 0) and the bifurcating coexistence state (µ(s), u(s), v(s)). Thanks to (7.21), ν2 (s) > 1 for each s ∈ (0, s1 ) and, therefore, (7.22) is as well satisfied. Arguing as above, the proof of (7.22) is concluded.

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J. López-Gómez

Note that, as a result from the previous analysis, we have that ps˜ ≪ 0 and qs˜ ≫ 0 for each s˜ ∈ S ∪ {0}.

(7.32)

Finally, let s1∗ , s2∗ ∈ S ∪ {0} such that µ(s) ˙ > 0,

s ∈ s1∗ , s2∗ .

Thanks to (7.32), ps ≪ 0 and qs ≫ 0 for each s > s1∗ sufficiently close to s1∗ . Thus, either ps ≪ 0 and qs ≫ 0 for each s ∈ (s1∗ , s2∗ ), or there exist s0 ∈ (s1∗ , s2∗ ) and t ∈ R such that ps0 0 and qs0 0 and either ps0 (t) = 0, or qs0 (t) = 0. Since ˙ 0 )mv(s0 ) > 0, −cv(s0 )ps0 + µ(s we find from Proposition 2.1 applied to the second equation of (7.17) that qs0 ≫ 0. Thus, −bu(s0 )qs0 < 0 and, thanks again to Proposition 2.1, the first equation of (7.17) gives ps0 ≪ 0, which is impossible. Therefore, for each s ∈ (s1∗ , s2∗ ), ps ≪ 0 and qs ≫ 0, which concludes the proof of (7.23). The proof of the theorem is completed.

7.4. Some bifurcation diagrams µ

In order to study the curves Cλ we did carried out some numerical investigations in [12], where we solved (1.2) using spectral collocation methods coupled with path-following techniques. To compute T -periodic solutions of (1.2), the most appropriate set of basis functions to use is trigonometric polynomials, and these were used to generate the bifurcaµ tion diagrams of Figs. 17 and 18. Fig. 17 shows the approximated components Cλ for the following problems, with T = 1 and a = d = 1, (a) µ = 3.32, m(t) = 1 + 0.7 sin(2πt), ℓ(t) = 1 + 0.7 cos(2πt), b(t) = 0.9 + 0.7 sin(2πt + π/4), c(t) = 0.9 + 0.7 cos(2πt + π/4). (b) µ = 3.32, m(t) = 1 + 0.7 sin(2πt), ℓ(t) = 1 + 0.7 cos(2πt), b(t) = 0.9 + 0.7 sin(2πt), c(t) = 0.9 + 0.7 cos(2πt). (c) µ = 5.00, ℓ(t) = m(t) = 1 + 0.7 sin(2πt), b(t) = c(t) = 0.9 + 0.7 sin(2πt). (d) µ = 3.32, ℓ(t) = m(t) = 1 − 0.7 sin(2πt), b(t) = c(t) = 1.1 + 0.7 sin(2πt). Given a µ > 0, we have plotted the parameter λ along the horizontal axis, and along the 2 vertical one we give the value u

2 + v 2 , where : ; ;∞ 2

f 2 = < c j

j =1

if f = c1 +

∞ c2j sin(2πj t) + c2j +1 cos(2πj t) . j =1

This particular choice of norm makes it easy to distinguish between the semi-trivial states (λ, µ, θ[λℓ,a] , 0) and (λ, µ, 0, θ[µm,d] ), which would otherwise cross near the bifurcation points and confuse the picture. Stable solutions are represented by continuous lines, unstable ones by dashed lines. Several different cases are shown according to the nature of the


Fig. 17. Bifurcation diagrams for µ > 0 constant.

Fig. 18. Two examples with both semi-trivial states neutrally stable.

453

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J. López-Gómez µ

bifurcation to coexistence states from the semi-trivial solutions. In all cases, Cλ possesses at most a finite number of hysteresis and turning points and the stability of the coexistence states change according to Theorem 7.7. Fig. 18 shows some of the possible situations when both semi-trivial states are neutrally stable. In some cases, (1.2) possesses a coexistence states, while in others it does not. Fig. 18 shows the following two cases, with T = 1 and a = d = 1: (a) µ = 5.365, m(t) = 1 + 0.7 sin(2πt), ℓ(t) = 1 + 0.7 cos(2πt), b(t) = c(t) = 0.9 + 0.7 sin(2πt). (b) µ = 5.365, m(t) = 1 + 0.7 sin(2πt), ℓ(t) = 1 + 0.7 cos(2πt), b(t) = 0.9 + 0.7 sin(2πt), c(t) = 0.9 + 0.7 cos(2πt). Case (a) provides us with an example where both semi-trivial states are neutrally stable and (1.2) does not admit a coexistence state. It should be noted that, thanks to the discussion µ closing Section 7.3, (1.2) cannot admit a further coexistence state outside Cλ . Case (b) provides us with an example where both semi-trivial states are neutrally stable and (1.2) possesses a unique coexistence state, which is stable.

7.5. Dynamics of (1.1) Thanks to the theory developed by P. de Mottoni and A. Schiaffino [29], all solutions of (1.1) must approach a T -periodic solution of (1.2) as time passes by. Combining this information with the theory developed in this section, one can easily obtain the validity of the following assertions. Subsequently, we shall denote by (u(t), v(t)) the unique positive solution of (1.1). 1. If λ 0 and µ 0, then limt↑∞ (u(t), v(t)) = (0, 0). 2. If λ > 0 and µ 0, then lim u(t), v(t) = (θ[λℓ,a] , 0).

t↑∞

(7.33)

3. If λ 0 and µ > 0, then lim u(t), v(t) = (0, θ[µm,d] ).

t↑∞

(7.34)

4. If λ > 0,

0 T

0

T


(7.38)

then (1.2) possesses a stable coexistence state. Moreover, if n 1 stands for its number of stable coexistence states, then (1.2) possesses n − 1 unstable coexistence states and a finite number of neutrally stable coexistence states. Furthermore, there exists a coexistence state (u0 , v0 ) for which (7.36) holds true. 9. If 1 0 0,

γ > 0,

(8.2)

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J. López-Gómez

which is a non-cooperative periodic system. As a result, the nice monotonicity properties available for competing species and symbiotic models are lost, and, in general, the compoµ nents of coexistence states Cλµ and Cλ bifurcating from the semi-trivial states are far from being analytic curves, except in a neighborhood of their bifurcation points from the semitrivial states. Nevertheless, in strong contrast with the classical cases of competition and symbiosis, in this model the existence of a coexistence state is characterized by the linear stability of the semi-trivial states.

8.1. Characterizing the existence of coexistence states Subsequently, we suppose m ≫ 0 and d ≫ 0. Then, 1 lim µ↑∞ T

T

0

b(t)θ[µm,d] (t) dt = ∞,

since lim

µ↑∞

θ[µm,d] m = , µ d

and, hence, for each λ > 0 there exists a unique value of µ, µ∗ > 0, such that 1 λ= T

0

T

b(t)θ[µ∗ m,d] (t) dt.

(8.3)

The following result is satisfied. T HEOREM 8.1. The following conditions are equivalent: (a) Problem (1.2) possesses a coexistence state. (b) λ > 0 and any semi-trivial state of (1.2) is linearly unstable. (c) The parameters (λ, µ) satisfy 1 T (bθ[µm,d] ) , λ > max 0, T 0

µ>

1 T

0

T

(cθ[λℓ,a] ),

(8.4)

where, for each µ ∈ R, θ[µm,d] ∈ CT1 stands for the maximal non-negative solution of u′ = λℓu − au2 . In other words, θ[µm,d] ≫ 0 if µ > 0, while θ[µm,d] = 0 if µ 0. Moreover, for each λ > 0, the component Cλµ of coexistence states constructed in Theorem 5.4 is bounded in R × CT × CT and it satisfies (λ, µ0 , θ[λℓ,a] , 0), (λ, µ∗ , 0, θ[µ∗ m,d] ) ∈ C¯ λµ ,

(8.5)

where µ∗ is the unique value of µ satisfying (8.3). Therefore, the µ-projection of Cλµ is the interval (µ0 , µ∗ ).


457

P ROOF. Suppose (λ, µ, u0 , v0 ) is a coexistence state of (1.2). Then, dividing by u0 the u-equation and integrating in [0, T ] gives λ=

1 T

T

(au0 + bv0 ) > 0.

0

So, λ > 0 is necessary for the existence. Subsequently, we will assume that λ > 0. Then, thanks again to the u-equation, u′0 = λℓu0 − au20 − bu0 v0 < λℓu0 − au20 , and, due to Proposition 2.6, u0 ≪ θ[λℓ,a] .

(8.6)

So, dividing by v0 the v-equation, integrating in [0, T ], and using (8.6) shows that µ=

1 T

T 0

(cu0 + dv0 ) >

1 T

T


0

since c < 0. Thus, the second estimate of (8.4) is necessary for the existence. Now, suppose µ > 0. Then, θ[µm,d] ≫ 0, v0′ = µmv0 − dv02 − cu0 v0 > µmv0 − dv02 , and, it is apparent from Proposition 2.6 that v0 ≫ θ[µm,d] .

(8.7)

Consequently, 1 λ= T

T 0

1 (au0 + bv0 ) > T

0

T

b(t)θ[µm,d] (t) dt

and, therefore, (8.4) is necessary for the existence of a coexistence state. It should be noted that (8.4) provides us with the set of values of (λ, µ) with λ > 0 for which any semi-trivial state of (1.2) is linearly unstable, i.e., (b) and (c) are equivalent and we have just seen that (a) implies (c). Now, fix λ > 0 and pick (µ, u0 , v0 ) ∈ Cλµ . Then, (8.7) is satisfied. Moreover, at any time t0 where v0 (t0 ) = (v0 )M , we have that v0′ (t0 ) = 0 and, hence, it follows from the v-equation that µm(t0 ) − d(t0 )v0 (t0 ) − c(t0 )u0 (t0 ) = 0.

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J. López-Gómez

Thus, thanks to (8.6), −c(t0 ) m(t0 ) µ+ u(t0 ) d(t0 ) d(t0 ) m −c |µ| + θ[λℓ,a] , d M d M

v0 CT = v0 (t0 ) =

and, consequently, Cλµ is bounded. Now, it is apparent that Theorem 5.4 concludes the proof. Indeed, the µ-projection of Cλµ must be the interval (µ0 , µ∗ ) and, therefore, (8.4) is sufficient for the existence of a coexistence state of (1.2).

8.2. Dynamics of (1.1) Thanks to the theory developed in [25], the following results, whose proofs are omitted here, are satisfied. Subsequently, we shall denote by (u(t), v(t)) the unique positive solution of (1.1). 1. If (0, 0) is linearly stable, i.e., if λ 0 and µ 0, then limt↑∞ (u(t), v(t)) = (0, 0). T 2. If λ > 0 and (θ[λℓ,a] , 0) is linearly stable, i.e., µ T1 0 c(t)θ[λℓ,a] (t) dt, then limt↑∞ (u(t), v(t)) = (θ[λℓ,a] , 0). T 3. If µ > 0 and (0, θ[µm,d] ) is linearly stable, i.e., λ T1 0 b(t)θ[µm,d] (t) dt, then limt↑∞ (u(t), v(t)) = (0, θ[µm,d] ). As far as to the problem of the uniqueness, multiplicity and stability of the coexistence states things are much more difficult to deal with than in the competing species and symbiotic prototype counterparts, since the linearization of (1.2) at any coexistence state has a non-cooperative structure—the off-diagonal entries of the coupling matrix of the system have contrary signs—and for such problems a general comparison principle within the spirit of Theorems 6.1 and 7.1 is far from being available. Therefore, the problem of ascertaining the signs of the Floquet exponents of a given coexistence state is extremely difficult to treat with. Quite strikingly, although the one-dimensional predator–prey model with diffusion under homogeneous Dirichlet boundary conditions is known to admit at most a coexistence state [26,10,18], there are choices of the several coefficient functions in the setting of (1.2) for which the predator–prey model admits two 2T -periodic coexistence states and one unstable T -periodic coexistence state [5,8,18]. Hence, the uniqueness result for the onedimensional elliptic model does not extend in general to the periodic prototype models, however both prototypes, viewed as abstract non-cooperative systems, possess the same operator structure [18]. In [25] were obtained some persistence results in the presence of coexistence states, and in [5] it was shown that if the product of the interactions b and c is sufficiently small, then the model admits at most a coexistence state, though we refrain of giving more details here. Actually, this uniqueness principle holds true in the general case when b and c are arbitrary. The details will appear elsewhere.


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References [1] S. Ahmad, On the non-autonomous Volterra–Lotka competition equations, Proc. Amer. Math. Soc. 117 (1993), 199–204. [2] S. Ahmad and A.C. Lazer, Asymptotic behaviour of solutions of periodic competition diffusion systems, Nonlinear Anal. 13 (1989), 263–284. [3] C. Alvárez and A.C. Lazer, An application of topological degree to the periodic competing species problem, J. Austral. Math. Soc. Ser. B 28 (1986), 202–219. [4] H. Amann, Fixed point equations and nonlinear eigenvalue problems in ordered Banach spaces, SIAM Rev. 18 (1976), 620–709. [5] Z. Amine and R. Ortega, A periodic prey-predator system, J. Math. Anal. Appl. 185 (1994), 477–489. [6] M.G. Crandall and P.H. Rabinowitz, Bifurcation from simple eigenvalues, J. Funct. Anal. 8 (1971), 321–340. [7] J.M. Cushing, Two species competition in a periodic environment, J. Math. Biol. 10 (1980), 385–390. [8] E.N. Dancer, Turing instabilities for systems of two equations with periodic coefficients, Differential Integral Equations 7 (1994), 1253–1264. [9] E.N. Dancer, Bifurcation from simple eigenvalues and eigenvalues of geometric multiplicity one, Bull. London Math. Soc. 34 (2002), 533–538. [10] E.N. Dancer, J. López-Gómez and R. Ortega, On the spectrum of some linear noncooperative elliptic systems with radial symmetry, Differential Integral Equations 8 (1995), 515–523. [11] M. Delgado, J. López-Gómez and A. Suárez, On the symbiotic Lotka–Volterra model with diffusion and transport effects, J. Differential Equations 160 (2000), 175–262. [12] J.C. Eilbeck and J. López-Gómez, On the periodic Lotka–Volterra competition model, J. Math. Anal. Appl. 210 (1997), 58–87. [13] J.E. Furter, J.C. Eilbeck and J. López-Gómez, Coexistence in the competition model with diffusion, J. Differential Equations 107 (1994), 96–139. [14] J.K. Hale and A. Somolinos, Competition for fluctuating nutrient, J. Math. Biol. 18 (1983), 255–280. [15] P. Hess and A.C. Lazer, On an abstract competition model and applications, Nonlinear Anal. 16 (1991), 917–940. [16] M.A. Krasnosel’skii, Translations Along Trajectories of Differential Equations, Math. Monogr. of the AMS, Amer. Math. Soc., Providence, RI (1968). [17] J. López-Gómez, Structure of positive solutions in the periodic Lotka–Volterra competition model when a parameter varies, Nonlinear Anal. 27 (1996), 739–768. [18] J. López-Gómez, A bridge between Operator Theory and Mathematical Biology, Fields Inst. Commun. 25 (2000), 383–397. [19] J. López-Gómez, Spectral Theory and Nonlinear Functional Analysis, Pitman Res. Notes Math. Ser., Vol. 426, Chapman & Hall/CRC, Boca Raton, FL (2001). [20] J. López-Gómez, Classifying smooth supersolutions in a general class of elliptic boundary value problems, Adv. Differential Equations 8 (2003), 1025–1042. [21] J. López-Gómez and M. Molina-Meyer, The maximum principle for cooperative weakly coupled elliptic systems and some applications, Differential Integral Equations 7 (1994), 383–398. [22] J. López-Gómez and M. Molina-Meyer, Singular perturbations in Economy and Ecology. The effect of strategic symbiosis in random competitive environments, Adv. Math. Sci. Appl. 14 (2004), 87–107. [23] J. López-Gómez and M. Molina-Meyer, Symbiosis in Competitive environments, Res. Inst. Math. Sci. Kyoto 12 (2003), 118–141. [24] J. López-Gómez and M. Molina-Meyer, Bounded components of positive solutions of abstract fixed point equations: mushrooms, loops and isolas, J. Differential Equations 209 (2005) 416–441. [25] J. López-Gómez, R. Ortega and A. Tineo, The periodic predator–prey Lotka–Volterra model, Adv. Differential Equations 1 (1996), 403–423. [26] J. López-Gómez and R. Pardo, Existence and uniqueness for the predator-prey model with diffusion: The scalar case, Differential Integral Equations 6 (1993), 1025–1031. [27] J. Mawhin, Les héritiers de Pierre-François Verhulst: une population dynamique, Acad. Roy. Belg. Bull. Cl. Sci. (6) 13 (2003), 349–378.

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[28] J. Mawhin, The legacy of P.F. Verhulst and V. Volterra in population dynamics, The First 60 Years of Nonlinear Analysis of Jean Mawhin, M. Delgado, J. López-Gómez, R. Ortega and A. Suárez, eds., World-Scientific (2004). [29] P. de Mottoni and A. Schiaffino, Competition systems with periodic coefficients: a geometric approach, J. Math. Biol. 11 (1981), 319–335. [30] R. Ortega and A. Tineo, On the number of positive solutions for planar competing Lotka–Volterra systems, J. Math. Anal. Appl. 193 (19945), 975–978. [31] P.H. Rabinowitz, Some global results for nonlinear eigenvalue problems, J. Funct. Anal. 7 (1971), 487–513. [32] H. Smith, Periodic competitive differential equations and the discrete dynamics of competitive maps, J. Differential Equations 64 (1986), 165–194. [33] H. Smith, Periodic solutions of periodic competitive and cooperative systems, SIAM J. Math. Anal. 17 (1986), 1289–1238. [34] A. Tineo, Existence of global coexistence state for periodic competition diffusion systems, Nonlinear Anal. 19 81992), 335–344. [35] A. Tineo, An iterative scheme for the N -competing species problem, J. Differential Equations (1995), 1–15. [36] F. Zanolin, Permanence and positive periodic solutions of Kolmogorov competing species models, Results Math. 21 (1992), 224–250.

CHAPTER 6

Nonlocal Initial and Boundary Value Problems: A Survey S.K. Ntouyas Department of Mathematics, University of Ioannina, 451 10 Ioannina, Greece E-mail: [email protected]

Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1. Examples of nonlocal conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Nonlocal initial value problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Existence and uniqueness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Nonlocal boundary value problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. First-order three-point boundary value problems . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Second-order three-point boundary value problems . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Third-order three-point boundary value problems . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. m-point boundary value problems reduced to three-point boundary value problems . . . . . . . . 3.5. Nonresonance results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6. Results at resonance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.7. m-point boundary value problems reduced to four-point boundary value problems . . . . . . . . . 3.8. The general case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.9. Positive solutions of some nonlocal boundary value problems . . . . . . . . . . . . . . . . . . . . 3.10. Positive solutions of nonlocal boundary value problems with dependence on the first-order derivative . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.11. Positive solutions of nonlocal problems for p-Laplacian . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .


463 463 465 465 469 470 475 484 489 490 498 505 513 518 542 547 554

Nonlocal initial and boundary value problems

463

1. Introduction The evolution of a physical system in time is described by an initial value problem, i.e. a differential equation (ordinary or partial) and an initial condition. In many cases it is better to have more initial information. The local condition is replaced then by a nonlocal condition, which gives better effect than the local initial condition, since the measurement given by a nonlocal condition is usually more precise than the only one measurement given by a local condition. The study of initial value problems (IVP for short) with nonlocal conditions is of significance, since they have applications in problems in physics and other areas of applied mathematics. Conditions of this type can be applied in the theory of elasticity with better effect than the initial or Darboux conditions. Consider the differential equation x ′ (t) = f t, x(t) ,

x(t0 ) = x0 ,

t 0, x(t) ∈ Rn .

(1.1)

The fundamental assumption used when modeling a system using a differential equation is that the time rate at time t, given as x ′ (t), depends only on the current status at time t, given as f (t, x(t)). Moreover, the initial condition is given in the form x(t0 ) = x0 . In applications, this assumption and the initial condition should be improved so that we can model the situations more accurately and therefore derive better results. One improvement of Eq. (1.1) is to assume that the time rate depends not only on the current status, but also on the status in the past; that is, the past history will contribute to the future development, or, there is a time-delay effect. Another improvement of Eq. (1.1) is the so-called differential equations with nonlocal conditions. That is, we extend the initial condition (also called local condition) x(t0 ) = x0 to the following nonlocal condition x(t0 ) + g x(·) = x0 ,

(1.2)

where x(·) denotes a solution (that is, x(·) is a function) and g is a mapping defined on some space consisting of certain functions. (Of course, g may be identically zero, in which case it reduces to the local condition or initial condition x(t0 ) = x0 .) The advantage of using nonlocal conditions is that measurements at more places can be incorporated to get better models.

1.1. Examples of nonlocal conditions Let p ∈ N and let t1 , t2 , . . . , tp be given real numbers such that t0 < t1 < t2 < · · · < tp t0 + α.

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S.K. Ntouyas

Then g can be defined by the formula

g(x) =

p

ci x(ti ),

(1.3)

i=1

where ci , i = 1, 2, . . . , p are given constants or by the relation g(x) =

p ci i=1

ǫi

ti

x(t) dt,

(1.4)

ti −ǫi

where ǫi , i = 1, 2, . . . , p are given positive constants such that: ti−1 < ti − ǫi < ti , i = 1, 2, . . . , p. Particularly, if x0 = 0, p = 1, t1 = t0 + α then u(t0 ) = −c1 x(t0 + α)

−c1 and x(t0 ) = ǫ1

t0 +α

x(t) dt

t0 +α−ǫ1

respectively. The constants ci , i = 1, 2, . . . , p in the nonlocal condition (1.3) can satisfy the inequalities |ci | > 1, i = 1, 2, . . . , p. It is remarkable that if ci = 0, i = 1, 2, . . . , p the results can be applied to kinematics to determine the evolution t → x(t) of the location of a physical object for which we do not know the positions x(0), x(t1 ), . . . , x(tp ), but we know that the nonlocal condition of (1.3) holds. Consequently, to describe some physical phenomena, the nonlocal condition can be more useful than the standard initial condition x(0) = x0 . From the nonlocal condition of (1.3) it is clear that when ci = 0, i = 1, 2, . . . , p we have the classical initial condition. Let us have one more example for partial differential equations. In the theory of diffusion and heat conduction one can encounter a mathematical model of the form: Lx + c(w, t)x = f (w, t), x(w, t) = φ(w, t), x(w, 0) +

N k=1

t ∈ Ω, 0 < t < T ,

w ∈ ∂Ω, 0 < t < T ,

βk (w)x(w, tk ) = ψ(w),

w ∈ Ω and tk ∈ (0, T ], k = 1, . . . , N,

where Ω is a bounded region in Rn and L is a uniformly parabolic operator with continuous and bounded coefficients. It represents the diffusion phenomenon of a small amount of gas in a transparent tube. If there is very little gas at the initial time, the measurement x(w, 0) of the amount of the gas in this instant may be less precise that the measurement x(w, 0) + N k=1 βk (x)x(w, tk ) of the sum of the amount of this gas.


465

2. Nonlocal initial value problems Here, we consider the following initial value problem x ′ = f (t, x), t ∈ I := [t0 , T ], x ∈ Rn , x(t0 ) + g x(·) = x0 ,

(2.1) (2.2)

where x(·) denotes a solution and g is a mapping acting on some space of functions defined on [0, T ]. Since g(x(·)) in Eq. (2.2) is defined on the interval [t0 , T ] rather than a single point, the IVP (2.1)–(2.2) is called an “initial value problem with nonlocal conditions” or “nonlocal initial value problem”, and can be applied with better effect than just using the classical initial value problem with x(t0 ) = x0 , because new measurements at more places are allowed, thus more information is available. For the IVP (2.1)–(2.2), observe that if x is a solution, then x(t) = x(t0 ) +

t

t0

f s, x(s) ds = x0 − g x(·) +

t t0

f s, x(s) ds.

(2.3)

On the other hand, assume that a function x on the interval [t0 , T ] satisfies (2.3). For this fixed function x, g(x(·)) is a fixed element in Rn , hence dtd g(x(·)) = 0. Therefore, if we take a derivative in t, then x is a solution of IVP (2.1)–(2.2). That is, we conclude that a continuous function x is a solution of the IVP (2.1)–(2.2) if and only if x(t) = x0 − g x(·) +

t

t0

f s, x(s) ds.

This leads to a mapping P on C([t0 , T ], Rn ) such that (P x)(t) = x0 − g x(·) +

t

t0

f s, x(s) ds.

2.1. Existence and uniqueness Motivated by physical problems, Byszewski and Lakshmikantham [12] considered the following nonlocal IVP x ′ = f (t, x), t ∈ I := [t0 , b], x(t0 ) + g t1 , t2 , . . . , tp , x(·) = x0 ,

(2.4) (2.5)

where t0 < t1 < · · · < tp < b, p ∈ N, x = (x1 , x2 , . . . , xn ) ∈ Ω, x0 = (x10 , . . . , xn0 ) ∈ Ω, f = (f1 , . . . , fn ) ∈ C(I × Ω, E), g = (g1 , . . . , gn ) : I p × Ω → E, g(t1 , . . . , tp , ·) ∈

466

S.K. Ntouyas

C(Ω, E) and Ω ⊂ E is a suitable subset. The symbol g(t1 , . . . , tp , x(·)) is used in the sense that in the place of · we can substitute only elements of the set {t1 , . . . , tp }. Let E = E1 ×E2 ×· · ·×En , where Ei , i = 1, 2, . . . , n are Banach spaces with norm · . T HEOREM 2.1. Assume that: (i) E is a Banach space with norm · , x0 ∈ E, and Ω := B(x0 , r) = {y: y − x0

r} ⊂ E. (ii) There exist constants Li > 0, i = 1, . . . , n such that fi (s, y) − fi (s, y) ¯ Li y − y

¯

for (s, y), (s, y) ¯ ∈ I × Ω, i = 1, . . . , n. (iii) There exist constants Ki > 0, i = 1, . . . , n such that

(iv)

gi (t1 , . . . , tp , z) − gi (t1 , . . . , tp , z¯ ) Ki z − z¯ ,

√ (Md + N ) n r, where Mi =

sup (s,y)∈I ×Ω

and d = b − t0 , i=1,...,n

√ (Ld + K) n < 1,

fi (s, y),

Ni = sup g(t1 , . . . , tp , z),

L = max Li ,

M = max Mi ,

z, z¯ ∈ Ω, i = 1, . . . , n.

i=1,...,n

z∈Ω

i = 1, . . . , n,

K = max Ki , i=1,...,n

N = max Ni . i=1,...,n

Then there exists a unique solution on the nonlocal IVP (2.4)–(2.5). P ROOF. It is easy to see, that problem (2.4)–(2.5) is equivalent to the integral equation x(t) = x0 − g t1 , . . . , tp , x(·) +

t

f s, x(s) ds,

t0

t ∈ I,

which is also equivalent to the following system of the integral equations xi (t) = xi0 − gi t1 , . . . , tp , x(·) +

t t0

fi s, x(s) ds,

We introduce the operator T given by (T y)(t) := (T1 y)(t), . . . , (Tn y)(t) ,

t ∈ I,

t ∈ I, i = 1, . . . , n.


467

where (Ti y)(t) = xi0 − gi t1 , . . . , tp , x(·) +

t

t0

fi s, x(s) ds,

t ∈ I, i = 1, . . . , n.

Let X := C(I, Ω). We will show that the operator T maps X into X. We observe that

T y − x0 = =

8 n i=1

Ti y − xi0

8 n =

91/2

> 2 sup(Ti y)(t) − xi0

i=1 t∈I

8 n

sup

i=1 t∈I

2

8 n =

91/2

91/2 2 fi s, y(s) ds + gi t1 , . . . , tp , y(·)

t

t0

>2 sup |t − t0 |Mi + Ni

i=1 t∈I

91/2

√ (Md + N ) n r,

for y ∈ X. Therefore T : X → X. Next, we will show that T is a contraction on X. We have:

T y − T y

¯ =

8 8

n i=1

Ti y − Ti y

¯

2

91/2

n = >2 = sup(Ti y)(t) − (Ti y)(t) ¯

8

8

i=1 t∈I

91/2

t n ds sup fi s, y(s) − fi s, y(s) ¯ i=1 t∈I

t0

+ gi t1 , . . . , tp , y(·) − gi t1 , . . . , tp , y(·) ¯

2 91/2

n = >2 ¯ ¯ + Ki y(·) − y(·) sup |t − t0 |Li y(s) − y(s) i=1 t∈I

√ (Ld + K) n y − y

¯

91/2

468

S.K. Ntouyas

for arbitrary y, y¯ ∈ X which proves that T is a contraction. Hence, by Banach fixed point theorem, in space X there is the only one fixed point of T and this point is the solution of the nonlocal problem (2.4)–(2.5). So, the proof of the theorem is complete. Consider now a nonlocal IVP with a special form of the nonlocal initial condition, x ′ (t) = f t, x(t) ,

x(0) +

p k=1

t ∈ J := [0, T ],

(2.6)

ck x(tk ) = x0 ,

(2.7)

where 0 < t1 < · · · < tp T , f : J × E → E is a given function and E is a Banach space with norm · , x0 ∈ E, ck = 0 and p ∈ N. By X we denote the Banach space C(J, E) with the standard norm · X .

p D EFINITION 2.2. Assume that k=1 ck = −1. A function x ∈ X is called a mild solution of (2.6)–(2.7) if satisfies the integral equation 8

x(t) = A x0 − where A = (1 +

p k=1

ck

tk

0

p

9 t f s, x(s) ds + f s, x(s) ds, 0

−1 k=1 ck ) .

D EFINITION 2.3. A function x : J → E is said to be a classical solution of the nonlocal problem (2.6)–(2.7) if (i) x is continuous on J and continuously differentiable on J , (ii) x ′ (t) = f (t, x(t)) for t ∈ J , and p (iii) x(0) + k=1 ck x(tk ) = x0 .

p It is easy to see that if f ∈ C(J ×E, E) and k=1 ck = −1, then x is the unique classical solution of the nonlocal problem (2.6)–(2.7) if and only if x is the unique mild solution of this problem. T HEOREM 2.4. Assume that: (1) f : J × E → E is continuous with respect to the first variable on J and there is L > 0 such that 2 f (t, z) − f (t, z¯ ) L

z − z¯

i=1

for pt ∈ J , z, z¯ ∈ E. (2) k=1 ck = −1. p (3) 2LT (1 + |A k=1 ck |) < 1.


469

Then the nonlocal IVP (2.6)–(2.7) has a unique classical solution. P ROOF. Introduce the operator P by the formula 8 9 tk p ck f s, x(s) ds (P x)(t) = A x0 − k=1

+

0

t

0

f s, x(s) ds,

t ∈ J, x ∈ X.

It is easy to see that P : X → X. We will prove that P is a contraction on X. We have 8 p 9 tk = A − (P x)(t) − (P x)(t) ¯ f s, x(s) − f s, x(s) ¯ ds ck 0 k=1 t + f s, x(s) − f s, x(s) ¯ ds 0 p 9 8 ¯ X. 2LT 1 + A ck x − x

k=1

By (3) operator P is a contraction. Consequently by Banach fixed point theorem in space X there is only one fixed point of P and this fixed point is the unique classical solution of the nonlocal IVP (2.6)–(2.7). The proof of the theorem is complete.

Theorem 2.4 is a special case of Theorem 2.4 of [11], where the functional differential equation x ′ (t) = f (t, x(t), x(a(t))), t ∈ J was considered. We point out that when we model some situations from physics and other applied sciences, we typically end up with partial differential equations. In recent years there has been increasing interest in studying evolution differential equations with nonlocal conditions. The interested reader is referred to [10] and [86] and the references cited therein. 3. Nonlocal boundary value problems Let f : [0, 1] × R2 → R be a continuous function and let e : [0, 1] → R be a function in L1 [0, 1], ai ∈ R, ξi ∈ (0, 1), i = 1, 2, . . . , m − 2, 0 < ξ1 < ξ2 < · · · < ξm−2 < 1. We consider the following second-order ordinary differential equation x ′′ (t) = f t, x(t), x ′ (t) + e(t), t ∈ (0, 1) (3.1) subject to the following boundary value conditions: x(0) = 0,

x(1) =

m−2 i=1

ai x(ξi ).

(3.2)

470

S.K. Ntouyas

It is well known, that if a function x ∈ C 1 [0, 1] satisfies the boundary conditions (3.2) and all αi have the same sign then there exists an η ∈ [ξ1 , ξm−2 ] such that x(0) = 0,

x(1) = αx(η),

x(0) = 0,

x(1) = αx(η).

with α = m−2 k=1 ai . Accordingly, the problem of the existence of a solution for the boundary value problem (BVP for short) (3.1)–(3.2) can be studied via the existence of a solution of the following three-point BVP (3.3)

The above so-called “nonlocal” or “multi-point” or “m-point” BVP was initiated by Il’in and Moiseev in [43,44], motivated by the work of Bitsadze and Samarskii on nonlocal linear elliptic BVPs [7,8]. The nonlocal BVP for ordinary differential equations arise in a variety of different areas of applied mathematics and physics, and describe many phenomena in the applied mathematical sciences. For example, the vibrations of a guy wire of a uniform cross-section and composed on N parts of different densities can be set up as a multi-point BVP (see [83]); many problems in the theory of elastic stability can be handled by the method of multi-point problems (see [90]). We will study nonlocal BVP for first, second or higher order ordinary differential equations.

3.1. First-order three-point boundary value problems Given a, b, c ∈ R with a < b < c. Let J := [a, c] and Mn×n the Banach space of all constant matrices of order n with the norm

B = max |bi,j |. 1i,j n

Let C(J ), L1 (J ), and AC(J ) the usual Banach spaces of all continuous functions, all Lebesque integrable functions and all absolutely continuous functions with the norms

x L1 = x(t) dt,

x ∞ = max x(t) : t ∈ J , J

′

x AC = x ∞ + x L1 ,

respectively. For α = (α1 , . . . , αn ) ∈ Rn , define

α = max |αi |: i = 1, . . . , n .

Denote by X, Y and Z the Banach spaces C[J, Rn ] = {(x1 , . . . , xn ): xi ∈ C(J )}, L1 [J, Rn ] = {(x1 , . . . , xn ): xi ∈ L1 C(J )}, and AC[J, Rn ] = {(x 1 , . . . , xn ): xi ∈ AC(J )} with the norms x X = max{ xi ∞ : i = 2, . . . , n}, x Y = ni=1 xi L1 and x Z = max{ xi AC : i = 2, . . . , n} respectively.


471

D EFINITION 3.1. We say that f : J × Rn → Rn is a Carathéodory function if (i) f (·, u) is Lebesgue measurable on J for each u ∈ Rn , (ii) f (t, ·) is continuous on Rn for a.e. t ∈ J , (iii) for each r ∈ (0, ∞), there exists an hr ∈ L1 (J, Rn ) such that fi (t, u) (hr )i (t),

for a.e. t ∈ J, u r, i = 1, . . . , n.

We study the problem of existence of solutions for the three-point BVP x ′ (t) = f t, x(t) ,

for a.e. t ∈ J,

(3.4)

Mx(a) + N x(b) + Rx(c) = α,

(3.5)

where f : [a, c] × Rn → Rn is a Carathéodory function, M, N, R ∈ Mn×n , and α ∈ Rn are given. T HEOREM 3.2. Let f : [a, c] × Rn → Rn be a Carathéodory function and α ∈ Rn . Assume that (A1) M, N, R are constant square matrices of order n such that det(M + N + R) = 0. (A2) There exist functions p, r ∈ L1 (J ) such that f (t, u) p(t) u + r(t),

for a.e. t ∈ J and u ∈ Rn . Then the three-point BVP (3.4)–(3.5) has at least one solution in C(J, Rn ) provided Γ p 1 < 1, where Γ = max (M + N + R)−1 R , (M + N + R)−1 M , (M + N + R)−1 (N + R), (M + N + R)−1 (N + M) .

P ROOF. Let e(·) ∈ L1 (J, Rn ) and α ∈ Rn , x ∈ AC(J ) be such that x ′ (t) = e(t),

for a.e. t ∈ J,

Mx(a) + N x(b) + Rx(c) = α. Then x(t) =

t a

−1

e(s) ds + (M + N + R)

α−N

a

b

e(s) ds − R

a

c

e(s) ds .

472

S.K. Ntouyas

If E is the identity matrix, for a t b < c, we have x(t) =

a

− − =

a

− −

t

E − (M + N + R)−1 N − (M + N + R)−1 R e(s) ds

t

b

t

b

(M + N + R)−1 N + (M + N + R)−1 R e(s) ds

c

(M + N + R)−1 R e(s) ds

(M + N + R)−1 Me(s) ds

b

t

c

b

(M + N + R)−1 (N + R)e(s) ds (M + N + R)−1 Re(s) ds,

and hence x(t) max (M + N + R)−1 M , (M + N + R)−1 (N + R), (M + N + R)−1 R e Y .

For a b t c we have x(t) =

a

− − =

a

− −

b

E − (M + N + R)−1 N − (M + N + R)−1 R e(s) ds

b

t

b

t

−E + (M + N + R)−1 R e(s) ds

c

(M + N + R)−1 R e(s) ds

(M + N + R)−1 Me(s) ds

b

t

t

(M + N + R)−1 (−M − N )e(s) ds

c

(M + N + R)−1 Re(s) ds,

and hence x(t) max (M + N + R)−1 M , (M + N + R)−1 (M + N ), (M + N + R)−1 R e Y .


473

By combining the above relations we get x(t) Γ e 1 where

Γ = max (M + N + R)−1 R , (M + N + R)−1 M , (M + N + R)−1 (N + R), (M + N + R)−1 (N + M) .

It is obvious that, if e = 0, then the problem x ′ (t) = 0,

for a.e. t ∈ J,

Mx(a) + N x(b) + Rx(c) = α, has the unique solution x(t) = w, where w = (M + M + R)−1 α. Moreover the problem x ′ (t) = f (t, x),

for a.e. t ∈ J,

Mx(a) + N x(b) + Rx(c) = α, has a solution x = y1 + w if and only if y1 is a solution of y ′ (t) = f (t, y + w),

for a.e. t ∈ J,

(3.6)

My(a) + Ny(b) + Ry(c) = 0.

(3.7)

Now we define L : D(L) ⊂ X → Y by D(L) = y ∈ AC(J ): My(a) + Ny(b) + Ry(c) = 0 ,

and for y ∈ D(L),

Ly = y ′ . We also define a nonlinear mapping G : X → X by Gy = f t, y(t) + w , t ∈ J.

We note that G is a bounded operator from X into Y . Next it is easy to see from (A1) that the linear mapping L : D(L) ⊂ X → Y , is a one-to-one mapping. Let the linear mapping K : Y → X be defined for e ∈ Y by (Ke)(t) =

a

t

−1

e(s) ds + (M + M + R)

α−N

b a

e(s) ds − R

a

c

e(s) ds .

474

S.K. Ntouyas

Then for e ∈ Y , we have Ke ∈ D(L) and LKe = e. For y ∈ D(L), we have KLy = y. Furthermore, it follows easily using the Arzelá–Ascoli theorem that KG maps a bounded subset of X into a relatively compact subset of X. Hence, KG : X → X is a compact mapping. We next note that y ∈ C(J, Rn ) is a solution of BVP (3.6)–(3.7) if and only if y is a solution to operator equation Ly − Gy, which is equivalent to the equation y = KGy. We apply the Leray–Schauder continuation theorem (see, e.g., [82, Corollary IV.7]) to obtain existence of a solution to y = KGy or equivalently to the BVP (3.6)–(3.7). To do this, it suffices to verify that the set of all possible solutions of the family of equations y ′ (t) = λf (t, y + w),

for a.e. t ∈ J,

My(a) + Ny(b) + Ry(c) = 0,

(3.8) (3.9)

is bounded in X = C(J, Rn ) by a constant independent of λ ∈ [0, 1]. Let y(t) be a solution of (3.8)–(3.9) for some λ ∈ [0, 1]. It follows from our assumptions that f (t, y(t) + w(t)) ∈ L1 (J, Rn ). We have

y X λΓ f t, y(t) + w Y Γ p L1 y + w X + r L1 Γ p L1 y X + w X + r L1 .

It follows from Γ p L1 < 1 that there exists a constant c0 , independent of λ ∈ [0, 1], such that

y X c0 . This completes the proof of the theorem.

T HEOREM 3.3. Let f : [a, c] × Rn → Rn be a Carathéodory function and α ∈ Rn . Assume that (A1) holds. Moreover we suppose that (A3) There exists function p ∈ L1 (J ) such that f (t, u) − f (t, v) p(t) u − v

for a.e. t ∈ J and all u, v ∈ Rn .


475

Then the three-point BVP (3.4)–(3.5) has a unique solution in C(J, Rn ) provided Γ p 1 < 1. P ROOF. We note that (A3) implies f (t, u) f (t, 0) + p(t) u ,

for a.e. t ∈ J and all u ∈ Rn . Hence the BVP (3.4)–(3.5) has at least one solution in C(J, Rn ) by Theorem 3.2. Suppose that u1 , u2 are two solutions of (3.4)–(3.5) in C(J, Rn ). Setting z = u1 − u2 , we have z′ = f t, u1 (t) − f t, u2 (t) , Mz(a) + N z(b) + Rz(c) = 0.

Then we have

z X λΓ f t, u1 (t) − f t, u2 (t) Y Γ p L1 u1 − u2 X Γ p L1 z X ,

which implies that z(t) = 0, for t ∈ J and hence u1 = u2 . This completes the proof of the theorem. Theorems 3.2 and 3.3 were taken from [74]. Existence and uniqueness of solutions of the BVP (3.4)–(3.5) were studied in [84] by using the successive over relaxation iteration and the Banach contraction mapping principle. 3.2. Second-order three-point boundary value problems In this section we consider the following three-point BVP x ′′ (t) = f t, x(t), x ′ (t) + e(t), t ∈ (0, 1) x(0) = 0,

x(1) = x(η),

(3.10) (3.11)

where f : [0, 1] × R2 → R, e : [0, 1] → R are given functions and η ∈ (0, 1). We will study the existence and uniqueness of the BVP (3.10)–(3.11). We use the classical spaces C[0, 1], C k [0, 1], Lk [0, 1], and L∞ [0, 1] of continuous, k-times continuously differentiable, measurable real valued functions whose kth power of the absolute value is Lebesgue integrable on [0, 1], or measurable functions that are essentially bounded on [0, 1]. We also use the Sobolev space W 2,k (0, 1), k = 1, 2 defined by W 2,k (0, 1) = x : [0, 1] → R: x, x ′ are absolutely continuous on [0, 1] with x ∈ Lk [0, 1]

476

S.K. Ntouyas

with its usual norm. We denote the norm in Lk [0, 1] by · k , and the norm in L∞ [0, 1] by

· ∞ . The BVP (3.10)–(3.11) can be put in the form of an operator equation Lx + N x = w, where L : D(L) ⊂ X → Y is a linear operator, N : X → Y is a nonlinear operator, and X, Y are suitable spaces in duality. Clearly the linear operator L in (3.10) is given by Lx = −x ′′ where the boundary conditions (3.11) are used to define the domain, D(L), of L. We begin by giving the following definition. D EFINITION 3.4. A function f : [0, 1] × R2 → R satisfies Carathéodory’s conditions if: (i) for each (x, y) ∈ R2 , the function t ∈ [0, 1] → f (t, x, y) ∈ R is measurable on [0, 1], (ii) for a.e. t ∈ [0, 1], the function (x, y) ∈ R2 → f (t, x, y) ∈ R is continuous on R2 , and 1 (iii) for each r > 0, there exists g0 r ∈ L [0, 1] such that |f (t, x, y)| gr (t) for a.e. 2 2 t ∈ [0, 1] and (x, y) ∈ R with x + y 2 r.

In the next existence theorems, we obtain appropriate a priori bounds by applying degree theory. We use Wirtinger-type inequalities to obtain the necessary a priori bounds needed to apply the Leray–Schauder continuation theorem [82, Corollary IV.7]. T HEOREM 3.5. Let f : [0, 1] × R2 → R satisfy Carathéodory’s conditions. Assume that there exist functions p, q, r ∈ L1 [0, 1] such that f (t, u, v) p(t)|u| + q(t)|v| + r(t),

(3.12)

for a.e. t ∈ [0, 1] and all (u, v) ∈ R2 . Then for every given function e ∈ L1 [0, 1], the BVP (3.10)–(3.11), has at least one solution in C 1 [0, 1] provided

q 1 1, and 1 − q L1 [0,1] √ η p L1 [η,1] + p L1 [0,1] + q L1 [0,1] < 1. 1 − q L1 [η,1] P ROOF. Let X be the Banach space C 1 [0, 1] and Y denote the Banach space L1 (0, 1) with their usual norms. We define a linear mapping L : D(L) ⊂ X → Y by setting D(L) = x ∈ W 2,1 (0, 1): x(0) = 0, x(1) = x(η) ,


477

and for x ∈ D(L), Lx = −x ′′ . We also define a nonlinear mapping N : X → Y by setting (N x)(t) = f t, x(t), x ′ (t) ,

t ∈ [0, 1].

We note that N is a bounded mapping from X into Y . Next, it is easy to see that the linear mapping L : D(L) ⊂ X → Y , is one-to-one mapping. Next, the linear mapping K : Y → X, defined for y ∈ Y by (Ky)(t) = −

t

0

(t − s)y(s) ds + t

η

0

t y(s) ds + 1−η

0

1

(1 − s)y(s) ds

is such that for y ∈ Y , Ky ∈ D(L) and LKy = y; and for u ∈ D(L), KLu = u. Furthermore, it follows easily using the Arzelá–Ascoli theorem that KN maps a bounded subset of X into a relatively compact subset of X. Hence KN : X → X is a compact mapping. We next note that x ∈ C 1 [0, 1] is a solution of the BVP (3.10)–(3.11) if and only if x is a solution to the operator equation Lx = N x + e. Now, the operator equation Lx = N x + e is equivalent to the equation x = KNx + Ke. We apply the Leray–Schauder continuation theorem (see, e.g., [82, Corollary IV.7]) to obtain the existence of a solution for x = KNx + Ke or equivalently to the BVP (3.10)–(3.11). To do this, it suffices to verify that the set of all possible solutions of the family of equations x ′′ (t) = λf t, x(t), x ′ (t) + λe(t), x(0) = 0,

t ∈ (0, 1),

x(1) = x(η),

(3.13) (3.14)

is, a priori, bounded in C 1 [0, 1] by a constant independent of λ ∈ [0, 1]. We observe first that for x ∈ W 2,1 (0, 1) with x(0) = 0, x(1) = x(η) there exists a ζ ∈ (0, 1), η < ζ < 1, such that x ′ (ζ ) = 0. It follows that

x 2

2 ′

x 2 , π

x ∞ x ′ 2 ,

x(1) = x(η) =

0

η

√ x (t) dt η x ′ 2 , ′

478

S.K. Ntouyas

′ x (1) =

1

1 ′′ x (t) dt. x (t) dt ′′

ζ

ζ

We multiply Eq. (3.13) by x and integrate from 0 to 1 to get 0=−

1

x (t)x(t) dt + λ

0

x ′ 22

x ′ 22 −

′′

0

− x ′ (1)x(1)

1

0

− x ′ (1)x(1) −

0

f t, x(t), x ′ (t) x(t) dt − λ 1

1

e(t)x(t) dt

0

f t, x(t), x ′ (t) x(t) dt − e 1 x ∞

2 p(t)x(t) + q(t)x(t)x ′ (t) + r(t)x(t) dt − e 1 x ∞

1

x ′ 22

−

√ η x ′ 2 x ′′ L1 [η,1]

− p 1 x 22 + q 1 x ∞ x ′ ∞ + r 1 x ∞ − e 1 x ∞ √ x ′ 22 − η x ′ 2 x ′′ L1 [η,1] − p 1 x ′ 22 + q 1 x ′ 2 x ′′ 1 − r 1 + e 1 x ′ 2 .

From Eq. (3.13) we have

x ′′ 1 p 1 x ∞ + q 1 x ′ ∞ + r 1

p 1 x ′ 2 + q 1 x ′′ 1 + r 1 ,

so that

x ′′ 1

p 1 x ′ 2

r 1 + . 1 − q 1 1 − q 1

Similarly we have

x ′′ L1 [η,1]

p L1 [η,1] x ′ 2 1 − q L1 [η,1]

+

r 1 . 1 − q L1 [η,1]

Consequently √ 1 − q 1 − η p L1 [η,1] q 1 r 1 +

√ η r 1

1 − q 1 − p 1 x ′ 2 1 − q L1 [η,1]

1 − q 1 + r 1 + e 1 1 − q 1 . 1 − q L1 [η,1]


479

Hence, there exists a constant C, independent of λ ∈ [0, 1] such that x ′ 2 C. It follows that there is a constant, still denoted by C, independent of λ ∈ [0, 1] such that

x C 1 [0,1] C.

This completes the proof of the theorem.

T HEOREM 3.6. Let f : [0, 1] × R2 → R satisfy Carathéodory’s conditions. Assume that a 0, b 0, α(t) ∈ L1 [0, 1] are such that f (t, u, v) a|u| + b|v| + α(t),

for a.e. t ∈ [0, 1] and all (u, v) ∈ R2 . Then for every given function e(t) ∈ L1 [0, 1], the BVP (3.10)–(3.11) has at least one solution in C 1 [0, 1] provided

2 a+b π

2 0 + η(1 − η) < 1. π

P ROOF. As in the proof of Theorem 3.5 it suffices to verify that the set of all possible solutions of the family of equations (3.13)–(3.14) is a priori bounded in C 1 [0, 1] by a constant independent of λ ∈ [0, 1]. Letting x to be a solution of (3.13)–(3.14) for some λ ∈ [0, 1] we get, as in Theorem 3.5, that 0=−

0

1

x ′′ (t)x(t) dt + λ

x ′ 22 − x ′ (1)x(1) −

1

0

0

f t, x(t), x ′ (t) x(t) dt − λ 1

1

e(t)x(t) dt

0

a|x|2 + b|x||x ′ | + α(t)|x| dt − e 1 x ∞

√ x ′ 22 − η x ′ 2 x ′′ L1 [η,1] − a x 22 − b x 2 x ′ 2 − α 1 + e 1 x ∞ 2 4 √ ′ 2 ′ ′′ a + b x ′ 22 − α 1 + e 1 x ′ 2 . x 2 − η x 2 x L1 [η,1] − π π2 Also

x ′′ L1 [η,1] f t, x(t), x ′ (t) L1 [η,1] + e 1 1 1 |x ′ | dx + α 1 + e 1 |x| dx + b a η

0

1−η

η

2 a + b x ′ 2 + α 1 + e 1 . π

480

S.K. Ntouyas

Consequently √ ( α 1 + e 1 )(1 + η) .

x 2 √ 1 − ((2/π)a + b)(2/π + η(1 − η)) ′

It then follows as in proof of Theorem 3.5 that there exists a constant C independent of λ ∈ [0, 1] such that x C 1 [0,1] C, which proves the theorem. We give now a uniqueness result for the BVP (3.10)–(3.11). T HEOREM 3.7. Let f : [0, 1] × R2 → R satisfy Carathéodory’s conditions. Assume that a 0, b 0, are such that f (t, u1 , v1 ) − f (t, u2 , v2 ) a|u1 − u2 | + b|v1 − v2 |,

(3.15)

for a.e. t ∈ [0, 1] and all (ui , vi ) ∈ R2 , i = 1, 2. Then for every given function e(t) ∈ L1 [0, 1], the BVP (3.10)–(3.11) has unique solution in C 1 [0, 1] provided

2 a+b π

2 0 + η(1 − η) < 1. π

P ROOF. We note that (3.15) implies that f (t, u, v) < a|u| + b|v| + f (t, 0, 0)

for all t ∈ [0, 1] and all (u, v) ∈ R2 . Hence the BVP (3.10)–(3.11) has a solution by Theorem 3.6. Let now u1 , u2 be two solutions of (3.10)–(3.11) in C 1 [0, 1]. Setting w = u1 − u2 we have w ′′ = f (t, u1 , u′1 ) − f (t, u2 , u′2 ), w(0) = 0,

t ∈ (0, 1),

w(1) = w(η).

Multiplying Eq. (3.16) by w and integrating over [0, 1] we get 0=−

0

0

−

0

0

1

f t, u1 (t), u′1 (t) − f t, u2 (t), u′2 (t) w(t) dt

− w(1)w ′ (1)

f t, u1 (t), u′ (t) − f t, u2 (t), u′ (t) w(t) dt 1 2

1

w ′ 22

′′

w w dt +

w ′ 22 −

1

−

1

√ η w ′ 2 w ′′ L1 [η,1]

a|u1 − u2 |2 + b|u′1 − u′2 ||u1 − u2 |2 dt

(3.16) (3.17)


w ′ 22 −

√ η w ′ 2 w ′′ L1 [η,1] −

481

2 4 b

w ′ 22 . a + π π2

But

w ′′ L1 [η,1] = f t, u1 (t), u′1 (t) − f t, u2 (t), u′2 (t) L1 [η,1] 0 2 a + b w ′ 22 , 1−η π and consequently 0 2 2 1− η(1 − η) + a + b w ′ 22 0, π π

t so that w ′ 2 = 0. Since w(0) = 0 we obtain using w(t) = 0 w ′ (t) dt that w ∞

w ′ 2 = 0. Hence w = 0 a.e. in [0, 1] and thus w(t) = 0 for every t ∈ [0, 1] because w is continuous. Theorems 3.5–3.7 were proved by Gupta in [25]. By means of rather different approach based on an existence theorem for operator inclusions, Marano proved in [80], that if p, q, r are in L1 [0, 1] and (3.12) holds, then the BVP (3.10)–(3.11) has at least one generalized solution x ∈ W 2,1 [0, 1] provided

p 1 + q 1 < 1, which is an improvement of Theorem 3.5. For this result of Marano, Gupta in [26] gave a simple proof by using degree theory and Wirtinger-type inequalities. Marano in [80] proved also that if p, q, r are in L2 [0, 1] and (3.12) holds, then the BVP (3.10)–(3.11) has at least one generalized solution x ∈ W 2,1 [0, 1] provided √ η+1

p 2 + q 2 < 1. π

In the case when p, q, r are in L2 (0, 1), and (3.12) holds, Gupta in [32] proved that the BVP (3.10)–(3.11) has at least one generalized solution x ∈ C 1 [0, 1] provided 2

p 2 + q 2 < 1. π The Leray–Schauder continuation theorem can be used without the use of Wirtingertype inequalities and using instead Green’s functions. The Green’s functions for various BVPs are easily computed. Then one uses Green’s functions to reduce the BVPs to integral equations. Thus finding a priori estimates can be realized by estimating the norms of integral operators, which can be solved by Green’s functions and its derivatives. In this

482

S.K. Ntouyas

direction Zhang and Han [93] proved that if p, q, r are in L1 [0, 1] and (3.12) holds, then the BVP (3.10)–(3.11) has at least one solution in C 1 [0, 1] provided η sp(s) + q(s) ds + max

1−s sp(s) + q(s) ds, 1 − η η s −η sp(s) + q(s) ds < 1. 1−η

0

1

1

η

In [9] Boucherif and Bouguima proved the existence of solutions of the BVP (3.10)– (3.11) by considering two types of nonlinearities, continuous and Carathéodory’s nonlinearities. The methods used in the first case rely on the topological transversality theorem of Granas [14], and in the second case on the technique of cut-off functions. They motivated their results by the remark that if f (t, u, v) = u + v + R(t, u, v) with R(t, u, v) r(t) for a.e. t ∈ [0, 1] then f satisfies condition (3.12) i.e. |f (t, u, v)| p0 (t)|u| + q0 |v| + r(t) but

p0 1 + q0 1 = 2 > 1. T HEOREM 3.8. Let f : [0, 1] × R2 → R be a continuous function satisfying the following conditions: (f1) there exists r > 0 such that

0

t

f s, x(s), x ′ (s) x(s) ds > 0 whenever x(t) > r.

(f2) |f (t, u, v)| ψ(|v|) for (t, u) ∈ [0, 1] × [−r, r], v ∈ R where ψ : [0,∞) → (0, ∞) +∞ s is such that 1/ψ is integrable over bounded intervals in [0, ∞) and 0 ψ(s) ds > 2r. Then the BVP (3.10)–(3.11) has at least one solution. P ROOF. We begin by examining the linear problem x ′′ = z,

x(0) = 0,

x(1) = x(η)

where z ∈ C([0, 1], R). This problem has a unique solution x ∈ C 2 [0, 1], given by x(t) =

0

t

(t − s)z(s) ds + t

0

η

t z(s) ds + 1−η

η

1

(1 − s)z(s) ds.

This relation defines a linear operator K : C[0, 1] → C 2 [0, 1] such that x = Kz is the unique solution. Moreover L = K −1 is defined by D(L) = x ∈ C 2 [0, 1]: x(0) = 0, x(1) = x(η) , Lx = x ′′ . For λ ∈ [0, 1] consider the one-parameter family of problems x ′′ (t) = λf t, x(t), x ′ (t) , t ∈ (0, 1),

(3.18)


x(0) = 0,

x(1) = x(η).

483

(3.19)

We shall prove that any solution x of (3.18)–(3.19) is a priori bounded, independently of λ. Let x be a solution of (3.18)–(3.19). If λ = 0 then x = 0 and so x 0 = 0 < r. Assume 0 < λ 1. Then λf satisfies (f1). Suppose x takes on a positive maximum at t0 ∈ [0, 1]. Then x ′ (t0 ) = 0 and x ′′ (t0 ) 0. Now, if x(t0 ) > r it follows from (f1) that

0

t0

′′

′

x (s)x(s) ds = x(t0 )x (t0 ) −

t0

x ′ (s)2 ds > 0.

0

Since x ′ (t0 ) = 0 we have a contradiction. Hence x(t0 ) r and therefore x 0 r. Note that t0 = 0 since x(0) = 0. Also, the case t0 = η or t0 = 1 leads to a contradiction. Now we want to show that there exists a constant m0 , such that |x ′ (t)| m0 for all t ∈ [0, 1]. Suppose on the contrary that for all positive constants m, there exists t0 ∈ (0, 1] such that x ′ (t0 ) > m or x ′ (t0 ) < −m. We will assume only the case x ′ (t0 ) > m, since the other case can be handled in a similar way. Let τ ∈ (0, 1) be such that x ′ (τ ) = 0 and x ′ (t) > 0 for all t ∈ (τ, t0 ]. This implies that

Hence

x ′′ (t) ψ x ′ (t)

for all t ∈ [τ, t0 ].

x ′′ (t)x ′ (t) x ′ (t) ψ(x ′ (t))

for all t ∈ [τ, t0 ].

Integrating this inequality from τ to t0 we get

0

x ′ (t0 )

s ds 2r. ψ(s)

It follows from the assumptions on ψ that there exists a constant m ˜ such that x ′ (t0 ) m, ˜ and so we get a contradiction. Since f is continuous, we have |x ′′ (t)| m1 := sup{|f (t, u, v)|: 0 t 1, u 0 r, v 0 m0 }. Hence x ′′ 0 m1 . Finally, let M = max(r, m0 , m1 ). Then we get, from

x = max( x 0 , x ′ 0 , x ′′ 0 ) that x M, and M is independent of λ. We apply the topological transversality of Granas [14]. Let U = {x ∈ D(L): x < M + 1}, and j : D(L) → C 1 [0, 1] with j (x) = x, the natural embedding. The Nemitskii operator F : C 1 [0, 1] → C[0, 1] is defined by F (x)(t) := f (t, x(t), x ′ (t)) for all t ∈ [0, 1]. For 0 λ 1 define a family of mappings Hλ : U → D(L)

by Hλ (x) = λKFj (x).

Hλ is a compact homotopy which has no fixed points on the boundary ∂U of U . Since the constant map H0 is essential, the topological transversality theorem implies that H1 is essential i.e. has a fixed point. This completes the proof.

484

S.K. Ntouyas

In the case of Carathéodory’s nonlinearities we state the following result whose proof is given in [9]. T HEOREM 3.9. Let f : [0, 1] × R2 → R be a function satisfying Carathéodory’s conditions. Assume that (f) |f (t, u, v)| ω(t, |u| + |v|) for a.e. t ∈ [0, 1] and all (u, v) ∈ R2 where ω : [0, 1] × R+ → R+ is nondecreasing in its second argument and 1 ρ→∞ ρ lim

0

1

ω(t, ρ) dt = 0.

Then the BVP (3.10)–(3.11) has at least one solution.

3.3. Third-order three-point boundary value problems In this section we consider third-order three-point BVPs. The existence and uniqueness of third-order BVPs deserve a good deal of attention, since they occur in a wide variety of applications. For example, a three-layer beam is formed by parallel layers of different materials. For an equally loaded beam of this type, has shown that the deflection ψ is governed by an ordinary third-order linear differential equation ψ ′′′ − K 2 ψ ′ + a = 0, where K 2 and a are physical parameters depending on the elasticity of the layers. The condition of zero moment at the free ends implies the boundary conditions ψ ′ (0) = ψ ′ (1) = 0, and the symmetry yields the third boundary condition ψ(1/2) = 0. We will study existence and uniqueness of the following three-point BVP x ′′′ (t) = f t, x(t), x ′ (t), x ′′ (t) + e(t),

x(0) = x(η) = x(1) = 0

t ∈ (0, 1),

(3.20) (3.21)

where e : [0, 1] → R is a function in L1 [0, 1], η ∈ (0, 1), and f : [0, 1] × R3 → R is a function satisfying Carathéodory’s conditions, that is (i) for each (x, y, z) ∈ R3 , the function t ∈ [0, 1] → f (t, x, y, z) ∈ R is measurable on [0, 1], (ii) for a.e. t ∈ [0, 1], the function (x, y, z) ∈ R3 → f (t, x, y, z) ∈ R is continuous on R3 , and


485

(iii) for each r > 0, there exists gr ∈0 L1 [0, 1] such that |f (t, x, y, z)| gr (t) for a.e. 3 t ∈ [0, 1] and (x, y, z) ∈ R with x 2 + y 2 + z2 r.

T HEOREM 3.10. Let f : [0, 1] × R3 → R satisfy Carathéodory’s conditions. Assume that (i) there exist a, b, c ∈ R and α(t) ∈ L1 [0, 1] such that f (t, x, y, z)y ay 2 + b|y||x| + c|y||z| + α(x)y, for a.e. t ∈ [0, 1] and all (x, y, z) ∈ R3 ; (ii) there exist functions p, q, r in L2 [0, 1] and a function S(t) ∈ L1 [0, 1] such that f (t, x, y, z) p(t)|x| + q(t)|y| + r(t)|z| + S(t),

for a.e. t ∈ [0, 1] and all (x, y, z) ∈ R3 . Let η ∈ (0, 1) be given. Then for any given function e ∈ L1 [0, 1], the tree-point BVP (3.20)– (3.21) has at least one solution in C 2 [0, 1] provided 4 2 4 2 2 |a| + 3 |b| + |c| + 2 p 2 + q 2 + r 2 < 1. 2 π π π π π P ROOF. Let X be the Banach space C 2 [0, 1] and Y denote the Banach space L1 (0, 1) with their usual norms. We define a linear mapping L : D(L) ⊂ X → Y by setting D(L) = x ∈ W 3,1 (0, 1): x(0) = x(η) = x(1) = 0 , and for x ∈ D(L),

Lx = −x ′′′ . We also define a nonlinear mapping N : X → Y by setting (N x)(t) = f t, x(t), x ′ (t), x ′′ (t) , t ∈ [0, 1].

We note that N is a bounded mapping from X into Y . Next, it is easy to see that the linear mapping L : D(L) ⊂ X → Y , is one-to-one mapping. Next, the linear mapping K : Y → X, defined for y ∈ Y by 1 (Ky)(t) = 2

t 0

(t − s)2 y(s) ds + Bt + Ct 2 ,

where 1 B= 2η(η − 1) 1 C= 2η(1 − η)

η

0

0

η

η (t − s) y(s) ds + 2(1 − η) 2

1 (t − s) y(s) ds − 2(1 − η) 2

1

0

0

1

(t − s)2 y(s) ds, (t − s)2 y(s) ds,

486

S.K. Ntouyas

is such that for y ∈ Y , Ky ∈ D(L) and LKy = y; and for u ∈ D(L), KLu = u. Furthermore, it follows easily using the Arzelá–Ascoli theorem that KN maps a bounded subset of X into a relatively compact subset of X. Hence KN : X → X is a compact mapping. We next note that x ∈ C 1 [0, 1] is a solution of the BVP (3.20)–(3.21) if and only if x is a solution to the operator equation Lx = N x + e. Now, the operator equation Lx = N x + e is equivalent to the equation x = KNx + Ke. We apply the Leray–Schauder continuation theorem (see, e.g., [82, Corollary IV.7]) to obtain the existence of a solution for x = KNx + Ke or equivalently to the BVP (3.20)–(3.21). To do this, it suffices to verify that the set of all possible solutions of the family of equations x ′′′ (t) = λf t, x(t), x ′ (t), x ′′ (t) + λe(t),

t ∈ (0, 1),

(3.22)

x(0) = x(η) = x(1) = 0,

(3.23)

is, a priori, bounded in C 2 [0, 1] by a constant independent of λ ∈ [0, 1]. We observe that for x ∈ W 3,1 (0, 1) with x(0) = x(η) = x(1) = 0, there exist ξ1 , ξ2 , ξ3 in (0, 1) with ξ1 < η < ξ2 , x ′ (ξ1 ) = x ′ (ξ2 ) = 0, x ′′ (ξ3 ) = 0. This gives 2 1 ′

x 2 ,

x ′ 2 x ′′ 2 , π π η ′′ ′ ξ1 ′′ x (t) dt, x (0) = x (t) dt

x 2

0

0

′ x (1) =

1

ξ2

′′ x (0) =

1 ′′ x (t) dt, x ′′ (t) dt η

ξ3

0

x (t) dt x ′′′ 1 , ′′

′′ x (1) =

1 ξ3

We multiply Eq. (3.22) by x ′ and integrate from 0 to 1 to get 0=−

1

′′′

x (t)x (t) dt + λ

0

−λ

′

0

1

e(t)x ′ (t) dt

0

1

x (t) dt x ′′′ 1 . ′′

f t, x(t), x ′ (t), x ′′ (t) x ′ (t) dt


487

x ′′ 22 − x ′′ (1)x ′ (1) − x ′′ (0)x ′ (0) 1 ′2 ax (t) + bx(t)x ′ (t) + cx ′ (t)x ′′ (t) + α(t)x ′ (t) dt +λ 0

− λ e 1 x ′ ∞ x ′′ 22 − x ′ (0) + x ′ (1) x ′′ 1 − |a| x ′ 22 − |b| x 2 x ′ 2 − |c| x ′ 2 x ′′ 2 − α 1 + e 1 x ′ ∞ η 1 ′′ ′′ ′′ 2 x (t) dt x ′′′ 1 x (t) dt + x 2 − 0

η

′′ 4 2 4 ′′ 2 |c|

x |a| + |b| + −

α

+

e

x 2

− 1 1 2 π π2 π3 4 2 4 |c|

x ′′ 22 |a| + |b| + x ′′ 22 − x ′′ 1 x ′′′ 1 − π π2 π3 − α 1 + e 1 x ′′ 2 .

From Eq. (3.22) we have

x ′′′ 1 p 2 x 2 + q 2 x ′ 2 + r 2 x ′′ 2 + S 1 + e 1 2 2 ′′

q

+

r

p

+ 2 2 x 2 + S 1 + e 1 . 2 π π2 Putting this in the previous inequality we find

x ′′ 2

1−

S 1 + 2 e 1 + α 1 4 4 |a| + π 3 |b| + π2 |c| + π22 p 2 + π2 q 2 π2

+ r 2

.

Hence, there exists a constant C, independent of λ ∈ [0, 1] such that x ′′′ 1 C. It follows that there is a constant, still denoted by C, independent of λ ∈ [0, 1] such that

x C 2 [0,1] C. This completes the proof of the theorem. In Theorem 3.10 we can do without assumption (i), if we observe that f (t, x, y, z)y f (t, x, y, z)|y| −p(t)|y||x| − q(t)y 2 − r(t)|y||z| − S(t)|y|.

488

S.K. Ntouyas

It is easy to see from the proof of Theorem 3.10 that the BVP (3.20)–(3.21) has at least one solution in C 2 [0, 1] provided 4 4

p 2 + q 2 + 2 r 2 < 1. π π2 T HEOREM 3.11. Let f : [0, 1]×R3 → R satisfy Carathéodory’s conditions. Suppose that (iii) there exist functions p, q, r ∈ L2 [0, 1] such that f (t, x1 , y1 , z1 ) − f (t, x2 , y2 , z2 )

p(t)|x1 − x2 | + q(t)|y1 − y2 | + r(t)|z1 − z2 |,

for a.e. t ∈ [0, 1] and all (xi , yi , zi ) ∈ R3 , i = 1, 2. Let η ∈ (0, 1) be given. Then for every e ∈ L1 [0, 1] the BVP (3.20)–(3.21) has exactly one solution in C 2 [0, 1] provided 4 4

p 2 + q 2 + 2 r 2 < 1. π π2 P ROOF. We note that (iii) implies that f (t, x, y, z) p(t)|x| + q(t)|y| + r(t)|z| + f (t, 0, 0, 0)

for a.e. t ∈ [0, 1] and all (x, y, z) ∈ R3 . Accordingly the BVP (3.20)–(3.21) has at least one solution in C 2 [0, 1]. Now, to prove the uniqueness, let x1 , x2 are two solutions of the BVP (3.20)–(3.21). Setting u(t) = x( t) − x2 (t) we then get u′′′ (t) = f t, x1 (t), y1 (t), z1 (t) − f t, x2 (t), y2 (t), z2 (t) , u(0) = u(η) = u(1) = 0.

We multiply Eq. (3.24) by u′ and integrate over [0, 1] to get 0=−

+

1

u′′′ (t)u′ (t) dt

0

0

1

u′′ 22

f t, x1 (t), y1 (t), z1 (t) − f t, x2 (t), y2 (t), z2 (t) u′ (t) dt

− u′′ 2 u′′′ 1 − p 2 u 2 u′ ∞ − q 2 u′ 2 u′ ∞

− r 2 u′ ∞ u′′ 2 u′′ 22 − u′′ 2 p 2 u 2 + q 2 u′ 2 + r 2 u′′ 2 2 2 −

p 2 + q 2 + r 2 u′′ 22 π π2

(3.24) (3.25)


489

4 4

u′′ 22 ,

q

p

+ 1− + 2 r

2 2 2 π π2 hence u′′ 2 = 0. It now follows from the estimate u 2 (2/π 2 ) u′′ 2 and the continuity of u that u(t) = 0 for every t ∈ [0, 1], i.e. x1 (t) = x2 (t) for every t ∈ [0, 1]. This completes the proof of the theorem. Theorems 3.10 and 3.11 were proved in [31]. For other results for third-order three-point BVPs the interested reader is referred to [1,24,81] and the references cited therein. 3.4. m-point boundary value problems reduced to three-point boundary value problems Let f : [0, 1] × R2 → R be either a continuous or a Carathéodory’s function and let e : [0, 1] → R be a function in L1 [0, 1], ai ∈ R, with all of the ai ’s having the same sign, ξi ∈ (0, 1), i = 1, 2, . . . , m − 2, 0 < ξ1 < ξ2 < · · · < ξm−2 < 1. We consider the following second-order ordinary differential equation x ′′ (t) = f t, x(t), x ′ (t) + e(t), t ∈ (0, 1) (3.26) subject to one of the following boundary value conditions: x(0) = 0,

x(1) =

m−2

ai x(ξi ),

(3.27)

x ′ (0) = 0,

x(1) =

m−2

ai x(ξi ),

(3.28)

x(0) = 0,

x ′ (1) =

i=1

i=1

m−2

ai x ′ (ξi ).

(3.29)

i=1

It is well known, that the existence of a solution for these BVPs can be studied via the existence of a solution for Eq. (3.26) subject to one of the following three-point boundary value conditions: x(0) = 0,

(3.30)

x ′ (0) = 0,

x(1) = αx(η), x(1) = αx(η),

(3.31)

x(0) = 0,

x (1) = αx (η),

(3.32)

′

′

where α = m−2 i=1 ai and η ∈ [ξ1 , ξm−2 ]. For certain boundary condition case such that the linear operator Lx = x ′′ , defined in a suitable Banach space, is invertible, is the so-called nonresonance case. Otherwise, the so-called resonance case. In the next sections we will give existence results for both, nonresonance and resonance cases.

490

S.K. Ntouyas

3.5. Nonresonance results Using the Leray–Schauder continuation theorem (see [82]) we first give an existence result for the three-point BVP (3.26), (3.30) in the case when α = 1. T HEOREM 3.12. Let f : [0, 1] × R2 → R be a function satisfying Carathéodory’s conditions. Assume that (3.12) holds. Also let α ∈ R, and η ∈ (0, 1) be given. Then the BVP (3.26), (3.30) has at least one solution in C 1 [0, 1] provided  if α 1,  p 1 + q 1 < 1, 1 − αη , if 1 < α < 1/η.  p 1 + q 1 < α(1 − η) P ROOF. Let X be the Banach space C 1 [0, 1] and Y denote the Banach space L1 (0, 1) with their usual norms. We denote a linear mapping L : D(L) ⊂ X → Y by setting D(L) = x ∈ W 2,1 (0, 1): x(0) = 0, x(1) = αx(η) , and for x ∈ D(L),

Lx = x ′′ . We also define a nonlinear mapping N : X → Y by setting (N x)(t) = f t, x(t), x ′ (t) , t ∈ [0, 1].

We note that N is a bounded mapping from X into Y . Next, it is easy to see that the linear mapping L : D(L) ⊂ X → Y , is one-to-one mapping. We note that since α 1, α = 1/η. Next, the linear mapping K : Y → X, defined for y ∈ Y by (Ky)(t) =

t

0

−

(t − s)y(s) ds + t 1 − αη

0

1

αt 1 − αη

0

η

(η − s)y(s) ds

(1 − s)y(s) ds

is such that for y ∈ Y , Ky ∈ D(L) and LKy = y; and for u ∈ D(L), KLu = u. Furthermore, it follows easily using the Arzelá–Ascoli theorem that KN maps a bounded subset of X into a relatively compact subset of X. Hence KN : X → X is a compact mapping. We next note that x ∈ C 1 [0, 1] is a solution of the BVP (3.26), (3.30) if and only if x is a solution to the operator equation Lx = N x + e. Now, the operator equation Lx = N x + e is equivalent to the equation x = KNx + Ke.


491

We apply the Leray–Schauder continuation theorem (see, e.g., [82, Corollary IV.7]) to obtain the existence of a solution for x = KNx + Ke or equivalently to the BVP (3.26), (3.30). To do this, it suffices to verify that the set of all possible solutions of the family of equations x ′′ (t) = λf t, x(t), x ′ (t) + λe(t), t ∈ (0, 1), (3.33) x(0) = 0,

x(1) = αx(η),

(3.34)

is, a priori, bounded in C 1 [0, 1] by a constant independent of λ ∈ [0, 1]. We observe that if x ∈ W 2,1 (0, 1), with x(0) = 0, x(1) = αx(η), with α 1, there exists a ζ ∈ (0, 1) with x ′ (ζ ) = 0. Indeed, suppose that α 1 and x ′ (t) > 0 for every t ∈ (0, 1). Then x(t) > 0 for every t ∈ (0, 1) and x(t) is strictly increasing on [0, 1]. We then get that 0 < x(1) − x(η) = (α − 1)x(η) 0, a contradiction. Then we have

x ∞ x ′ ∞ x ′′ 1 .

(3.35)

Now let x(t) be a solution of (3.33)–(3.34) for some λ ∈ [0, 1], so that x ∈ W 2,1 (0, 1) with x(0) = 0, x(1) = αx(η). We then get from Eq. (3.33) that

x ′′ 1 = λf t, x(t), x ′ (t) + e(t)1 p 1 x ∞ + q 1 x ′ ∞ + r 1 + e 1 p 1 + q 1 x ′′ 1 + r 1 + e 1 .

It follows from the assumption that there is a constant c, independent of λ ∈ [0, 1], such that

x ′′ 1 c. It is now immediate from (3.35) that the set of solutions of the family of equations (3.33)– (3.34) is, a priori, bounded in C 1 [0, 1] by a constant independent of λ ∈ [0, 1]. This completes the proof of the theorem when α 1. Let now α > 1 and η ∈ (0, 1) with αη < 1. It suffices to verify that the set of all possible solutions of the family of equations (3.33)–(3.34) is, a priori, bounded in C 1 [0, 1] by a constant independent of λ ∈ [0, 1]. For x ∈ W 2,1 (0, 1), with x(0) = 0, x(1) = αx(η), if α > 1, there exists a ζ ∈ (η, 1) such that (α − 1)x(η) = x(1) − x(η) = (1 − η)x ′ (ζ ), or x(η) = (1 − η)/(α − 1)x ′ (ζ ). Then we have

x ∞ x ′ ∞

α(1 − η) . 1 − αη

We then see from Eq. (3.33) that

x ′′ 1 = λf t, x(t), x ′ (t) + e(t)1

492

S.K. Ntouyas

p 1 x ∞ + q 1 x ′ ∞ + r 1 + e 1 α(1 − η)

x ′′ 1 + r 1 + e 1 p 1 + q 1 1 − αη

for a solution x of the family of equations (3.33)–(3.34) for some λ ∈ [0, 1]. It is then immediate that the set of solutions of the family of equations (3.33)–(3.34) is, a priori, bounded in C 1 [0, 1] by a constant, independent of λ ∈ [0, 1]. This completes the proof of the theorem. Now we study the m-point BVP (3.26)–(3.27) using the a priori estimates that we obtained for the three-point BVP (3.26), (3.30). This is because for every solution x(t) of the ], depending on x(t), such that x(t) is also a BVP (3.26)–(3.27) there exists η ∈ [ξ1 , ξm−2 solution of the BVP (3.26), (3.30) with α = m−2 i=1 ai = 1.

T HEOREM 3.13. Let f : [0, 1] × R2 → R be a function satisfying Carathéodory’s condim−2 tions. Assume that (3.12) holds. Also let α = i=1 ai , and η ∈ (0, 1) be given. Then the BVP (3.26)–(3.27) has at least one solution in C 1 [0, 1] provided  if α 1,  p 1 + q 1 < 1, 1 − αξm−2 , if 1 < α < 1/ξm−2 .  p 1 + q 1 < α(1 − ξ1 )

P ROOF. We will give only the proof for α = m−2 i=1 ai 1; the other case is similar. The proof is quite similar to that of Theorem 3.12 and uses the a priori bounds for the set of solutions of the family of equations (3.33)–(3.34). Let X be the Banach space C 1 [0, 1] and Y denote the Banach space L1 (0, 1) with their usual norms. We denote a linear mapping L : D(L) ⊂ X → Y by setting

D(L) = x ∈ W

2,1

(0, 1): x(0) = 0, x(1) =

m−2 i=1

(

ai x(ξi ) ,

and for x ∈ D(L), Lx = x ′′ . We also define a nonlinear mapping N : X → Y by setting (N x)(t) = f t, x(t), x ′ (t) , t ∈ [0, 1].

We note that N is a bounded mapping from X into Y . Next, it is easy to see that the linear mapping L : D(L) ⊂ X → Y , is one-to-one mapping. Next, the linear mapping K : Y → X, defined for y ∈ Y by (Ky)(t) =

0

t

(t − s)y(s) ds + At


493

where A is given by 8

A 1−

m−2 i=1

9

ai ξi =

m−2

ai

i=1

0

ξ1

(ξi − s)y(s) ds −

1 0

(1 − s)y(s) ds,

is such that for y ∈ Y , Ky ∈ D(L) and LKy = y; and for u ∈ D(L), KLu = u. Furthermore, it follows easily using the Arzelá–Ascoli theorem that KN maps bounded subsets of X into a relatively compact subsets of X. Hence KN : X → X is a compact mapping. We, next, note that x ∈ C 1 [0, 1] is a solution of the BVP (3.26)–(3.27) if and only if x is a solution to the operator equation Lx = N x + e. Now, the operator equation Lx = N x + e is equivalent to the equation x = KNx + Ke. We apply the Leray–Schauder continuation theorem to obtain the existence of a solution for x = KNx + Ke or equivalently to the BVP (3.26)–(3.27). To do this, it suffices to verify that the set of all possible solutions of the family of equations x ′′ (t) = λf t, x(t), x ′ (t) + λe(t), x(0) = 0,

x(1) =

m−2

t ∈ (0, 1),

ai x(ξi ),

(3.36) (3.37)

i=1

is, a priori, bounded in C 1 [0, 1] by a constant independent of λ ∈ [0, 1]. 2,1 Let, now, x(t) be a solution m−2 of (3.36)–(3.37) for some λ ∈ [0, 1], so that x ∈ W (0, 1) with x(0) = 0, x(1) = i=1 ai x(ξi ). Accordingly, there exists, an η ∈ [ξ1 , ξm−2 ], depending on x, such that x(t) is a solution of the three-point BVP x ′′ (t) = λf t, x(t), x ′ (t) + λe(t), x(0) = 0,

t ∈ (0, 1),

x(1) = αx(η).

It then follows, as in the proof of Theorem 3.12 that there is a constant c, independent of λ ∈ [0, 1], and η ∈ [ξ1 , ξm−2 ], such that

x ∞ x ′ ∞ x ′′ 1 c. Thus the set of solutions of the family of equations (3.36)–(3.37) is, a priori, bounded in C 1 [0, 1] by a constant, independent of λ ∈ [0, 1]. This completes the proof of the theorem.

494

S.K. Ntouyas

Theorems 3.12 and 3.13 were proved in [33]. In Theorem 3.12 the functions p, q, r in the condition (3.12) are in L1 (0, 1). If p, q are in L∞ (0, 1) and r, e in L2 (0, 1) then the BVP (3.26), (3.30) has at least one solution in C 1 [0, 1] provided  2 2    π π p ∞ + q ∞ < 1, √    2 p ∞ + q ∞ < 2(1 − αη) , π α(1 − η)

if α 1, if 1 < α < 1/η.

In the case when α 1 and αη = 1 we have a sharper condition for the solvability of BVP (3.26), (3.30). Thus, if tp, q, r are in L1 [0, 1] and (3.12) holds, then the BVP (3.26), (3.30) has at least one solution in C 1 [0, 1] provided  1 − αη   ,  tp(t)1 + q(t)1 < 1−η   tp(t) + q(t) < αη − 1  1 1 (α − 1)η

if αη 1, if αη > 1.

The above conditions were proved in [33] and based on a priori estimates obtained by a different method than that was used in Theorem 3.12. In the case when α ∈ R, α 1 Gupta and Trofimchuk in [38] gave constructive conditions for the solvability of the BVP (3.26), (3.30) using the spectral radius of a compact linear operator, and in [39] new solvability conditions based on a new type Wirtinger inequality. For other results see [37]. In the case when α ∈ R with αη = 1 a better condition for the solvability of the BVP (3.26), (3.30) is given by Gupta and Trofimchuk in [38]. They proved that, if tp, q, t[tp + q], r are in L1 [0, 1] and (3.12) holds, then the BVP (3.26), (3.30) has at least one solution in C 1 [0, 1] provided max

0

+

1 − α − 1 sp(s) + q(s) ds 1 − αη

η

1 |1 − αη|

1

η

1

η

(1 − s) sp(s) + q(s) ds,

|α − 1| |s − αη| sp(s) + q(s) ds + |1 − αη| |1 − αη|

0

η

s sp(s) + q(s) ds < 1.

Moreover, Gupta in [30], when α = 1 and αη = 1, obtained new a priori estimates which are sharper than those used in the previous theorems. More precisely, he proved that if p, q, r are in L1 (0, 1) and (3.12) holds, then the BVP (3.26), (3.30) has at least one solution in C 1 [0, 1] provided M p 1 +

1

q 1 < 1, 1−τ


495

where M and τ are appropriate constants. Finally, we note that in [40] Gupta and Trofimchuk studied examples of three-point BVP by making extensive use of computer algebra systems like Maple and MathCad. Concerning the uniqueness of the solutions of the BVPs (3.26), (3.30) and (3.26)–(3.27) we have the following results. T HEOREM 3.14. Let f : [0, 1] × R2 → R be a function satisfying Carathéodory’s conditions. Assume that there exist nonnegative constants c, d such that f (t, x1 , x2 ) − f (t, y1 , y2 ) c|x1 − x2 | + d|y1 − y2 |

for a.e. t ∈ [0, 1] and all (xi , xi ) ∈ R2 , i = 1, 2. Also let α ∈ R, and η ∈ (0, 1) be given. Then the BVP (3.26), (3.30) has exactly one solution in C 1 [0, 1] provided  2 2   c + d < 1, π π √    2 c + d < 2(1 − αη) , π α(1 − η)

if α 1, if 1 < α < 1/η.

P ROOF. The existence of a solution for the BVP (3.26), (3.30) follows from Theorem 3.12. Let now x1 (t), x2 (t) be two solutions of the BVP (3.26), (3.30). We then get x1′′ (t) − x2′′ (t) = f t, x1 (t), x1′ (t) − f t, y1 (t), y1′ (t) , (x1 − x2 )(0) = 0,

0 < t < 1,

(x1 − x2 )(1) = α(x1 − x2 )(η).

It follows that ′′ x − x ′′ = f t, x1 (t), x ′ (t) − f t, y1 (t), y ′ (t) 1 1 1 2 2 2 ′ ′ c x1 − x2 2 + x1 − x2 2 2 2 c + d x1′′ − x2′′ 2 . π π

Hence, we get that x1′′ − x2′′ 2 = 0. It now follows from the inequalities

x1 − x2 2

2 x ′ − x ′ 4 x ′′ − x ′′ = 0, 1 2 2 1 2 2 π π2

that x1 (t) = x2 (t) for a.e. t ∈ [0, 1] and hence for every t ∈ [0, 1] because of the continuity of x1 (t) and x2 (t) on [0, 1]. This completes the proof of the theorem in the case when α 1. The proof for the case 1 < α < 1/η is similar.

496

S.K. Ntouyas

T HEOREM 3.15. Let f : [0, 1] × R2 → R be as in Theorem 3.14. Then for any given e(t) in L2 (0, 1), the m-point BVP (3.26)–(3.27) has exactly one solution in C 1 [0, 1] provided   p 1 + q 1 < 1, 1 − αξm−2 ,  p 1 + q 1 < α(1 − ξ1 )

if α 1, if 1 < α < 1/η.

We now give a theorem which allows f to have nonlinear growth. We do this by imposing a decomposition condition for f . We need the following simple lemma. L EMMA 3.16. Let x ∈ C 1 [0, 1] satisfy x(0) = 0, x(1) = αx(η), where η ∈ (0, 1), and α > 1, α = 1/η, then there exist ζ and C0 ∈ (0, 1) such that x ′ (ζ ) = C0 x(1). P ROOF. If αη > 1, let C0 = 1/(αη). There exists ζ ∈ (0, 1) with x ′ (ζ ) =

x(η) − x(0) = C0 x(1). η

If αη < 1, let C0 = x ′ (ζ ) =

α−1 α(1−η) .

There exists ζ ∈ (η, 1) with

α−1 x(1) − x(η) = x(η) = C0 x(1). 1−η α(1 − η)

T HEOREM 3.17. Assume that f : [0, 1] × R2 → R is continuous and has the decomposition f (t, x, p) = g(t, x, p) + h(t, x, p) such that (1) pg(t, x, p) 0 for all (t, x, p) ∈ [0, 1] × R2 ; (2) h(t, x, p)| a(t)|x| + b(t)|p| + u(t)|x|r + v(t)|p|k + c(t) for all (t, x, p) ∈ [0, 1] × R2 where a, b, u, v are in L1 [0, 1] and 0 r, k < 1. Then, for α = 1/η, there exists a solution x ∈ C 1 [0, 1] to BVP (3.26), (3.30) provided that   

a 1 + b 1 <      

a 1 + b 1 <         a 1 + b 1
0 such that for v ∈ R with |v| > N , one has f (t, u, v) −l|u| + n|v| − M

for t ∈ [0, 1], u ∈ R

where n > l 0, M 0. (3) There exists R > 0 such that for |v| > R one has either for t ∈ [0, 1]

vf (t, vt, v) 0 or else

for t ∈ [0, 1].

vf (t, vt, v) 0

Then, for every continuous function e, the BVP (3.26), (3.30) with αη = 1 has at least one solution in C 1 [0, 1] provided that l 2 p 1 + q 1 + < 1. n

We give the proof via several lemmas. We now let L be the linear operator from D(L) ⊂ X → Z = L1 (0, 1) defined by D(L) = x ∈ W 2,1 (0, 1): x(0) = 0, x(1) = x(η)/η

and for x ∈ D(L), Lx = x ′′ . Let X1 = {x ∈ X: x(0) = 0}.

L EMMA 3.22. Suppose L is as above. Then L : D(L) ⊂ X → Z is Fredholm of index zero. Furthermore, the linear operator K : im(L) → D(L) ∩ X1 defined by (Ky)(t) =

t 0

τ

y(s) ds dτ,

0

y ∈ im(L)

is such that K = L−1 P , where LP = L|D(L)∩X1 . Also Ky y 1 for all y ∈ im(L). P ROOF. It is easy to see that ker(L) = {ct: c ∈ R}. We show that 1 im(L) = y ∈ L [0, 1]:

0

1

Y (t) dt =

0

1

Y (ηt) dt, where Y (t) =

0

t

y(s) ds .

500

S.K. Ntouyas

In fact, for y ∈ im(L), there is x ∈ D(L) with y(t) = x ′′ (t). Therefore

1

Y (t) dt =

0

0

1

x ′ (t) − x ′ (0) dt = x(1) − x ′ (0),

and

1

Y (ηt) dt =

0

0

1

x ′ (ηt) − x ′ (0) dt = x(η)/η − x ′ (0).

1 1 Since x(1) = η1 x(η), we have 0 Y (t) dt = 0 Y (ηt) dt. On the other hand, suppose y ∈ 1 1 t L1 [0, 1] is such that 0 Y (t) dt = 0 Y (ηt) dt. Let x(t) = 0 Y (s) ds, then x ∈ D(L) and x ′′ (t) = y(t). For y ∈ L1 [0, 1], let 2 Qy = 1−η

0

1 t

y(s) ds dt,

ηt

and let y1 (t) = y(t) − Qy. Then Y1 (t) = 2 Qy = 1−η

0

1 t 0

t 0

y(s) ds dt −

y(s) ds − (Qy)(t), and writing Qy in the form

0

1 ηt 0

y(s) ds dt ,

we see that

0

1 t 0

y(s) ds dt −

Qy = 2

0

1 ηt 0

y(s) ds dt − η

Qy , 2

that is

0

1

Y1 (t) dt =

1

Y1 (ηt) dt. 0

This shows that y1 ∈ im(L). Hence Z = im(L) + R. Since im(L) ∩ R = {0}, we have Z = im(L) ⊕ R and therefore L is Fredholm of index zero. Now we define a projection from X onto ker(L) by setting (P x)(t) = x ′ (0)t and let X1 = {x ∈ X, x ′ (0) = 0}. Then, for x ∈ D(L) ∩ X1 , we have (KLP x)(t) = Kx ′′ (t) =

t 0

τ 0

x ′′ (s) ds dτ =

and for y ∈ im(L), we have (LP Ky)(t) =

t 0

τ

y(s) ds dτ 0

′′

= y(t).

0

t

x ′ (τ ) − x ′ (0) dτ = x(t),


501

This shows that K = L−1 P . Also we have

and

(Ky)(t)

∞

(Ky)′ (t) =

0

1 1 0

y(s) ds dτ y(t) , 1

t

y(s) ds,

so

0

(Ky)′ (t)

∞

and hence Ky y 1 which completes the proof.

y(t)1 ,

L EMMA 3.23. Let U1 = {x ∈ D(L) \ ker(L), Lx + λNx = 0 for some λ ∈ [0, 1]}. Then U1 is a bounded subset of X. P ROOF. Suppose that x ∈ U1 , and Lx = −λNx, then λ = 0 and QN x = 0. Therefore

0

1 τ ητ

f t, x(t), x ′ (t) + e(t) dt dτ = 0,

and hence there exists γ ∈ (0, 1) such that

f γ , x(γ ), x ′ (γ ) = e(γ ) e(t) . ∞

Also for x ∈ D(L) \ ker(L), by Lemma 3.22 and condition (1)

(I − P )x = KL(I − P )x L(I − P )x = L(x) 1 1 ′ N (x) 1 p 1 x ∞ + q 1 x ∞ + r 1 + e 1 .

If for some t0 ∈ [0, 1], |x ′ (t0 )| N then we have ′ ′ x (0) = x (t0 ) −

t0 0

x (t) dt N + x ′′ 1 . ′′

Otherwise, if |x ′ (t)| > N for all t, from condition (2) we obtain

so that

′ e ∞ + M l x (γ ) + x ∞ , n n ′ ′ x (0) = x (γ ) −

0

γ

e ∞ + M l + x ∞ + x ′′ 1 . x (t) dt n n ′′

502

S.K. Ntouyas

Therefore we have in either case P (x) = x ′ (0) max e ∞ + M , N + l x ∞ + x ′′ 1 . n n

Writing x(t) =

t 0

x ′ (s) ds, we obtain

x ∞ x ′ 1 x ′ ∞ . Therefore

x ′ ∞ x (I − P )(x) + P x

l p 1 + q 1 +

x ′ ∞ + x ′′ 1 + C, n where C = r 1 +max{ e ∞ +M/n, N }. Let C1 = 1−[ p 1 + q 1 + nl ], so that C1 > 0. Then we can write

x ′ ∞

1 ′′ C

x 1 + , C1 C1

and then

x ′′ 1 = L(x)1 N x 1 p 1 x ∞ + q 1 x ′ ∞ + r 1 + e 1 p 1 + q 1 x ′ ∞ + r 1 + e 1

where C2 =

p 1 + q 1 ′′

x 1 + C2 , C1

p 1 + q 1 C1

+ r 1 + e 1 . If C3 =

x ∞ x ′ ∞

p 1 + q 1 C1

then C3 < 1 and hence

C C2 + , C1 (1 − C3 ) C1

which proves that U1 is bounded. L EMMA 3.24. The set U2 := {x ∈ ker(L): N (x) ∈ im(L)} is bounded.

P ROOF. Suppose that x ∈ U2 so that x(t) = ct, where c is a constant. Since QN x = 0, we have

0

1 τ ητ

f (t, ct, c) dt dτ = −

0

1 τ ητ

e(t) dt dτ.


503

Therefore there exists ξ ∈ (0, 1) such that |f (ξ, cξ, c)| |e(ξ )| e ∞ . It follows that M + e ∞ . |c| max N, n−l

For, if |c| > N , then by condition (2) we obtain e ∞ −l|cξ | + n|c| − M and hence |c| (M + e ∞ )/(n − l). Thus U2 is bounded. L EMMA 3.25. If in condition (3) we assume that there exists R > 0 such that for all |v| > R, vf (t, vt, v) 0, for t ∈ [0, 1], then the set U3 := x ∈ ker(L): H (x, λ) = λJ x + (1 − λ)QNx = 0, λ ∈ [0, 1] ,

is bounded, where J : ker(L) → Z0 , is the linear isomorphism given by J (ct) = c. P ROOF. Assume that xn (t) − cn t ∈ U3 and cn t = |cn | → ∞ as n → ∞. Then there exists λn ∈ [0, 1] such that λn cn + (1 − λn )(QN )(cn t) = 0. {λn } has a convergent subsequence, for simplicity we write λn → λ0 . We show that λ0 = 1. Indeed, otherwise we have λn = −(1 − λn )

(QN )cn t , cn

and as previously we find that (1 − λn )

(QN )cn t

→0 |cn |

(n → ∞),

contradicting λn → 1. Hence for n large enough, 1 − λn = 0, and therefore λn cn = Q f (t, cn t, cn ) + e(t) , 1 − λn and so λn 2 = 1 − λn 1 − η

0

1 τ ητ

2 f (s, cn s, cn ) ds dτ + cn cn (1 − η)

0

1 τ

e(s) ds dτ.

ητ

Since |cn | → ∞, we may assume that |cn | > max{N, R}. Then for large enough n we have f (s, cn s, cn ) n−l − M n−l. cn |cn | 2

504

S.K. Ntouyas

By our assumption cn f (t, cn t, cn ) 0 this yield f (t, cn t, cn )/cn −(n − l)/2. Hence, by Fatou’s lemma, lim sup

1 τ

f (s, cn s, cn ) 1 ds dτ + cn cn n→∞ 0 ητ 1 τ f (s, cn s, cn ) ds dτ lim sup cn n→∞ 0 ητ 1 τ f (s, cn s, cn ) ds dτ lim sup cn n→∞ 0 ητ −

0

1 τ

e(s) ds dτ

ητ

(n − l)(1 − η) . 4

This is a contradiction with λn /(1 − λn ) 0. Thus U3 is bounded.

P ROOF OF T HEOREM 3.21. Firstly, by Arzelá–Ascoli theorem, it can be shown that the linear operator K : im(L) → D(L) ∩ X1 in Lemma 3.22 is compact operator, so N is L-compact. Let Ω be a bounded open set containing 3i=1 Ui . Then by the above lemmas the conditions of Theorem 3.20 are satisfied and therefore Lx + N x = 0 has at least one solution in D(L) ∩ Ω so that the BVP (3.26), (3.30) with αη = 1 has at least one solution. T HEOREM 3.26. Assume that f : [0, 1] × R2 → R is continuous and has the decomposition f (t, x, p) = g(t, x, p) + h(t, x, p). Assume that (1) There exists M1 > 0 such that for x ∈ D(L) := {x ∈ W 2,1 (0, 1): x(0) = 0, x(1) = 1 ′ η x(η)}, if |x (t)| > M1 for all t ∈ [0, 1], then

0

1 s ηs

f t, x(t), x ′ (t) + e(t) dt ds = 0;

(2) There exists M2 > 0, such that for all v ∈ R with |v| > M2 one has either

or

v f (t, vt, v) + e(t) 0 for t ∈ [0, 1],

v f (t, vt, v) + e(t) 0 for t ∈ [0, 1];

(3) pg(t, x, p) 0 for all (t, x, p) ∈ [0, 1] × [−M, M] × R;


505

(4) |h(t, x, p)| a(t)|x| + b(t)|p| + u(t)|x|r + v(t)|p|k + c(t) for (t, x, p) ∈ [0, 1] × [−M, M] × R where a, b, u, v are in L1 [0, 1] and 0 r, k < 1. Then, the BVP (3.26), (3.30) with αη = 1 has at least one solution in C 1 [0, 1] provided that 1

a 1 + b 1 < . 2 Theorem 3.21 is taken over from [16]. For the proof of Theorem 3.26 we refer to [15]. Other results are given by Gupta in [27,34]. In [16] is also proved the following uniqueness result. T HEOREM 3.27. Suppose that the conditions (1) and (2) in Theorem 3.21 are replaced by the following conditions respectively: (1) There exist functions p, q in L1 [0, 1] such that f (t, u1 , v1 ) − f (t, u2 , v2 ) p(t)|u1 − u2 | + q(t)|v1 − v2 |

for t ∈ [0, 1] and (u1 , v1 ), (u2 , v2 ) ∈ R2 . (2) There exists n > l 0 such that

f (t, u1 , v1 ) − f (t, u2 , v2 ) −l|u1 − u2 | + n|v1 − v2 |

for t ∈ [0, 1], (u1 , v1 ), (u2 , v2 ) ∈ R2 . Then the BVP (3.26), (3.30) with αη = 1 has exactly one solution in C 1 [0, 1] provided that l 2 p 1 + q 1 + < 1. n 3.7. m-point boundary value problems reduced to four-point boundary value problems Let f : [0, 1]×R2 → R be either a continuous or a Carathéodory’s function and e : [0, 1] → R be a function in L1 [0, 1], ci , aj ∈ R, with all of the ci ’s, and all of aj ’s, having the same sign, ξi , τj ∈ (0, 1), i = 1, 2, . . . , m − 2, j = 1, 2, . . . , n − 2, 0 < ξ1 < ξ2 < · · · < ξm−2 < 1, 0 < τ1 < τ2 < · · · < τn−2 < 1. Consider the following second-order ordinary differential equation x ′′ (t) = f t, x(t), x ′ (t) + e(t),

t ∈ (0, 1)

(3.38)

subject to one of the following boundary conditions

x(0) =

m−2 i=1

ci x ′ (ξi ),

x(1) =

n−2 j =1

aj x(τj ),

(3.39)

506

S.K. Ntouyas

x(0) =

m−2

x(0) =

m−2

x(0) =

m−2

ci x ′ (ξi ),

x ′ (1) =

i=1

ci x ′ (ξi ),

x(1) =

i=1

i=1

ai x ′ (τj ),

(3.40)

ai x(τj ),

(3.41)

j =1

n−2 j =1

x ′ (1) =

ci x(ξi ),

n−2

n−2

ai x ′ (τj ).

(3.42)

j =1

It is well known that if a function x ∈ C 1 satisfies one of the boundary conditions (3.39)– (3.42) and ci , aj , i = 1, 2, . . . , m − 2, j = 1, 2, . . . , n − 2 are as above, then there exist ζ ∈ [ξ1 , ξm−2 ], η ∈ [τ1 , τn−2 ] such that x(0) = γ x ′ (ζ ),

x(1) = αx(η),

(3.43)

x(0) = γ x (ζ ),

x (1) = αx (η),

(3.44)

x(0) = γ x(ζ ),

x(1) = αx(η),

(3.45)

′

′

′

′

′

(3.46) x(0) = γ x(ζ ), x (1) = αx (η), m−2 respectively with γ = i=1 ci , α = n−2 j =1 aj . As in the case of m-point BVPs which are reduced to three-point BVPs, we shall prove an existence result the BVP (3.38)–(3.39), proving first an existence result for the BVP (3.38), (3.43), and using the a priori bounds obtained for this problem for the BVP (3.38)– (3.39). In the next lemma we obtain the needed a priori bounds, which are independent of ζ and η, for the BVP (3.38), (3.43). L EMMA 3.28. Let ζ , η ∈ (0, 1) is given and x(t) ∈ W 2,1 (0, 1) be such that x(0) = γ x ′ (ζ ), x(1) = αx(η). Then

x ∞ A x ′ ∞ ,

x ′ ∞ B x ′′ 1

where A=

1,

L, 1 + |γ |,

if α 0, if α > 0, α = 1, if α = 1

and  1,     1   ,  1−Q B= 1    ,     1−S 1,

if α 0, γ = 0, if α 0, γ = 0, if α > 0, α = 1, if α = 1,


507

where for α > 0, α = 1,  1   M = min α, < 1,   α     1 1−η |α|(1 − η) L = min ,1 + ,1 + , 1 + |γ | ,  1−M |1 − α| |1 − α|      |1 − α| |1 − α| 1   S = min L, L, L 1−η α(1 − η) |γ | for α < 0,

1−α 1 1−α , , Q = min 1 − η |α|(1 − η) |γ | and for α = 0, Q =

1 |γ |

provided Q < 1 and S < 1.

P ROOF. We consider the following cases: Case 1: α 0. In this case x(1)x(η) 0 and accordingly there exists a θ ∈ [η, 1] such that x(θ ) = 0. Hence it follows that x ∞ x ′ ∞ . Also if γ = 0, we have from x(0) = 0 and x(θ ) = 0 that there exists a z ∈ (0, θ) such that x ′ (z) = 0. Accordingly, we get that

x ′ ∞ x ′′ 1 . Suppose, now, that α < 0 and γ = 0. Next we see from Mean Value Theorem there exists ω ∈ (η, 1) such that (α − 1)x(η) = x(1) − x(η) = (1 − η)x ′ (ω) and hence x(η) =

1−η ′ x (ω). α−1

Also, since x(1) = αx(η) we get x(1) =

α(1 − η) ′ x (ω). α−1

From the relations x ′ (t) = x ′ (ω) + x ′ (t) = x ′ (ω) +

t ω t ω

x ′′ (s) ds =

α−1 x(η) + 1−η

t ω

α−1 x(1) + x ′′ (s) ds = α(1 − η)

x ′′ (s) ds,

t

x ′′ (s) ds

ω

and ′

′

x (t) = x (ζ ) +

0

t

1 x (s) ds = x(0) + γ ′′

0

t

x ′′ (s) ds

508

S.K. Ntouyas

then follows that

x ′ ∞

1

x ′′ 1 , 1−Q

1−α 1 where Q = min{ 1−α 1−η , |α|(1−η) , |γ | } if Q < 1. Finally, for α = 0, γ = 0 it is easy to see that 1 Q = |γ1 | since we require that Q < 1 and 1−η > 1. Case 2: α > 0, α = 1. We first consider the relations

x(t) = x(1) +

x(t) = x(η) +

t

1

x ′ (s) ds = αx(η) +

t

x ′ (s) ds

1

and t

η

1 x (s) ds = x(1) + α ′

t

x ′ (s) ds.

η

Since, now, M = min{α, α1 } < 1, we get from the above relations that

x ∞

1

x ′ ∞ . 1−M

Next, we get the relations x(t) = x(1) +

x(t) = x(η) +

t

1

x ′ (s) ds =

α(1 − η) ′ x (ω) + α−1

t

x ′ (s) ds

1

and t

η

1−η ′ x (s) ds = x (ω) + α−1 ′

t

x ′ (s) ds.

η

From these relations and t t x ′ (s) ds = γ x ′ (ζ ) + x ′ (s) ds x(t) = x(0) + 0

0

it is immediate that

x ∞ L x ′ ∞ , 1 ,1 + where L = min{ 1−M

x ′ ∞

1−η |α|(1−η) |α−1| , 1 + |α−1| , 1 + |γ |}.

1

x ′′ 1 , 1−S

Further, we have


509

|1−α| 1 where S = min{ |1−α| 1−η L, α(1−η) L, |γ | L} if S < 1. ′ imCase 3: α = 1. Since x(1) = x(η) there exists an ω ∈ (η, t 1)′ with x (ω)′= 0. Itist then ′ ′′ mediate that x ∞ x 1 . Also since x(t) = x(0) + 0 x (s) ds = γ x (ζ ) + 0 x ′ (s) ds, it is immediate that x ∞ (1 + |γ |) x ′ ∞ . This completes the proof of the lemma.

T HEOREM 3.29. Let f : [0, 1] × R2 → R be a function satisfying Carathéodory’s conditions. Assume that (3.12) holds. Also let η ∈ (0, 1) be given and α, γ ∈ R with 1 + γ = α(γ + η). Moreover we assume that Q < 1 and S < 1. Then the BVP (3.38), (3.43) has at least one solution in C 1 [0, 1] provided  p + q < 1, 1 1    p + q < 1 − Q, 1

1

L p 1 + q 1 < 1 − S,    1 + |γ | p 1 + q 1 < 1,

α 0, γ = 0, α 0, γ = 0, α > 0, α = 1, α = 1.

P ROOF. Let X be the Banach space C 1 [0, 1] and Y denote the Banach space L1 (0, 1) with their usual norms. We denote a linear mapping L : D(L) ⊂ X → Y by setting D(L) = x ∈ W 2,1 (0, 1): x(0) = γ x ′ (ζ ), x(1) = αx(η) ,

and for x ∈ D(L),

Lx = x ′′ . We also define a nonlinear mapping N : X → Y by setting (N x)(t) = f t, x(t), x ′ (t) ,

t ∈ [0, 1].

We note that N is a bounded mapping from X into Y . Next, it is easy to see that the linear mapping L : D(L) ⊂ X → Y , is one-to-one mapping. Next, the linear mapping K : Y → X, defined for y ∈ Y by (Ky)(t) =

0

t

(t − s)y(s) ds + γ

ζ

y(s) ds

0

η γ +t α (η − s)y(s) ds 1 + γ − α(γ + η) 0 ζ 1 y(s) ds , (1 − s)y(s) ds + γ (α − 1) −

+

0

0

t ∈ [0, 1]

is such that for y ∈ Y , Ky ∈ D(L) and LKy = y; and for u ∈ D(L), KLu = u. Furthermore, it follows easily using the Arzelá–Ascoli theorem that KN maps bounded subsets of X into a relatively compact subsets of X. Hence KN : X → X is a compact mapping.

510

S.K. Ntouyas

We, next, note that x ∈ C 1 [0, 1] is a solution of the BVP (3.38), (3.43) if and only if x is a solution to the operator equation Lx = N x + e. Now, the operator equation Lx = N x + e is equivalent to the equation x = KNx + Ke. We apply the Leray–Schauder continuation theorem to obtain the existence of a solution for x = KNx + Ke or equivalently to the BVP (3.38), (3.43). To do this, it suffices to verify that the set of all possible solutions of the family of equations x ′′ (t) = λf t, x(t), x ′ (t) + λe(t), ′

x(0) = γ x (0),

t ∈ (0, 1),

x(1) = αx(η)

(3.47) (3.48)

is, a priori, bounded in C 1 [0, 1] by a constant independent of λ ∈ [0, 1]. (I) Assume that α 0, γ = 0. From Lemma 3.28 we have

x ∞ x ′ ∞ x ′′ 1 . Let, now, x(t) be a solution of (3.47)–(3.48) for some λ ∈ [0, 1], so that x ∈ W 2,1 (0, 1) with x(0) = γ x ′ (ζ ), x(1) = αx(η). We then get

x ′′ 1 = λf t, x(t), x ′ (t) + e(t)1

p 1 x ∞ + q 1 x ′ ∞ + r 1 + e 1 p 1 + q 1 x ′′ 1 + r 1 + e 1 .

It follows from our assumption that there is a constant c, independent of λ ∈ [0, 1], such that

x ′′ 1 c. It is now immediate that the set of solutions of the family of equations (3.47)–(3.48) is, a priori, bounded in C 1 [0, 1] by a constant independent of λ ∈ [0, 1]. (II) Assume that α 0, γ = 0. Then we have, by Lemma 3.28 that

x ∞ x ′ ∞ ,

x ′ ∞

1

x ′′ 1 . 1−Q

We then get

x ′′ 1 = λf t, x(t), x ′ (t) + e(t)1


511

p 1 x ∞ + q 1 x ′ ∞ + r 1 + e 1 1

x ′′ 1 + r 1 + e 1 . p 1 + q 1 1−Q We proceed as in case (I). The process for the other cases is similar to the previous cases and we omit the details. This completes the proof of the theorem. We study now the multi-point BVP (3.38)–(3.39) using the a priori estimates that can be obtained for a four-point BVP (3.38), (3.43). This is because for every solution x(t) of the BVP (3.38)–(3.39), there exist η ∈ [ξ1 , ξm−2 ], ζ ∈ [τ1 , τn−2], depending on, x(t), such that m−2 x(t) is also a solution of the BVP (3.38), (3.43) with γ = i=1 ci and α = n−2 j =1 aj . The proof is quite similar to the proof of Theorem 3.29 and uses the a priori estimates obtained in the proof of Lemma 3.28 for the set of solutions of the family of equations (3.38), (3.43). T HEOREM 3.30. Let f : [0, 1] × R2 → R be a function satisfying Carathéodory’s conditions. Assume that (3.12) holds. Let ci , aj ∈ R, with all of the ci ’s (respectively, aj ’s), having the same sign, ξi , τj ∈ (0, 1), i = 1, 2, . . . , m − 2, j = 1, 2, . . . , n − 2, 0 < ξ1 < ξ2 < · · · < ξm−2 < 1, 0 < τ1 < τ2 < · · · < τn−2 < 1 be given. Suppose that 8m−2 98 9 n−2 n−2 1+ aj τj = 0. aj − ci 1 − j =1

i=1

j =1

m−2 ′ ′ Let γ = i=1 ci and α = n−2 j =1 aj . Moreover we assume that Q < 1, and S < 1, where M = min{α, α1 } < 1, 1 − τ1 |α|(1 − τ1 ) 1 ,1 + ,1 + , 1 + |γ | , 1−M |1 − α| |1 − α| 1 |1 − α| |1 − α| ′ L, L , S = min L, 1 − τn−2 α(1 − τn−2 ) |γ | 1−α 1 1−α ′ Q = min . , , 1 − τn−2 |α|(1 − τn−2 ) |γ | L′ = min

Then the BVP (3.38)–(3.39) has at least one solution in C 1 [0, 1] provided  p + q < 1, 1 1    p + q < 1 − Q′ , 1

1

L′ p 1 + q 1 < 1 − S ′ ,    1 + |γ | p 1 + q 1 < 1,

α 0, γ = 0, α 0, γ = 0, α > 0, α = 1, α = 1.

512

S.K. Ntouyas

P ROOF. Let X be the Banach space C 1 [0, 1] and Y denote the Banach space L1 (0, 1) with their usual norms. We denote a linear mapping L : D(L) ⊂ X → Y by setting

D(L) = x ∈ W

2,1

(0, 1): x(0) =

m−2 i=1

′

ci x (ξi ), x(1) =

n−2

(

aj x(τj ) ,

j =1

and for x ∈ D(L), Lx = x ′′ . We also define a nonlinear mapping N : X → Y by setting (N x)(t) = f t, x(t), x ′ (t) , t ∈ [0, 1].

We note that N , is a bounded mapping from X into Y . Next, it is easy to see that the linear mapping L : D(L) ⊂ X → Y , is one-to-one mapping. Next, the linear mapping K : Y → X, defined for y ∈ Y by

(Ky)(t) =

t

0

(t − s)y(s) ds + ct + k,

t ∈ [0, 1],

where c and k are given by 4

8m−2 98 9 n−2 5 n−2 ci 1 − aj − aj τj c 1+ j =1

i=1

=

8n−2 j =1

+

aj − 1

n−2

aj

98m−2

ci

ξi

y(s) ds

0

τj

(τj − s)y(s) ds −

0

j =1

i=1

j =1

9

1 0

(1 − s)y(s) ds

and 4

5 9 n−2 8m−2 98 n−2 m−2 n−2 ci aj aj τj k = aj − 1+ ci 1 − j =1

i=1

−

m−2 i=1

ci

0

1

j =1

(1 − s)y(s) ds + 1 −

i=1

n−2 j =1

aj τ j

0

j =1

9 m−2 i=1

ci

τj

(τj − s)y(s) ds

ξi

y(s) ds,

0

is such that for y ∈ Y , Ky ∈ D(L)and LKy = y; and for u ∈ D(L), KLu = u. Furthermore, it follows easily using the Arzelá–Ascoli theorem that KN maps bounded subsets of X into a relatively compact subset of X. Hence KN : X → X is a compact mapping.


513

We, next, note that x ∈ C 1 [0, 1] is a solution of the BVP (3.38)–(3.39) if and only if x is a solution to the operator equation Lx = N x + e. Now, the operator equation Lx = N x + e is equivalent to the equation x = KNx + Ke. We apply the Leray–Schauder continuation theorem to obtain the existence of a solution for x = KNx + Ke or equivalently to the BVP (3.38)–(3.39). To do this, it suffices to verify that the set of all possible solutions of the family of equations x ′′ (t) = λf t, x(t), x ′ (t) + λe(t), x(0) =

m−2

ci x ′ (ξi ),

i=1

x(1) =

n−2

t ∈ (0, 1),

(3.49)

aj x(τj )

(3.50)

j =1

is, a priori, bounded in C 1 [0, 1] by a constant independent of λ ∈ [0, 1]. Let, now, x(t) be a solution of (3.49)–(3.50) for some λ ∈ [0, 1], so that x ∈ W 2,1 (0, 1) n−2 m−2 ′ with x(0) = i=1 ci x (ξi ), x(1) = j =1 aj x(τj ). Accordingly, there exist ζ ∈ [ξ1 , ξm−2 ] and η ∈ [τ1 , τn−2 ] depending on x(t), such that x(t) is a solution of the four point BVP x ′′ (t) = λf t, x(t), x ′ (t) + λe(t), x(0) = γ x ′ (ζ ),

t ∈ (0, 1),

x(1) = αx(η).

It then follows, as in the proof of Theorem 3.30 that there is a constant c, independent of λ ∈ [0, 1], and η ∈ [ξ1 , ξm−2 ], ζ ∈ [τ1 , τn−2 ] such that

x ∞ c1 x ′ ∞ c2 x ′′ 1 c, where c1 , c2 are constants independent of λ, η, ζ . Thus the set of solutions of the family of equations is, a priori, bounded in C 1 [0, 1] by a constant, independent of λ ∈ [0, 1]. This completes the proof of the theorem. Theorems 3.29 and 3.30 are taken from [35]. Similar results for the BVP (3.38), (3.40) are proved in [35] and for the BVPs (3.38), (3.41) and (3.38), (3.42) in [36].

3.8. The general case Let f : [0, 1] × R2 → R be either a continuous or a Carathéodory’s function and e(t) ∈ L1 [0, 1]. Let ξi , ηj , ci , aj , i = 1, 2, . . . , m − 2, j = 1, 2, . . . , n − 2, 0 < ξ1 < ξ2 < · · ·
0 (m1 + 1 i m − 2), or there exists n1 ∈ {1, 2, . . . , n − 3} such that aj > 0 (1 j n1 ), aj < 0 (n1 + 1 j n − 2), furthermore (H1) There exist functions a, b, c, r in L1 [0, 1], and constant θ ∈ [0, 1) such that for all (x, y) ∈ R2 , t ∈ [0, 1] either f (t, x, y) a(t)|x| + b(t)|y| + c(t)|y|θ + r(t) or else f (t, x, y) a(t)|x| + b(t)|y| + c(t)|x|θ + r(t).

518

S.K. Ntouyas

(H2) There exists constant M > 0 such that, for x ∈ dom(L), if |x(t)| > M for all t ∈ [0, 1], then m−2

ci

i=1

ξi

0

0

s

f τ, x(τ ), x ′ (τ ) + e(τ ) dτ ds = 0.

(H3) There exists constant M ∗ > 0 such that for any d ∈ R, if |d| > M ∗ , then either d

m−2

ci

i=1

ξi

0

0

s

f (τ, d, 0) + e(τ ) dτ ds < 0

or else d

m−2 i=1

ci

ξi 0

0

s

f (τ, d, 0) + e(τ ) dτ ds > 0.

Then, for every e ∈ L1 [0, 1], the BVP (3.51)–(3.52) in the case (1), i.e. when m−2 i=1 ci ξi = n−2 m−2 2 2 0, γ = 1, α = 1, i=1 ci ξi = 0, j =1 aj ηj = 1, has at least one solution in C 1 [0, 1] provided 1

a 1 + b 1 < , -1 + 1

n−2

i=j |aj |(1 − ηj ) where -1 = a + . 1 − n−2 aj ηj j =1

3.9. Positive solutions of some nonlocal boundary value problems There is much attention focused on question of positive solutions of BVPs for ordinary differential equations. Much of interest is due to the applicability of certain Krasnosel’skii fixed point theorems or the Leggett–Williams multiple fixed point theorem, or a synthesis of both to obtain positive solutions or multiple positive solutions which lie in a cone. Here we present some of the results on positive solutions of some nonlocal BVPs. Consider the differential equation x ′′ + a(t)f (x) = 0,

t ∈ (0, 1)

(3.80)

with the boundary conditions x(0) = 0,

αx(η) = x(1),

(3.81)

where 0 < η < 1. Our purpose here is to give some existence results for positive solutions to (3.80)–(3.81), assuming that αη < 1 and f is either superlinear or sublinear.


519

Set f (x) . x→∞ x

f (x) , x→0+ x

f∞ = lim

f0 = lim

Then f0 = 0 and f∞ = ∞ correspond to the superlinear case, and f0 = ∞ and f∞ = 0 correspond to the sublinear case. By the positive solution of the BVP (3.80)–(3.81) we understand a function x(t) which is positive on 0 < t < 1 and satisfies the differential equation (3.80) and the boundary conditions (3.81). The key tool in our approach is the following Krasnosel’skii’s fixed point theorem in a cone [54] (see also [21]). T HEOREM 3.33. Let E be a Banach space, and let K ⊂ E be a cone. Assume Ω1 , Ω2 are open bounded subsets of E with 0 ∈ Ω1 , Ω 1 ⊂ Ω2 , and let A : K ∩ Ω 2 \ Ω1 −→ K

be a completely continuous operator such that (i) Au u , u ∈ K ∩ ∂Ω1 , and Au u , u ∈ K ∩ ∂Ω2 ; or (ii) Au u , u ∈ K ∩ ∂Ω1 , and Au u , u ∈ K ∩ ∂Ω2 . Then A has a fixed point in K ∩ (Ω 2 \ Ω1 ). We give first some preliminary lemmas. L EMMA 3.34. Let αη = 1 then for y ∈ C[0, 1], the problem x ′′ (t) + y(t) = 0, x(0) = 0,

t ∈ (0, 1),

(3.82)

αx(η) = x(1)

(3.83)

has a unique solution x(t) = −

+

0

t

(t − s)y(s) ds −

t 1 − αη

0

1

αt 1 − αη

0

η

(η − s)y(s) ds

(1 − s)y(s) ds.

L EMMA 3.35. Let 0 < α < η1 . If y ∈ C[0, 1] and y 0, for t ∈ (0, 1) then the unique solution x of the problem (3.82)–(3.83) satisfies x(t) 0, t ∈ [0, 1]. P ROOF. From the fact that x ′′ (t) = −y(t) 0, we know that the graph of x(t) is concave down on (0, 1). So, if x(1) 0, then the concavity of x and the boundary condition x(0) = 0 imply that x 0 for t ∈ [0, 1]. If x(1) < 0, then we have that x(η) < 0 and x(1) = αx(η) > η1 x(η) which contradicts to the concavity of x.

520

S.K. Ntouyas

L EMMA 3.36. Let αη > 1. If y ∈ C[0, 1] and y 0, for t ∈ (0, 1) then (3.82)–(3.83) has no positive solution. P ROOF. Assume that (3.82)–(3.83) has a positive solution x. If x(1) > 0, then x(η) > 0 αx(η) x(η) and x(1) 1 = 1 > η which contradicts to the concavity of x. If x(1) = 0 and x(τ ) > 0 for some τ ∈ (0, 1), then x(η) − x(1) = 0, τ = η. If τ ∈ (0, η), then x(τ ) > x(η) = x(1), which contradicts to the concavity of x again. L EMMA 3.37. Let 0 < α < η1 . If y ∈ C[0, 1] and y 0, for t ∈ (0, 1) then the unique solution x of the problem (3.82)–(3.83) satisfies inf x(t) γ x ,

t∈[η,1]

where γ = min{αη, α(1−η) 1−αη , η}. P ROOF. We divide the proof into two steps. Step 1. We deal with the case 0 < α < 1. In this case, by Lemma 3.35, we know that x(η) x(1). Set x t¯ = x .

If t¯ η < 1, then mint∈[η,1] x(t) = x(1) and 1 − αη x(1) − x(η) (0 − 1) = x(1) . x t¯ x(1) + 1−η α(1 − η) Then min x(t)

t∈[η,1]

α(1 − η) . 1 − αη

If η < t¯ < 1, then mint∈[η,1] x(t) = x(1). From the concavity of x, we know that

x(t¯ ) t¯

which combined with boundary condition αx(η) = x(1), gives

x . Therefore

x(1) αη

x(t¯ ) t¯

x(t¯ ) =

min x(t) αη x .

t∈[η,1]

Step 2. We deal with the case 1 < α < η1 . In this case, we have x(η) x(1). Set x t¯ = x .

x(η) η


521

Then we can choose t¯ such that η t¯ 1. This contradicts to the concavity of x. From x(η) x(1) and the concavity of x, we know that mint∈[η,1] x(t) = x(η). Using the conx(t¯ ) cavity of x and Lemma 3.35, we have x(η) η t¯ which implies that min x(t) η x .

t∈[η,1]

This completes the proof. The main result here is the following: T HEOREM 3.38. Assume that (A1) f ∈ C([0, ∞), [0, ∞)); (A2) a ∈ C([0, 1], [0, ∞)) and there exists x0 ∈ [η, 1] such that a(x0 ) > 0. Then the BVP (3.80)–(3.81) has at least one positive solution in the case (i) f0 = 0 and f∞ = ∞ (superlinear) or (ii) f0 = ∞ and f∞ = 0 (sublinear).

P ROOF. (i) Suppose that f0 = 0 and f∞ = ∞. We wish to show the existence of a positive solution of (3.80)–(3.81). Now (3.80)–(3.81) has a solution x = x(t) if and only if x solves the operator equation x(t) = −

+

0

t

(t − s)a(s)f x(s) ds −

t 1 − αη

1

0

:= Ax(t).

αt 1 − αη

η 0

(1 − s)a(s)f x(s) ds

(η − s)a(s)f x(s) ds

Denote 2 K = x: x ∈ C[0, 1], x 0, min x(t) γ x . ηt1

It is obvious that K is a cone in C[0, 1]. Moreover, by Lemma 3.37, AK ⊂ K. It is also easy to check that A : K → K is completely continuous. Now f0 = 0, we may choose H1 > 0 so that f (x) ǫx, for 0 < x < H1 , where ǫ > 0 satisfies ǫ 1 − αη

0

1

(1 − s)a(s) ds 1.

Thus, if x ∈ K and x = H1 we get t Ax(t) 1 − αη

0

1


522

S.K. Ntouyas

t 1 − αη ǫ 1 − αη ǫ 1 − αη

1

(1 − s)a(s)ǫx(s) ds

0 1

(1 − s)a(s) ds x

0 1 0

(1 − s)a(s) dsH1 .

Now if we let Ω1 = x ∈ C[0, 1]: x < H1 ,

then Ax x , for x ∈ K ∩ ∂Ω1 . 2 > 0 such that f (x) ρx, for x H 2 , where ρ Further since f∞ = ∞, there exists H is chosen so that ηγ ρ 1 − αη

1

(1 − s)a(s) ds > 1.

η

Let H2 = max{2H1 , Hγ2 } and Ω2 = {x ∈ C[0, 1]: x < H2 }, then x ∈ K and x = H2 implies 2 , min x(t) γ x H

ηt1

and so

Ax(η) = −

0

η

(η − s)a(s)f x(s) ds −

1

αη 1 − αη

0

η


η (1 − s)a(s)f x(s) ds 1 − αη 0 η 1 (η − s)a(s)f x(s) ds =− 1 − αη 0 1 η + (1 − s)a(s)f x(s) ds 1 − αη 0 1 η η 1 = a(s)f x(s) ds + sa(s)f x(s) ds 1 − αη η 1 − αη 0 1 η − sa(s)f x(s) ds 1 − αη 0 1 η a(s)f x(s) ds 1 − αη η +


523

1 η − sa(s)f x(s) ds (by η < 1) 1 − αη η 1 η = (1 − s)a(s)f x(s) ds. 1 − αη η Hence, for x ∈ K ∩ ∂Ω2 , ηγ 1 − αη

Ax ρ

1

η

(1 − s)a(s) ds x x .

Therefore, by the first part of Theorem 3.33, it follows that A has a fixed point in K ∩ (Ω 2 \ Ω1 ), such that H1 x H2 . This completes the superlinear part of the theorem. (ii) Suppose next that f0 = ∞ and f∞ = 0. We first choose H3 > 0 such that f (x) Mx for 0 < x < H3 , where Mγ

η 1 − αη

η

1

(1 − s)a(s) ds 1.

Then Ax(η) = −

0

η


1

αη 1 − αη

η (1 − s)a(s)f x(s) ds 1 − αη 0 1 η (1 − s)a(s)f x(s) ds 1 − αη η 1 η (1 − s)a(s)Mx(s) ds 1 − αη η 1 η (1 − s)a(s)Mγ ds x

1 − αη η +

0

η


H3 . Thus, we may let Ω3 = {x ∈ C[0, 1]: x < H3 } so that

Ax x ,

x ∈ K ∩ ∂Ω3 .

4 > 0 so that f (x) λx for x H 4 , where λ > 0 Now, since f∞ = 0, there exist H satisfies λ 1 − αη

0

1

(1 − s)a(s) ds 1.

524

S.K. Ntouyas

We consider two cases: Case 1. Suppose f is bounded, say f (x) N for all x ∈ [0, ∞). In this case choose H4 = max 2H3 ,

N 1 − αη

0

1

(1 − s)a(s) ds

so that for x ∈ K with x = H4 we have Ax(t) = −

t

0


1

αt 1 − αη

η

0

t (1 − s)a(s)f x(s) ds 1 − αη 0 1 t (1 − s)a(s)f x(s) ds 1 − αη 0 1 1 (1 − s)a(s)N ds 1 − αη 0 +


H4

and therefore Ax x . Case 2. If f is unbounded, then we know from (A1) that there is H4 : H4 > 4 } such that max{2H3 , γ1 H f (x) f (H4 )

for 0 < x H4 .

Then for x ∈ K and x = H4 we have Ax(t) = −

0

t


1

αt 1 − αη


t 1 − αη 0 1 t (1 − s)a(s)f (H4 ) ds 1 − αη 0 1 1 (1 − s)a(s)λH4 ds 1 − αη 0 +

H4 .

Therefore, in either case we may put Ω4 = x ∈ C[0, 1]: x < H4 ,

0

η



525

and for x ∈ K ∩ ∂Ω4 we may have Ax x . By the second part of Theorem 3.33, if follows that the BVP (3.80)–(3.81) has a positive solution. The proof of the theorem is completed. The previous results are taken from [69]. Theorem 3.38 was proved either for sub- or superlinear case. Therefore the following questions are natural: • Whether or not we can obtain similar conclusion, if f0 = f∞ = 0 or f0 = f∞ = ∞; / {0, ∞}. • Whether or not we can obtain similar conclusion, if f0 , f∞ ∈ Motivated by the results in [69], Liu in [57] established some simple criteria for the existence of positive solutions of the BVP (3.80)–(3.81), which gives a positive answer to the questions stated above. The key tool in his approach is the following fixed point index theorem [21]. T HEOREM 3.39. Let E be Banach space and K ⊂ E be a cone in E. Let r > 0, and define Ωr = {x ∈ K: x < r}. Assume A : Ω r → K is a completely continuous operator such that Ax = x for x ∈ ∂Ωr . (i) If Ax x for x ∈ ∂Ωr , then i(A, Ωr , K) = 1. (ii) If Ax x for x ∈ ∂Ωr , then i(A, Ωr , K) = 0. In what follows, for the sake of convenience, set 1 −1 Λ1 = (1 − αη) (1 − s)a(s) ds , 0

1 −1 . (1 − s)a(s) ds Λ2 = (1 − αη) ηγ η

T HEOREM 3.40. Assume that the following assumptions are satisfied: (H1) f0 = f∞ = ∞. (H2) There exist constants ρ1 > 0 and M1 ∈ (0, Λ1 ) such that f (u) M1 ρ1 , u ∈ [0, ρ1 ]. Then the BVP (3.80)–(3.81) has at least two positive solutions x1 and x2 such that 0 < x1 < ρ1 < x2 . P ROOF. At first, in view of f0 = ∞, then for any M∗ ∈ (Λ2 , ∞), there exist ρ∗ ∈ (0, ρ1 ) such that 0 x ρ∗ .

f (x) M∗ x,

Set Ωρ∗ = {x ∈ K: x < ρ∗ }. Since x ∈ ∂Ωρ∗ ⊂ K, we have minηt1 x(t) γ x . Thus, for any x ∈ ∂Ωρ∗ , we have Ax(η) = −

0

η


αη 1 − αη

0

η


526

S.K. Ntouyas

=

1 η + (1 − s)a(s)f x(s) ds 1 − αη 0 1 η η 1−η a(s)f x(s) ds + sa(s)f x(s) ds 1 − αη η 1 − αη 0 1 η − sa(s)f x(s) ds 1 − αη η 1 η (1 − s)a(s)f x(s) ds 1 − αη η 1 η (1 − s)a(s)M∗ x(s) ds 1 − αη η γ ηM∗ 1 (1 − s)a(s) x ds 1 − αη η

> x , which yields

Ax > x ,

for y ∈ ∂Ωρ∗ .

Hence, Theorem 3.39 implies i(A, Ωρ∗ , K) = 0. Next, since f∞ = ∞, then for any M ∗ ∈ (Λ2 , ∞), then there exist ρ ∗ > ρ1 such that f (x) M ∗ x,

0 x γρ ∗ .

Set Ωρ ∗ = {x ∈ K: x < ρ ∗ } for x ∈ ∂Ωρ ∗ . Since x ∈ K, we have minηt1 x(t) γ x = γρ ∗ . Thus, for any x ∈ ∂Ωρ ∗ , we have Ax(η) = −

0

η


αη 1 − αη

1 η (1 − s)a(s)f x(s) ds 1 − αη 0 1 η (1 − s)a(s)f x(s) ds 1 − αη η 1 η (1 − s)a(s)M ∗ x(s) ds 1 − αη η γ ηM ∗ 1 (1 − s)a(s) x ds 1 − αη η

+

> x ,

0

η



527

which implies

Ax > x ,

for y ∈ ∂Ωρ ∗ .

Hence, Theorem 3.39 yields i(A, Ωρ∗ , K) = 0. Finally, set Ωρ1 = {x ∈ K: x < ρ1 }. For any x ∈ ∂Ωρ1 we obtain Ax(t)

t 1 − αη M1 ρ 1 1 − αη

1

0

1

(1 − s)a(s)f x(s) ds (1 − s)a(s) ds

0

< ρ1 = x , which yields

Ax < x ,

for y ∈ ∂Ωρ1 .

Thus, Theorem 3.39 again shows that i(A, Ωρ1 , K) = 1. Hence, since ρ∗ < ρ1 < ρ ∗ it follows from the additivity of the fixed point index that i A, Ωρ1 \ Ω ρ∗ , K = 1,

i A, Ωρ ∗ \ Ω ρ1 , K = −1.

Thus, A has a fixed point x1 in Ωρ1 \ Ω ρ∗ , and a fixed point x2 in Ωρ ∗ \ Ω ρ1 . Both are positive solutions, 0 < x1 < ρ1 < x2 , and the proof of the theorem is complete. T HEOREM 3.41. Assume that the following assumptions are satisfied: (H3) f0 = f∞ = 0. (H4) There exist constants ρ2 > 0 and M2 ∈ (Λ2 , ∞) such that f (u) M2 ρ2 , u ∈ [γρ2 , ρ2 ]. Then the BVP (3.80)–(3.81) has at least two positive solutions x1 and x2 such that 0 < x1 < ρ2 < x2 . P ROOF. First, since f0 = 0, for any ε ∈ (0, Λ1 ), there exists ρ∗ ∈ (0, ρ2 ) such that f (x) εx,

for x ∈ [0, ρ∗ ].

Setting Ωρ∗ = {x ∈ K: x < ρ∗ } for any x ∈ ∂Ωρ∗ , we get t Ax(t) 1 − αη

ερ∗ 1 − αη

1

0

0

1

(1 − s)a(s)f x(s) ds (1 − s)a(s) ds < ρ∗ = x ,

528

S.K. Ntouyas

which yields

Ax < x ,

for x ∈ ∂Ωρ∗ .

Thus Theorem 3.39 implies i(A, Ωρ∗ , K) = 1. Second, in view f∞ = 0, then for any ε ∈ (0, Λ1 ), there exists ρ0 > ρ2 such that f (x) εx,

for x ∈ [ρ0 , ∞),

and we consider two cases. Case (i). Suppose that f is unbounded; then from f ∈ C([0, ∞), [0, ∞)), we know that there is ρ ∗ > ρ0 such that f (x) f (ρ ∗ ), for x ∈ [0, ρ ∗ ]. Since ρ ∗ > ρ0 , one has f (x) f (ρ ∗ ) ερ ∗ , for x ∈ [0, ρ ∗ ]. For x ∈ K, x = ρ ∗ we obtain t Ax(t) 1 − αη

ερ∗ 1 − αη

1 0 1

(1 − s)a(s)f x(s) ds (1 − s)a(s) ds < ρ∗ = x .

0

Case (ii). Suppose that f is bounded, say f (x) L. Taking ρ ∗ max{L/ε, ρ2 }, for x ∈ K, x = ρ ∗ one has Ax(t)

t 1 − αη L 1 − αη

1 0 1 0

(1 − s)a(s)f x(s) ds (1 − s)a(s) ds < ρ∗ = x .

Hence, in either case, we always may set Ωρ ∗ = {x ∈ K: x < ρ ∗ } such that

Ax < x ,

for x ∈ ∂Ωρ∗ .

Thus Theorem 3.39 implies i(A, Ωρ∗ , K) = 1. Finally set Ωρ2 = {x ∈ K: x < ρ2 }, for x ∈ ∂Ωρ2 , since x ∈ K, minηt1 x(t) γ x = γρ2 , and hence we can get Ax(η)

η 1 − αη

η

γ ηM2 ρ2 1 − αη

1


η

1

(1 − s)a(s) ds > ρ2 = x ,

which yields

Ax > x ,

for x ∈ ∂Ωρ2 .


529

Thus Theorem 3.39 implies i(A, Ωρ2 , K) = 0. Hence, since ρ∗ < ρ2 < ρ ∗ it follows from the additivity of the fixed point index that i A, Ωρ2 \ Ω ρ∗ , K = −1,

i A, Ωρ ∗ \ Ω ρ2 , K = 1.

Thus, A has a fixed point x1 in Ωρ2 \ Ω ρ∗ , and a fixed point x2 in Ωρ ∗ \ Ω ρ2 . Both are positive solutions, 0 < x1 < ρ2 < x2 , and the proof of the theorem is complete. / {0, ∞} we have the following For the case when f0 , f∞ ∈ T HEOREM 3.42. Suppose that (H2) and (H4) hold and that ρ1 = ρ2 . Then the BVP (3.80)– (3.81) has at least one positive solution x satisfying ρ1 < x < ρ2 or ρ2 < x < ρ1 . Theorems 3.40–3.42 were taken from [57]. A method to study the existence of positive solutions of some three-point BVPs is to write the BVP as an equivalent Hammerstein integral equation of the form x(t) =

1 0

k(t, s)a(s)f x(s) ds ≡ T x(t),

and seek fixed points of T in the cone of positive functions in the space C[0, 1]. We use the fixed point index for compact maps, which is based on Leray–Schauder degree theory, and use a well-known nonzero fixed point theorem in order to prove that T has a positive fixed point. We apply this method for the BVP (3.80)–(3.81) using the cone defined by K = x ∈ C[0, 1]: x 0, min x(t): a t b c x ,

and the following kernel (Green’s function) in the Hammerstein integral operator

k(t, s) =

 

αt 1 (η − s), t (1 − s) − 1 − αη  1 − αη 0,

sη s>η

−

t − s, 0,

st s > t.

b Let a, b ∈ (0, 1] and suppose that a a(t) dt > 0. We are able to find upper and lower bounds for k(t, s) with s fixed, of the same type. We have the same freedom in choosing the numbers a and b. Let us find the upper and lower bounds for the BVP (3.80)–(3.81). We have to exhibit Φ(s), a subinterval [a, b] ⊂ [0, 1] and a constant c ∈ (0, 1] such that k(t, s) Φ(s), k(t, s) cΦ(s),

for every t, s ∈ [0, 1], for every s ∈ [0, 1], t ∈ [a, b].

3.9.1. Upper bounds We shall show that we may take Φ(s) = max{1, α} s(1−s) 1−αη . (In this case αη < 1 but it is possible to have α > 1.)

530

S.K. Ntouyas

Case 1: s > η. t < s is simple so consider t s. Then k(t, s) = s + (αη−s)t 1−αη . If also s αη then it is a decreasing function of t so the maximum occurs when t = s and k(t, s)

s − sαη + s(αη − s) s(1 − s) = Φ(s). 1 − αη 1 − αη

If s < αη (which can happen only if α > 1) the maximum occurs at t = 1 and then k(t, s)

αη(1 − s) s(1 − s) 1 the maximum occurs when t = 1 and then

αs(1 − η) s(1 − s) α = Φ(s), 1 − αη 1 − αη

using s η. For α 1 the maximum occurs when t = s and then k(t, s) =

αs(s − η) + s(1 − s) s(1 − s) = Φ(s). 1 − αη 1 − αη

3.9.2. Lower bounds We will show that we may take arbitrary a > 0 and b 1. (1−s) a s(1−s) Case 1: s > η. For t < s, k(t, s) = t1−αη 1−αη aηΦ(s). For t s, k(t, s) = s−

t (s−αη) 1−αη .

If s > αη then the minimum occurs when t = 1 so

s(1 − s) αη(1 − s) αηΦ(s), k(t, s) αη = ηΦ(s), 1 − αη 1 − αη

α 1, α > 1.

If s αη (only possible if α > 1) the minimum is at t = s and k(t, s)

s(1 − s) ηΦ(s). 1 − αη

Case 2: s η. First suppose a t s. (This case cannot occur if α η.) Then k(t, s) = For α < 1 we have [1 − αη + (α − 1)s] 1 − αη + (α − 1)η = 1 − η so k(t, s) is increasing in t and has a minimum when t = a. Thus t[1−αη+(α−1)s] . 1−αη

k(t, s)

a [1 − η] 4a(1 − η)Φ(s), 1 − αη

since s(1 − s) 1/4. Note that 4a(1 − η) < 1 since α < η. For α > 1, k(t, s) is clearly increasing so we have k(t, s)

a a 4(1 − αη)a 1 − αη + (α − 1)s [1 − αη] Φ(s). 1 − αη 1 − αη α


Note that

4(1−αη)a α

=

4aαη(1−αη) α2 η

1 the minimum occurs either at t = s or t = a but in both cases k(t, s) s

1 − αη Φ(s) η(1 − αη)Φ(s). α

The conclusion is that we may take

c=

min a, αη, 4a(1 − η), α(1 − η) , min aη, 4a(1 − αη), η(1 − αη) ,

α < 1, α 1.

Hence we have:

T HEOREM 3.43. Let a, b ∈ (0, 1] and suppose that and m=

max

1

0t1 0

k(t, s)a(s) ds

−1

,

b a

a(t) dt > 0. Let c as defined above

M=

min

0t1 a

b

k(t, s)a(s) ds

−1

Then for 0 < αη < 1 the BVP (3.80)–(3.81) has at least one positive solution if either (h1) 0 lim sup x→0

f (x) f (x) < m and M < lim inf ∞, x→∞ x x

or (h2) 0 lim sup x→∞

f (x) f (x) < m and M < lim inf ∞, x→0 x x

and has two positive solutions if there is ρ > 0 such that either

(E1)

 f (x)   < m,  0 lim sup  x  x→0   f (x) min : x ∈ [cρ, ρ] cM, x = T x  ρ    f (x)    0 lim sup < m, x x→∞

for x ∈ ∂Ωρ ,

and

.

532

S.K. Ntouyas

or

(E2)

where

 f (x)   M < lim sup ∞,   x   x→0  f (x) max : x ∈ [0, ρ] m, x = T x  ρ    f (x)    M < lim sup ∞, x x→∞

2 Ωρ = x ∈ K: c x min x(t) < cρ , atb

for x ∈ ∂Kρ ,

and

Kr = x ∈ K: x < ρ

and K is a closed convex set in a Banach space. Theorem 3.43 is taken from Webb [92]. Similar results are given by Infante [45] who proved existence of eigenvalues of some nonlocal BVP, including nonlocal boundary conditions other than (3.81), as (a) x ′ (0) = 0, αx ′ (η) = x(1), 0 < η < 1, (b) x(0) = 0, αx ′ (η) = x(1), 0 < η < 1, (c) x ′ (0) = 0, αx(η) = x(1), 0 < η < 1. Infante and Webb [47] obtained more general results for existence of positive solutions of some m-point BVPs in the case when all the parameters occurring in the boundary conditions are not positive and the nonlinear term allow more general behaviour than being either sub- or superlinear. Two four-points BVPs are studied in details in [47]. Also interesting results were given for the following three-point BVP x ′′ + a(t)f (x) = 0,

x ′ (0) = 0,

t ∈ (0, 1),

(3.84)

αx(η) = x(1),

(3.85)

where 0 < η < 1, 0 < α < 1 by Liu in [56]. By applying Krasnosel’skii’s fixed point theorem he proved existence • of single positive solution under f0 = 0, f∞ = ∞ or f0 = ∞, f∞ = 0, • of two positive solution under f0 = f∞ = ∞ or f0 = f∞ = 0, • of positive solutions under f0 , f∞ ∈ {0, ∞}. In [56] some interesting examples were given to demonstrate the results. A more general three-point BVP was studied by Ma and Wang. In [79] they studied the existence of positive solutions of the following BVP x ′′ (t) + a(t)x ′ (t) + b(t)x(t) + h(t)f (x) = 0, x(0) = 0,

x(1) = αx(η),

t ∈ (0, 1),

(3.86) (3.87)

where f ∈ C([0, 1], [0, ∞)), h ∈ C([0, 1], [0, ∞)) and there exists x0 ∈ [0, 1] such that h(x0 ) > 0, and a ∈ C[0, 1], b ∈ C([0, 1], (−∞, 0)). Under these assumptions they proved


533

the existence of at least one positive solution of the BVP (3.86)–(3.87) either in superlinear or sublinear case, by applying the Krasnosel’skii’s fixed point theorem in cones. If in the BVP (3.80)–(3.81) the boundary condition (3.81) is nonhomogeneous, i.e. x(0) = 0,

x(1) − αx(η) = b,

(3.88)

Ma in [78], by using Schauder’s fixed point theorem, proved in the superlinear case that, if (A1) and (A2) of Theorem 3.38 hold, then there exists a positive number b∗ such that (3.80), (3.88) has at least one positive solution for b: 0 < b < b∗ and no solution for b > b∗ . This result was improved and complemented by Zhang and Wang in [95], where they studied the BVP (3.80), (3.88) under the following conditions: (H1) α ∈ (0, 1/η), η ∈ (0, 1); (H2) a(t) is a nonnegative measurable function defined on (0, 1) and 0

η 0

sa(s) ds < +∞,

0
M; (H6) limu→0+ f (u) u < δ, where δ, M are suitable defined constants, and proved that: • the BVP (3.80), (3.88) has a positive solution for all b > 0 if (H1)–(H4) hold; • there exists a positive number b∗ such that (3.80), (3.88) has at least one positive solution for b: 0 < b < b∗ and no solution for b > b∗ if (H1)–(H3), (H5) and (H6) hold; • there exists a positive number b∗ such that (3.80), (3.88) has at least two solution for b: 0 < b < b∗ , at least one for b = b∗ , none for b > b∗ if (H1), (H2), (H3∗ ), (H5) and (H6) hold. We remark that (H2) allows a(t) to be singular at t = 0 and/or t = 1, and (H5) and (H6) allow but not require the nonlinearity f (x) to be superlinear at zero and infinity. Now, we consider the following three-point nonlinear second-order BVP x ′′ (t) + λa(t)f x(t) = 0,

x(0) = 0,

t ∈ (0, 1),

(3.89)

αx(η) = x(1),

(3.90)

where 0 < η < 1. For this problem, an open interval of eigenvalues is determined, which in return, imply the existence of a positive solution of (3.89)–(3.90) by appealing to Krasnosel’skii’s fixed point theorem. For the sake of simplicity, we let A = (1 − αη)−1

0

1

(1 − η)a(s) ds,

B = η(1 − αη)−1

0

1

(1 − η)a(s) ds.

534

S.K. Ntouyas

T HEOREM 3.44. Assume that (A1) f ∈ C([0, ∞), [0, ∞)); (A2) a ∈ C([0, 1], [0, ∞)) and does not vanish identically on any subinterval. (A3) limx→0+ f (x) x = l with 0 < l < ∞. f (x) (A4) limx→∞ x = L with 0 < L < ∞. Then, for each λ satisfying either 1 1 (i) γ BL < λ < Al or 1 (ii) γ 1Bl < λ < AL the BVP (3.89)–(3.90) has at least one positive solution. P ROOF. Let λ given as in (i), and choose ǫ > 0 such that 1 1 λ . γ B(L − ǫ) A(l + ǫ) Consider also the cone K and the operator A defined in the proof of Theorem 3.38. By (A3), there exists H1 > 0 such that f (x) (l + ǫ)x, for 0 < x H1 . So, choosing x ∈ K with x = H1 , we have t Ax(t) = λ 1 − αη λ

t 1 − αη

1 λ 1 − αη λ

1 1 − αη

1 0 1

(1 − s)a(s)f x(s) ds (1 − s)a(s)(l + ǫ)x(s) ds

0 1

(1 − s)a(s)(l + ǫ) x ds

0 1 0

(1 − s)a(s)(l + ǫ)H1 ds

λA(l + ǫ) x x . Consequently, Ax x . So, if we set Ω1 = x ∈ C[0, 1]: x < H1 ,

then Ax x , for x ∈ K ∩ ∂Ω1 . Next we construct the set Ω2 . Considering (A4) there exists H 2 such that f (x) (L − ǫ)x, for x H 2 . Let H2 = max{2H1 , Hγ2 } and Ω2 = {x ∈ C[0, 1]: x < H2 }, then x ∈ K and x = H2 implies 2 , min x(t) γ x H

ηt1


535

and so η Ax(η) = λ 1 − αη λ λ

η 1 − αη η 1 − αη

γη =λ 1 − αη

1

η

1

(1 − s)a(s)(L − ǫ)x(s) ds

η

1

(1 − s)a(s)(L − ǫ)γ x ds

η

η


1

(1 − s)a(s)(L − ǫ)H2 ds

λBγ (L − ǫ) x

= x . Hence, for x ∈ K ∩ ∂Ω2 ,

Ax x . Therefore, by the first part of Theorem 3.33, it follows that A has a fixed point in K ∩ (Ω 2 \ Ω1 ), completing the proof in case (i). Consider now the case (ii). Let λ given as in (ii) and choose ǫ > 0 such that 1 1 λ . γ B(l − ǫ) A(L + ǫ) We omit the rest of the proof, since it is similar to that of Theorem 3.38.

Theorem 3.44 is taken from Raffoul [89]. He proved also that: • if (A1), (A2), (A4) hold and limx→0+ f (x) x = ∞ then the BVP (3.89)–(3.90) has at 1 ; least one positive solution for each λ satisfying 0 < λ < AL f (x) • if (A1), (A2), (A3) hold and limx→∞ x = ∞ then the BVP (3.89)–(3.90) has at 1 . least one positive solution for each λ satisfying 0 < λ < Al Other existence and multiplicities of positive solutions for the BVP (3.89)–(3.90) were proved by Ma in [70] by using fixed point index theory and the method of upper and lower solutions. He proved in [70] the following result. T HEOREM 3.45. Assume that: (A1) λ is a positive parameter; η ∈ (0, 1) and αη < 1. (A2) a : [0, 1] → [0, ∞) is continuous and does not vanish identically on any subset of positive measure. (A3) limx→∞ f (x) x = ∞.

536

S.K. Ntouyas

Then there exists a positive λ∗ such that the BVP (3.89)–(3.90) has at least two positive solutions for 0 < λ < λ∗ , at least one positive solution for λ = λ∗ , and no positive solutions for λ > λ∗ . Interesting results on the existence of multiple positive solutions for three-point BVP can be obtained by using the Leggett–Williams fixed point theorem. We will give such a result proving the existence of triple positive solutions of the following BVP x ′′ + f (t, x) = 0, x(0) = 0,

t ∈ (0, 1),

x(1) = αx(η).

(3.91) (3.92)

In this approach, we do not need the assumption that f is sublinear or superlinear, which was required in Theorem 3.38. For convenience of the reader, we present here the necessary definitions from cone theory in Banach spaces. D EFINITION 3.46. Let E be a Banach space over R. A nonempty, closed set P ⊂ E is said to be a cone provided that (a) αu + βv ∈ P for all u, v ∈ P and all α, β 0 and (b) u, −u ∈ P implies u = 0. If P ⊂ E is a cone, we denote the order induced by P on E by . For u, v ∈ P , we write u v if and only if v − u ∈ P . D EFINITION 3.47. The map ψ is said to be a nonnegative continuous concave functional on P provided ψ : P → [0, ∞) is continuous and ψ λx + (1 − λ)y λψ(x) + (1 − λ)ψ(y)

for all x, y ∈ P and λ ∈ [0, 1].

Let 0 < a < b be given and let ψ be a nonnegative continuous concave functional on the cone P . Define the convex sets Pr and P (ψ, a, b) by

and

Pr = y ∈ P : y < r P (ψ, a, b) = y ∈ P : a ψ(y), and y b .

Our consideration is based on the following fixed point theorem given by Leggett and Williams in 1979 [55] (see also Guo and Lakshmikantham [21]). T HEOREM 3.48 (Legget–Williams fixed-point theorem). Let T : P c → P c be a completely continuous operator and let ψ be a nonnegative continuous concave functional


537

on P such that ψ(y) y for y ∈ P c . Suppose that there exist 0 < a < b < d c such that (C1) {y ∈ P (ψ, b, d): ψ(y) > b} = ∅ and ψ(T y) > b for all y ∈ P (ψ, b, d); (C2) T y < a for all y a, and (C3) ψ(T y) > b for y ∈ P (ψ, b, c) with T y > d. Then T has at least three fixed points y1 , y2 , and y3 such that y1 < a, b < ψ(y2 ) and

y3 > a with ψ(y3 ) < b. T HEOREM 3.49. Assume that η ∈ (0, 1), α > 0 and αη < 1. Assume that: (A1) f : [0, 1] × [0, ∞) → [0, ∞) is continuous and f (t, ·) does not vanish identically on any subset of [0, 1] with positive measure. Suppose also that there exist constants 0 < a < b < b/γ c such that (D1) f (t, x) < ma, for 0 t 1, 0 x a, (D2) f (t, x) b/δ, for η t 1, b x b/γ , (D3) f (t, x) mc, for 0 t 1, 0 x c, where m=

2 − αη + αη2 2(1 − αη)

−1

,

αη(1 − η)2 η(1 − η)2 , , δ = min 2(1 − αη) 2(1 − αη)

and γ is defined in Lemma 3.37. Then the BVP (3.91)–(3.92) has at least three positive solutions x1 , x2 and x3 satisfying x1 < a, b < ψ(x2 ) and x3 > a with ψ(x3 ) < b. P ROOF. Let E = C[0, 1] be endowed with the maximum norm, x = max0t1 |x(t)|, and the ordering x y if x(t) y(t) for all t ∈ [0, 1]. From the fact x ′′ (t) = −f (t, x) 0, we know that x(t) is concave on [0, 1]. So, define the cone P ⊂ E by P = x ∈ E: x is concave and nonnegative valued on [0, 1] .

Finally, let the nonnegative concave functional ψ : P → [0, ∞) be defined by ψ(x) = min x(t),

x ∈ P.

ηt1

We notice that for each x ∈ P , ψ(x) x . Define an operator T : P → E by T x(t) = −

+

0

t

(t − s)f s, x(s) ds −

t 1 − αη

0

1

αt 1 − αη

(1 − s)f s, x(s) ds.

0

η

(η − s)f s, x(s) ds

We note that, if x ∈ P then T x(t) 0, 0 t 1. In view of (T x)′′ (t) = −f (t, x(t)) 0, 0 t 1, we see that T x ∈ P ; that is to say that T : P → P . Also T is completely continuous.

538

S.K. Ntouyas

We now show that all the conditions of Theorem 3.48 are satisfied. Now if x ∈ P c , then

x c and (D3) implies f (t, x(t)) mc, 0 t 1. Consequently,

T x = max − 0t1

0

t

(t − s)f s, x(s) ds −

αt 1 − αη

1

η 0


t (1 − s)f s, x(s) ds 1 − αη 0 t η αt (t − s)f s, x(s) ds + (η − s)f s, x(s) ds max 1 − αη 0 0t1 0 1 t (1 − s)f s, x(s) ds + 1 − αη 0 t η αt max (t − s) ds + (η − s) ds 1 − αη 0 0t1 0 1 t (1 − s) ds · mc + 1 − αη 0 +

2 − αη + αη2 · mc 2(1 − αη) = c.

=

Hence, T : P c → P c . In the same way, if x ∈ P c , then assumption (D1) yields f (t, x(t)) < ma, 0 t 1. As in the argument above, we can obtain that T : P a → Pa . Therefore condition (C2) of Theorem 3.48 is satisfied. To check condition (C1) of Theorem 3.48, we choose x(t) = b/γ , 0 t 1. It is easy to see that x(t) = b/γ ∈ P (ψ, b, b/γ ) and ψ(x) = ψ(b/γ ) > b, and so {x ∈ P (ψ, b, b/γ ): ψ(x) > b} = ∅. Hence, if x ∈ P (ψ, b, b/γ ), then b x(t) b/γ , η t 1. From assumption (D2), we have f (t, x(t)) b/δ, η t 1, and by the definition of ψ and the cone P , we have to distinguish two cases, (i) ψ(T x) = T x(η) and (ii) ψ(T x) = T x(1). In case (i) we have ψ(T x) = T x(η) η =− (η − s)f s, x(s) ds − 0

1

αη 1 − αη

(1 − s)f s, x(s) ds

0

η


η 1 − αη 0 η 1 1 η − (η − s)f s, x(s) ds + (1 − s)f s, x(s) ds 1 − αη 0 1 − αη 0 η η η 1 =− f s, x(s) ds + sf s, x(s) ds 1 − αη 0 1 − αη 0 +


1 1 η η + f s, x(s) ds − sf s, x(s) ds 1 − αη 0 1 − αη 0 1 η η 1 = f s, x(s) ds + sf s, x(s) ds 1 − αη η 1 − αη 0 1 η − sf s, x(s) ds 1 − αη 0 1 1 η η > f s, x(s) ds − sf s, x(s) ds 1 − αη η 1 − αη η 1 η b (1 − s) ds · 1 − αη η δ =

η(1 − η)2 b · 2(1 − αη) δ

b. In case (ii), we have

ψ(T x) = T x(1) 1 =− (1 − s)f s, x(s) ds − 0

=

=

> =

1

0

η


1 (1 − s)f s, x(s) ds 1 − αη 0 1 η αη α (1 − s)f s, x(s) ds − (η − s)f s, x(s) ds 1 − αη 0 1 − αη 0 1 1 αη αη f s, x(s) ds − sf s, x(s) ds 1 − αη 0 1 − αη 0 η η α αη f s, x(s) ds + sf s, x(s) ds − 1 − αη 0 1 − αη 0 1 1 αη αη f s, x(s) ds − sf s, x(s) ds 1 − αη η 1 − αη 0 η α sf s, x(s) ds + 1 − αη 0 1 1 αη αη f s, x(s) ds − sf s, x(s) ds 1 − αη η 1 − αη η 1 αη (1 − s)f s, x(s) ds 1 − αη η +

=

α 1 − αη

539

540

S.K. Ntouyas

αη(1 − η)2 b · 2(1 − αη) δ

δ·

b = b, δ

i.e. ψ(T x) > b,

∀x ∈ P (ψ, b, b/γ ).

This shows that condition (C1) of Theorem 3.48 is satisfied. We finally show that (C3) of Theorem 3.48 also holds. Suppose that x ∈ P (ψ, b, c) with T x > b/γ . Then we have ψ(T x) = min T x(t) γ · T x > γ · b/γ = b. ηt1

So, condition (C3) of Theorem 3.48 is satisfied. Therefore an application of Theorem 3.48 completes the proof. Theorem 3.49 was taken from [42]. For the BVP (3.91)–(3.92) Ma in [76] studied multiplicity results at resonance, i.e. when αη = 1, by developing the methods of lower and upper solutions when the lower and upper solutions are well ordered as well as opposite ordered, by the connectivity properties of the solution set of parameterized families of compact vector fields. Let us discuss some extensions of the above results. Consider the following m-point BVP x ′′ + a(t)f (x) = 0,

t ∈ (0, 1),

(3.93)

x(0) = 0,

m−2

(3.94)

x(1) =

αi x(ξi )

i=1

where m−2 αi 0 for i = 1, 2, . . . , m − 3 and αm−2 > 0, 0 < ξ1 < ξ2 < · · · < ξm−2 < 1, i=1 αi ξi < 1. By using the Krasnosel’skii’s fixed point theorem in cones Ma in [72] proved the existence of positive solution of the BVP (3.93)–(3.94) under the assumptions m−2that a ∈ C([0, 1], [0, ∞)), and there exists x0 ∈ [ξm−2 , 1] such that a(x0 ) > 0 and i=1 αi ξi < 1, either in superlinear or sublinear case. The steps of the proof are parallel to that of the proof of Theorem 3.38. A natural generalization of the boundary condition (3.94) is x(0) = 0,

b a

h(t)x(t) dt = x(1),

(3.95)

b b where [a, b] ⊂ (0, 1), h ∈ C([a, b], [0, ∞)), a th(t) dt = 1 and b a h(t) dt < 1. The existence of positive solutions for the BVP (3.80), (3.95) is studied by Ma [73] when f is either superlinear or sublinear.


541

Another result for the following m-point BVP x ′′ + a(t)f (x) = 0, x ′ (0) =

m−2

t ∈ (0, 1),

βi x ′ (ξi ),

x(1) =

i=1

(3.96) m−2

αi x(ξi )

(3.97)

i=1

m−2 where αi , βi 0 and m−2 i=1 βi < 1, was given by Ma and Castaneda in [71] i=1 αi < 1, also by using the Krasnosel’skii’s fixed point theorem in cones and either in superlinear or sublinear case. These results were generalized and improved by Liu [58] by applying topological degree methods. The result for the BVP (3.80), (3.88) was generalized by Guo et al. in [23], where they studied the following BVP (3.80), (3.98) where (3.98) stands for the boundary condition

x(0) = 0,

x(1) −

m−2 i=1

αi x(ξi ) = b,

(3.98)

where b, αi > 0 (i = 1, 2, . . . , m − 2). In this problem a(t) is allowed to be singular at t = 0, 1. The m-point BVP x ′′ + f (t, x) = 0, x(0) = 0,

t ∈ (0, 1),

x(1) =

m−2

(3.99)

αi x(ξi )

(3.100)

i=1

m−2 where αi > 0 for i = 1, 2, . . . , m − 2, 0 < ξ1 < ξ2 < · · · < ξm−2 < 1, i=1 αi ξi < 1 and f : [0, 1] × [0, ∞) → [0, ∞) a continuous function, was studied by Liu et al. in [64] by using the Legget–Williams fixed point theorem and Green’s functions. Existence and multiplicity results for positive solutions for the m-point BVP ′ p(t)x ′ − q(t)x + f (t, x) = 0,

ax(0) − bp(0)x ′ (0) = ′

cx(1) − dp(1)x (1) =

m−2

αi x(ξi ),

m−2

βi x(ξi ),

0 < t < 1,

i=1

i=1

where p, q ∈ C([0, 1], (0, ∞)), a, b, c, d ∈ [0, ∞) are given by Ma in [77]. See also [75] for results for superlinear semipositone m-point BVPs.

542

S.K. Ntouyas

Three-point BVP of higher-order ordinary differential equations was studied by Liu and Ge in [65] where they consider BVP consisting of the equation x (n) + λa(t)f x(t) = 0,

t ∈ (0, 1)

with one of the following boundary value conditions: x(0) = αx(η), (i)

x (0) = 0,

x(1) = βx(η), i = 1, 2, . . . , n − 2,

and x (n−2) (0) = αx (n−2) (η),

x (i) (0) = 0,

x (n−2) (1) = βx (n−2) (η),

i = 1, 2, . . . , n − 3,

where η ∈ (0, 1), α 0, β 0, and a : (0, 1) → R may change sign, f (0) > 0, and λ > 0 is a parameter. For other recent results on positive solutions for nonlocal BVP the interested reader is referred to [13,18,46,48,51,64,67,68] and the references cited therein.

3.10. Positive solutions of nonlocal boundary value problems with dependence on the first-order derivative All the results in the previous section were proved under the assumption that the first derivative x ′ is not involved explicitly in the nonlinear term. In this section we are concerned with the existence of positive solutions for the second-order three-point BVP x ′′ (t) + f t, x(t), x ′ (t) , x(0) = 0,

0 < t < 1,

(3.101)

x(1) = αx(η),

(3.102)

where f : [0, 1] × [0, ∞) × R → [0, ∞) is continuous, α > 0, 0 < η < 1 and 1 − αη > 0. To show the existence of positive solutions to BVP (3.101)–(3.102), we use an extension of Krasnosel’skii’s fixed point theorem in cones, proved in [19]. To state this fixed point theorem some notations are necessary. Let X be a Banach space and K ⊂ X a cone. Suppose α, β : X → R+ are two convex functionals satisfying α(λx) = |λ|α(x),

β(λx) = |λ|β(x),

λ ∈ R,

and

x M max α(x), β(x) α(x) α(y)

for x ∈ X

and

for x, y ∈ K, x y,


543

where M > 0 is a constant. T HEOREM 3.50. Let r2 > r1 > 0, L > 0 be constants and Ωi = x ∈ X: α(x) < ri , β(x) < L ,

i = 1, 2,

two bounded open sets in X. Set Di = x ∈ X: α(x) = ri . Assume T : K → K is a completely continuous operator satisfying (a) α(T u) < r1 , u ∈ D1 ∩ K; α(T u) > r2 , u ∈ D2 ∩ K; (b) β(T u) < L, u ∈ K; (c) there is a p ∈ (Ω ∩ K) \ {0} such that α(p) = 0 and α(x + λp) α(x) for all x ∈ K and λ 0. Then T has at least one fixed point in (Ω2 \ Ω 1 ) ∩ K. From Lemmas 3.34 and 3.37 we know that the unique solution of the BVP x ′′ + y(t) = 0,

0 < t < 1,

x(0) = 0,

x(1) = αx(η)

is given by

t

αt x(t) = − (t − s)y(s) ds − 1 − αη 0 1 t + (1 − s)y(s) ds 1 − αη 0

0

η

(η − s)y(s) ds

and satisfies min x(t) γ x ,

t∈[η,1]

where γ = min{αη, α(1−η) 1−αη , η}. Moreover it is easy to see that, if 1 − αη = 0, the Green function for the BVP −x ′′ = 0,

0 < t < 1,

x(0) = 0,

x(1) = αx(η)

544

S.K. Ntouyas

is given by  s[(1 − t) − α(η − t)]  ,    1 − αη     s(1 − t) + αη(t − s)   ,  1 − αη G(t, s) =  t[(1 − s) − α(η − s)]   ,   1 − αη       t (1 − s) , 1 − αη

s t, s η, η s t, t s η, t s, s η.

Let X = C 1 ([0, 1], R) with x = max0t1 [x 2 (t) + (x ′ (t))2 ]1/2 , and K = {x ∈ X: x(t) 0, x is concave on [0, 1]}. Define functionals α(x) = max0t1 |x(t)| and √ β(x) = max0t1 |x ′ (t)| for each x ∈ X. Then x 2 max{α(x), β(x)} and α(λx) = |λ|α(x),

β(λx) = |λ|β(x),

x ∈ X, λ ∈ R,

for x, y ∈ K, x y.

α(x) α(y), We set M = max

0t1 0

Q=

1

G(t, s) ds,

m = max

0t1 η

1

G(t, s) ds,

3 − αη + αη2 . 2(1 − αη)

T HEOREM 3.51. Let f : [0, 1] × [0, ∞) × R → [0, ∞) be a continuous function, α > 0, 0 < η < 1 and 1 − αη > 0. Suppose that there are L > b > γ b > c > 0 such that f (t, u, v) satisfies the growth conditions: (1) f (t, u, v) < c/M for (t, u, v) ∈ [0, 1] × [0, c] × [−L, L]; (2) f (t, u, v) b/m for (t, u, v) ∈ [0, 1] × [γ b, b] × [−L, L]; (3) f (t, u, v) < L/Q for (t, u, v) ∈ [0, 1] × [0, b] × [−L, L]. Then the BVP (3.101)–(3.102) has at least one positive solution y(t) satisfying ′ y (t) < L. c < α(x) < b, P ROOF. Take

Ω1 = x ∈ X: Ω2 = x ∈ X:

x(t) < c, x ′ (t) < L , x(t) < b, x ′ (t) < L

two bounded open sets in X, and D1 = x ∈ X: α(x) = c ,

D2 = x ∈ X: α(x) = b .


545

Let ∗

f (t, u, v) =

f (t, u, v), f (t, b, v),

(t, u, v) ∈ [0, 1] × [0, b] × (−∞, ∞), (t, u, v) ∈ [0, 1] × (b, ∞) × (−∞, ∞),

and

f1 (t, u, v) =

f ∗ (t, u, v), (t, u, v) ∈ [0, 1] × [0, ∞) × [−L, L], f ∗ (t, u, −L), (t, u, v) ∈ [0, 1] × [0, ∞) × (−∞, −L], f ∗ (t, u, L), (t, u, v) ∈ [0, 1] × [0, ∞) × [L, ∞).

Then f1 ∈ C([0, 1] × [0, ∞) × R, R+ ). Define (T x)(t) =

1 0

G(t, s)f1 s, x(s), x ′ (s) ds.

Obviously, T : K → K is completely continuous, and there is a p ∈ (Ω2 ∩ K) \ {0} such that α(x + λp) α(x) for all x ∈ K and λ 0. For x ∈ D1 ∩ K, α(x) = c. From (1), we get α(T x) = max t∈[0,1] < max

G(t, s)f1 s, x(s), x ′ (s) ds

1 0

1

G(t, s)

t∈[0,1] 0

c c ds = max M M t∈[0,1]

1

0

G(t, s) ds = c.

Whereas for x ∈ D2 ∩ K, α(x) = b. We have x(t) γ α(x) = γ b for t ∈ [η, 1]. So, from (2), we get 1 ′ G(t, s)f1 s, x(s), x (s) ds α(T x) = max t∈[0,1] 0 1 ′ > max G(t, s)f1 s, x(s), x (s) ds t∈[0,1]

> max

η

t∈[0,1] η

1

G(t, s)

b b ds = max m m t∈[0,1]

1

η

G(t, s) ds = b.

For x ∈ K, from (3), we get t β(T x) = max − f1 s, x(s), x ′ (s) ds t∈[0,1]

+

0

1 1 − αη

α − 1 − αη

1

0

0

η

(1 − s)f1 s, x(s), x ′ (s) ds

′ (η − s)f1 s, x(s), x (s) ds

546

S.K. Ntouyas

1 < 1+ 1 − αη =

0

3 − αη + αη2

1

α (1 − s) ds + 1 − αη

0

η

(η − s) ds

L Q

L = L. 2(1 − αη) Q

Theorem 3.50 implies there is y ∈ (Ω2 \ Ω 1 ) ∩ K such that y = T y. So, y is a positive solution for BVP (3.101)–(3.102) satisfying ′ y (t) < L.

c < α(x) < b,

Thus, the proof of the theorem is complete.

Theorem 3.51 was proved in [19], where one more result was proved in the case when 0 < α 1 and η ∈ (0, 1), under the assumptions (1), (2) and the following one (4) f (t, u, v) < L2 /(2b) for (t, u, v) ∈ [0, 1] × [0, b] × [−L, L]. Consider now a three-point BVP ′ p(t)x ′ (t) = f t, x(t), x ′ (t) , x ′ (0) = 0,

t ∈ [0, 1],

x(1) = x(η)

(3.103) (3.104)

where f : [0, 1] × R × R → R is continuous, p : [0, 1] → R is a positive continuous differentiable function, mint∈[0,1] p(t) := p1 > 0 and η ∈ (0, 1). For this problem the linear operator Lx(t) = (p(t)x ′ (t))′ is not invertible, so the three-point BVP (3.103)–(3.104) is a resonance problem. By using a theorem of a fixed point index for A-proper semilinear operators Bai and Fang [6] proved the following theorem. T HEOREM 3.52. Suppose (1) f : [0, 1] × R × R → R is continuous and there exist constants a > 0, b > 0, and 0 < c < p12 /(2 p ∞ ) such that f (t, x, y) a + b|x| + c|y|,

∀t ∈ [0, 1], x, y ∈ R.

(2) There exists M > 0 such that f (t, x, 0) > 0,

∀t ∈ [0, 1], x > M.

(3) f (t, x, y) 0, ∀t ∈ [0, 1], y ∈ R and there exist constants 0 < σ < b and ε > 0 such that f (t, x, y) σ x,

∀t ∈ [0, 1], 0 x ε, y ∈ R.

Then the BVP (3.103)–(3.104) has at least one positive solution.


547

A more general nonlocal BVP was studied by Palamides [87]. He consider the following BVP x ′′ (t) = f t, x(t), x ′ (t) , αx(0) − βx ′ (0) = 0,

t ∈ (0, 1), x(1) =

m−2

αi x(ξi )

i=0

with α 0, β > 0. Existence of positive solution is given, under superlinear and/or sublinear growth rate in f . A different method is employed based on analysis of the corresponding vector field on the (x, x ′ )-face plane and Kneser’s property of the solutions funnel. Finally positive solutions for 2nth order nonlocal BVP was studied by Guo et al. in [22] and [20] where they consider BVPs consisting of the equation x (2n) (t) = f t, x(t), x ′′ (t), . . . , x 2(n−1) (t) ,

0 t 1,

and one of the following boundary conditions: x (2i) (0) = 0,

x (2i) (1) =

m−2

kij x (2i) (ξj ),

j =1

0 i n − 1,

and x (2i) (0) − βi x (2i+1) (0) = 0,

x (2i) (1) =

m−2

kij x (2i) (ξj ),

j =1

0 i n − 1.

They use the Legget–Williams fixed point theorem and a fixed point theorem in double cones respectively. For other recent results we refer to [49,50,52,53].

3.11. Positive solutions of nonlocal problems for p-Laplacian The purpose of this section is to establish the existence of positive solutions to the following three-point boundary value problem for p-Laplacian ′ ′ g(u ) + a(t)f (u) = 0,

u(0) = 0,

for 0 < t < 1,

and u(ν) = u(1),

(3.105) (3.106)

where g(v) = |v|p−2 v, with p > 1, and ν ∈ (0, 1). We will prove the existence of at least three positive pseudo-symmetric solutions of the BVP (3.105)–(3.106) where we now define what we mean by a pseudo-symmetric function.

548

S.K. Ntouyas

D EFINITION 3.53. For ν ∈ (0, 1) a function u ∈ C[0, 1] is said to be pseudo-symmetric if u is symmetric over the interval [ν, 1]. That is, for t ∈ [ν, 1] we have u(t) = u(1 − (t − ν)). In this setting we are able to verify that for all x in our cone σu = 1+ν 2 . In our approach we will use a new multiple fixed point theorem, now called the five functionals fixed point theorem, obtained by Avery [2], which generalized the Leggett– Williams fixed point theorem [55] in terms of functionals rather than norms. We state first the five functional fixed point theorem. Let γ , β, θ be nonnegative, continuous, convex functionals on P and α, ψ be nonnegative, continuous, concave functionals on P . Then, for nonnegative real numbers h, a, b, d and c, we define the convex sets,

and

P (γ , c) = x ∈ P : P (γ , α, a, c) = x ∈ P : Q(γ , β, d, c) = x ∈ P : P (γ , θ, α, a, b, c) = x ∈ P :

γ (x) < c ,

a α(x), γ (x) c , β(x) d, γ (x) c ,

a α(x), θ(x) b, γ (x) c ,

Q(γ , β, ψ, h, d, c) = x ∈ P : h ψ(x), β(x) d, γ (x) c .

T HEOREM 3.54. Let P be a cone in a real Banach space E. Suppose there exist positive numbers c and M, nonnegative, continuous, concave functionals α and ψ on P , and nonnegative, continuous, convex functionals γ , β, and θ on P , with α(x) β(x)

and x Mγ (x)

for all x ∈ P (γ , c). Suppose A : P (γ , c) → P (γ , c) is completely continuous and there exist nonnegative numbers h, a, k, b, with 0 < a < b such that: (i) {x ∈ P (γ , θ, α, b, k, c): α(x) > b} = ∅ and α(Ax) > b for x ∈ P (γ , θ, α, b, k, c); (ii) {x ∈ Q(γ , β, ψ, h, a, c): β(x) < a} = ∅ and β(Ax) < a for x ∈ Q(γ , β, ψ, h, a, c); (iii) α(Ax) > b for x ∈ P (γ , α, b, c) with θ (Ax) > k; (iv) β(Ax) < a for x ∈ Q(γ , β, a, c) with ψ(Ax) < h. Then A has at least three fixed points x1 , x2 , x3 ∈ P (γ , c) such that, β(x1 ) < a,

b < α(x2 ),

and a < β(x3 )

with α(x3 ) < b.


549

Assume f : [0, ∞) → [0, ∞) is continuous, and let a : [0, 1] → [0, ∞) be continuous. Let ν ∈ (0, 1), and let E = C[0, 1] be the Banach space with the sup-norm, u = sup{|u(x)|: 0 x 1}, and define the cone P ⊂ E by P = u ∈ E: u(0) = 0, u is concave, and u is symmetric on [ν, 1] .

ν Hereafter, suppose ν ∈ (0, 1), with 0 a(r) dr > 0, and we will choose a δ ∈ (0, ν), such ν that δ a(t) dt > 0, and the constants M ∗ and m∗ , defined by

∗

M =

ν

0

G

σ

a(r) dr ds,

s

and ∗

m =

δ

0

G

a(r) dr ds,

s m∗ M∗ .

satisfy the inequality ν < m=

M=

σ

G

δ

ν

δ

0

Trivially, we have δ <

a(r) dr ds = δG

δ

m∗ M∗ .

ν

a(r) dr

We let

and σ

0

G

σ s

a(r) dr ds,

as well as, h1 =

ν

δ

h2 =

h3 =

δ

0

G

G

σ

a(r) dr ds,

s

δ

a(r) dr ds,

s

and

0

δ

G

σ

a(r) dr ds.

δ

Define the nonnegative, continuous, concave functionals α, ψ , and the nonnegative, continuous, convex functionals β, θ , γ on the cone P by: γ (x) = θ (x) := max x(t) = x(σ ), t∈[0,1]

β(x) := max x(t) = x(ν), t∈[δ,ν]

550

S.K. Ntouyas

α(x) = ψ(x) := min x(t) = x(ν). t∈[δ,ν]

In our main result, we will make use of the following lemma. The lemma is easily proved using the concavity and the pseudo-symmetry of all u ∈ P . L EMMA 3.55. Let x ∈ P . Then (D1) u(δ) δu(1) = δu(ν), and (D2) σ u(ν) νu(σ ) = ν u . We are now ready to apply the five functionals fixed point theorem to an operator A to give sufficient conditions for the existence of at least three positive pseudo-symmetric solutions to (3.105)–(3.106). T HEOREM 3.56. Assume that ν ∈ (0, 1), a : [0, 1] → [0, ∞) is a pseudo-symmetric continuous function, δ ∈ (0, ν) such that

ν

a(t) dt > 0 with ν
g( mb ) for all b x bδ , Ma−ch2 (ii) f (x) < g( M(h ) for all aδ x aσ ν , and 1 +h3 ) c (iii) f (x) g( M ) for all 0 x c. Then the three-point boundary value problem (3.105)–(3.106) has at least three positive pseudo-symmetric solutions u1 , u2 , u3 such that max u1 (t) < a < max u2 (t)

t∈[δ,ν]

t∈[δ,ν]

and

min u2 (t) < b < min u3 (t).

t∈[δ,ν]

t∈[δ,ν]

P ROOF. Define the completely continuous operator A on P by  t σ   G a(r)f u(r) dr ds,  0 s 1 s Au(t) = w(t) =    w(ν) + G a(r)f u(r) dr ds, t

where

σ=

0 t σ, σ t 1,

σ

ν +1 . 2

We first note that for u ∈ P we have Au(t) 0, Au(0) = 0, and applying the Fundamental Theorem of Calculus we have that Au is concave. Furthermore, for t ∈ [ν, 1] Au(t) = Au 1 − (t − ν) .


551

Consequently, Au ∈ P , that is, A : P → P . Moreover, since ′ g (Au)′ (t) = −a(t)f u(t) 0 for all 0 < t < 1,

we have that all fixed points of A are solutions of (3.105)–(3.106). Thus we set out to verify that the operator A satisfies the five functionals fixed point theorem which will prove the existence of three fixed points of A which satisfy the conclusion of the theorem. If u ∈ P (γ , c), then γ (u) = maxt∈[0,1] u(t) c. Thus γ (Au) = Au(σ ) σ = G =

0

s

σ

0

σ

G

c M

= c.

s σ

0

σ

a(r)f u(r) dr ds a(r)g

G

σ

c M

dr ds

a(r) dr ds

s

Hence, A : P (γ , c) → P (γ , c). Next, let N =

and

m∗ +δM ∗ . 2

Thus m∗ > N > δM ∗ , and if we define

 t σ b   G a(r) dr ds,  N 0 s uP (t) = 1 s  b   uP (ν) + G a(r) dr ds, N t σ

 t σ aδ   G a(r) dr ds,  N 0 s uQ (t) = 1 s  aδ   uQ (ν) + G a(r) dr ds, N t σ

then, clearly uP , uQ ∈ P . Furthermore, α(uP ) = uP (δ) =

b N

θ (uP ) = uP (ν) =

b N

δ

0

G

σ s

0 t σ, σ t 1,

0 t σ, σ t 1,

bm∗ a(r) dr ds = > b, N

and

0

ν

G

s

σ

a(r) dr ds =

bM ∗ b < , N δ

552

S.K. Ntouyas

as well as, ψ(uQ ) = uQ (δ) =

aδ N

β(uQ ) = uQ (ν) =

aδ N

δ

0

G

σ

s

aδm∗ a(r) dr ds = > aδ, N

and ν

0

G

σ s

a(r) dr ds =

aM ∗ δ < a. N

Therefore, b uP ∈ u ∈ P γ , θ, α, b, , c : α(u) > b , δ and uQ ∈ u ∈ Q(γ , β, ψ, aδ, a, c): β(u) < a ,

hence, these sets are nonempty. If u ∈ P (γ , θ, α, b, bδ , c), then b u(t) bδ , for all t ∈ [δ, ν], and thus by condition (i) of this theorem, α(Au) = Au(δ) δ = G 0

δ

0

G

σ s ν δ

a(r)f u(r) dr ds

a(r)f u(r) dr ds

b dr ds m 0 δ δ ν b = G a(r) dr ds m 0 δ

>

δ

G

ν

a(r)g

= b.

Hence, condition (i) of the five functionals fixed point theorem is satisfied. If u ∈ P (γ , α, b, c) with θ(Au) > bδ , then by Lemma 3.55(D1), we have α(Au) = Au(δ) δAu(1) = δAu(ν) = δθ(Au) > b. Thus, condition (iii) of the five functionals fixed point theorem is satisfied.


553

If u ∈ Q(γ , β, ψ, aδ, a, c), then aδ u(t) a, for all t ∈ [δ, ν], and thus by Lemma 3.55(D2), aδ u(t) aσ ν , for all t ∈ [δ, σ ]. Thus by condition (ii) of this theorem, β(Au) = Au(ν) ν = G 0

=

0

0

+

δ G

σ

s σ

s

δ G

δ

s

ν

δ

a(r)f u(r) dr ds

a(r)f u(r) dr ds +

δ

a(r)f u(r) dr ds +

G

s

σ

ν

a(r)f u(r) dr ds

0

G

δ G

σ s

δ

σ

a(r)f u(r) dr ds

a(r)f u(r) dr ds

δ c G a(r) dr ds < M 0 s δ σ Ma − ch2 + G a(r) dr ds M(h1 + h3 ) 0 δ ν σ Ma − ch2 + G a(r) dr ds M(h1 + h3 ) δ s

δ

ch2 (Ma − ch2 )h3 (Ma − ch2 )h1 + + M M(h1 + h3 ) M(h1 + h3 ) = a. =

Hence, condition (ii) of the five functionals fixed point theorem is satisfied. If u ∈ Q(γ , β, a, c), with ψ(Au) < aδ, then by Lemma 3.55, we have β(Au) = Au(ν)

Au(δ) ψ(Au) = < a. δ δ

Consequently, condition (iv) of the five functionals fixed point theorem is also satisfied. Therefore, the hypotheses of the five functionals fixed point theorem 3.54 are satisfied, and there exist at least three positive pseudo-symmetric solutions u1 , u2 , u3 ∈ P (γ , c) for the three-point boundary value problem (3.105)–(3.106) such that, β(u1 ) < a < β(u2 )

and α(u2 ) < b < α(u3 ).

Theorem 3.56 was taken from [3]. Existence of positive solutions for the BVP (3.105)– (3.106) was proved also in [91] and [41], relying on Krasnosel’skii’s and Legget–Williams fixed point theorems respectively. BVP with p-Laplacian and more general boundary conditions was studied in [66], where the boundary conditions u(0) − B0 (u′ (η)) = 0, u′ (1) = 0

554

S.K. Ntouyas

′ and u′ (0) = 0, u(1) + B1 (u = 0 are used and in [4,5] where the m-point boundary (η)) m−2 m−2 con′ (0) = ′ (ξ ), u(1) = ditions u(0) = 0, u(1) = m−2 a u(ξ ) and u b u i i i=1 i i=1 i i=1 ai u(ξi ) are used. Finally multi-point BVP for p-Laplacian at resonance was proved by Ni and Ge in [85] and Garcia-Huidobro et al. in [17].

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Author Index Roman numbers refer to pages on which the author (or his/her work) is mentioned. Italic numbers refer to reference pages. Numbers between brackets are the reference numbers. No distinction is made between first and co-author(s).

Abbondandolo, A. 80, 106, 121, 142 [1] Adams, R.A. 98, 126, 129, 142 [2] Aftabizadeh, A. 489, 554 [1] Agrachev, A.A. 3, 16, 18, 57, 67, 74 [1]; 74 [2] Ahmad, S. 439, 459 [1]; 459 [2] Albrecht, F. 297, 348 [1] Alexandroff, A. 315, 348 [2] Alikakos, N. 314, 321, 332, 348 [3] Alvárez, C. 439, 459 [3] Amann, H. 104, 106, 121, 142 [3]; 142 [4]; 275, 314, 315, 320, 332, 338, 340, 345, 348 [4]; 349 [5]; 349 [6]; 349 [7]; 349 [8]; 349 [9]; 349 [10]; 349 [11]; 398, 459 [4] Ambrosetti, A. 80, 142 [5] Amine, Z. 458, 459 [5] Angenent, S. 349 [12]; 349 [27] Arioli, G. 90, 129, 138, 142 [6] Arnold, V.I. 5, 6, 8, 19, 27, 74 [3] Aubin, J.P. 154, 188, 228, 229, 233, 234, 235 [1]; 235 [2]; 235 [3]; 235 [4] Avery, R. 548, 553, 554 [2]; 554 [3]

Berestycki, H. 91, 115, 121, 142 [7]; 142 [8]; 143 [20] Berliocchi, H. 190, 235 [10] Berman, A. 282, 284, 286–289, 349 [18]; 349 [19] Birkhoff, G. 315, 349 [20] Bitsadze, A. 470, 554 [7]; 554 [8] Bliss, G.A. 4, 74 [8] Bolotin, S.V. 139, 143 [21] Boltyanskii, V.G. 29, 75 [30]; 223, 235 [11]; 235 [12]; 237 [83] Bony, J.M. 153, 235 [13] Bothe, D. 233, 234, 235 [14]; 235 [15] Boucherif, A. 482, 484, 554 [9] Bouguima, S. 482, 484, 554 [9] Bouligand, H. 159, 160, 235 [16] Bressan, A. 233, 235 [17] Brezis, H. 11, 13, 74 [9]; 153, 154, 156, 157, 235 [18]; 235 [19] Browder, F. 156, 157, 235 [19] Brunovsky, P. 296, 314, 349 [21]; 349 [22] Byszewski, L. 465, 469, 554 [10]; 554 [11]; 554 [12]

Bahri, A. 91, 142 [7]; 142 [8] Bai, C. 546, 554, 554 [4]; 554 [5]; 554 [6] Barbu, V. 3, 11, 38, 47, 67, 70, 74 [4]; 74 [5]; 74 [6]; 230, 235 [5] Bartsch, T. 88–90, 97, 107, 125, 142 [9]; 142 [10]; 142 [11]; 143 [12]; 143 [13]; 143 [14]; 143 [15]; 143 [16] Batty, C. 349 [13] Bebernes, W. 227, 235 [6] Bellman, R. 3, 74 [7]; 223, 235 [7]; 235 [8]; 235 [9] Benaïm, M. 296, 302, 349 [14]; 349 [15]; 349 [16]; 349 [17] Benci, V. 80, 88, 97, 106, 121, 143 [17]; 143 [18]; 143 [19]

Calvert, B. 542, 554 [13] Carathéodory, C. 223, 235 [29] Cârj˘a, O. 154, 158, 176, 178, 190, 203, 210, 213, 225, 227, 228, 231, 233, 234, 235 [20]; 235 [21]; 235 [22]; 235 [23]; 235 [24]; 235 [25]; 235 [26]; 235 [27]; 235 [28] Castaneda, N. 533, 557 [78] Cellina, A. 154, 188, 228, 229, 233, 234, 235 [3] Cerami, G. 96, 143 [22] Cesari, L. 223, 236 [30] Chang, K.C. 81, 82, 106, 110, 121, 124, 143 [23] Chen, M. 314, 349 [24] Chen, X. 314, 349 [24] Chen, X.-Y. 314, 349 [23] 559

560

Author Index

Chi¸s-Ster, ¸ I. 232, 236 [31] Cholewa, J. 332, 345, 349 [25] Chow, S.N. 331, 349 [26] Clarke, F.H. 3, 14, 15, 32, 50, 73, 74 [10]; 74 [11]; 74 [12]; 74 [13]; 74 [14]; 163, 175, 223, 226, 236 [32]; 236 [33]; 236 [34]; 236 [35] Clements, Ph. 349 [27] Coddington, E.A. 16, 74 [15]; 349 [28] Cohen, D.S. 314, 352 [95] Colombo, F. 340, 349 [29] Conley, C. 124, 143 [24]; 293, 349 [30]; 349 [31] Coppel, W. 349 [32] Cornet, B. 166, 236 [36] Cosner, C. 345, 349 [33] Coti Zelati, V. 80, 126, 135, 136, 138–140, 142 [5]; 143 [25]; 143 [26] Courant, R. 7, 8, 74 [16]; 223, 236 [37]; 314, 349 [34] Crandall, M.G. 68, 70, 74 [17]; 75 [18]; 75 [19]; 75 [20]; 151, 152, 154, 233, 236 [38]; 236 [39]; 371, 404, 407, 459 [6] Cushing, J.M. 392, 439, 459 [7]

Fang, J. 546, 554, 554 [4]; 554 [5]; 554 [6] Federer, H. 161, 236 [41] Feferman, S. 156, 236 [42] Felmer, P. 118, 124, 143 [37]; 143 [38]; 144 [39] Feng, W. 497, 505, 554 [15]; 554 [16] Fife, P. 350 [49]; 350 [50] Filippov, A.F. 213, 236 [43] Fleckinger-Pellé, J. 327, 350 [45]; 350 [46] Fleming, W.H. 3, 73, 75 [22] Foias, C. 350 [43] Fomin, S.V. 4, 8, 75 [24] Fonda, A. 124, 144 [40] Fournier, G. 92, 94, 124, 144 [42] Frankowska, H. 190, 228, 234, 235 [4]; 236 [44]; 236 [45] Freedman, H.I. 320, 313, 356 [235]; 357 [236] Friedman, A. 350 [47]; 350 [48] Frobenius, G. 315, 350 [51] Fryszkowski, A. 233, 236 [46] Fukaya, K. 125, 144 [41] Fukuhara, M. 219, 220, 236 [47] Furter, J.E. 384, 459 [13]

Da Prato, G. 70, 74 [5] Dafermos, C.M. 327, 350 [35] Dancer, E.N. 316, 318, 320–322, 332, 350 [36]; 350 [37]; 350 [38]; 392, 397, 458, 459 [8]; 459 [9]; 459 [10] Dancer, N. 107, 109, 143 [27] de Leenheer, P. 302, 350 [41] de Mottoni, P. 314, 329–331, 350 [42]; 438, 454, 460 [29] de Pagter, B. 349 [27] DeAngelis, D.L. 242, 350 [39] Degiovanni, M. 121, 143 [28] Deimling, K. 350 [40] Delgado, M. 438, 459 [11] Ding, Y.H. 97, 129, 132, 135, 136, 138, 140, 143 [12]; 143 [13]; 143 [29]; 143 [30]; 143 [31] Dlotko, T. 332, 345, 349 [25] Dugundji, J. 482, 483, 554 [14] Dunford, N. 201, 234, 236 [40]

Gamkrelidze, R.V. 16, 29, 74 [1]; 75 [23]; 75 [30]; 223, 237 [83] Gao, Y. 547, 554 [20] Garcia-Huidobro, M. 554, 554 [17] Gatzke, H. 297, 348 [1] Gautier, S. 228, 236 [48] Ge, W. 540–542, 546, 547, 553, 554, 554 [19]; 554 [20]; 555 [23]; 555 [41]; 555 [42]; 556 [65]; 556 [66]; 557 [85] Gelfand, I.M. 4, 8, 75 [24] Ginzburg, V.L. 110, 113, 144 [43]; 144 [44]; 144 [45] Girardi, M. 115, 136, 138, 143 [30]; 144 [46] Girsanov, I.V. 161, 236 [49] Glas, D. 254, 350 [55] Gonzales, R. 223, 236 [50] Goursat, E. 223, 236 [51] Graef, J. 542, 554 [18] Granas, A. 482, 483, 554 [14] Greiner, G. 350 [52] Grossberg, S. 297, 350 [53]; 350 [54] Guckenheimer, J. 80, 138, 142, 144 [47] Guo, D. 519, 525, 536, 554 [21] Guo, Y.X. 121, 144 [48]; 541, 542, 546, 547, 554 [19]; 554 [20]; 554 [22]; 555 [23]; 556 [64] Gupta, C.P. 481, 489, 494, 495, 497, 505, 513, 516, 542, 554, 554 [1]; 554 [13]; 554 [17]; 555 [24]; 555 [25]; 555 [26]; 555 [27]; 555 [28]; 555 [29]; 555 [30]; 555 [31]; 555 [32]; 555 [33]; 555 [34]; 555 [35]; 555 [36]; 555 [37]; 555 [38]; 555 [39]; 555 [40]

Eden, A. 350 [43] Eilbeck, J.C. 363, 384, 439, 452, 459 [12]; 459 [13] Ekeland, I. 15, 50, 74 [13]; 75 [21]; 80, 115, 118, 126, 135, 139, 140, 143 [25]; 143 [32]; 143 [33]; 143 [34]; 143 [35] Elsner, L. 286, 350 [44] Evans, L.C. 68, 70, 74 [17] Fadell, E.R. 88, 109, 121, 143 [36]

Author Index Gürel, B.Z. 113, 144 [44] Haddad, A. 297, 348 [1] Haddad, G. 227, 236 [52] Hadeler, K. 254, 350 [55] Hájek, O. 223, 236 [53] Hale, J.K. 301–303, 305, 307, 309, 313, 314, 329, 331, 332, 344, 349 [24]; 349 [26]; 350 [56]; 350 [57]; 350 [58]; 350 [59]; 350 [60]; 350 [61]; 439, 459 [14] Hall, G.R. 80, 145 [75] Han, Y. 482, 557 [93] Hartman, P. 151, 152, 220, 236 [54]; 236 [55] He, X. 540, 553, 555 [41]; 555 [42] Heijmans, H. 349 [27] Henderson, J. 553, 554 [3] Henry, D. 332–334, 350 [62] Herman, M. 113, 144 [49] Hess, P. 314, 316, 318, 320, 321, 329, 332, 348 [3]; 350 [38]; 350 [63]; 350 [64]; 350 [65]; 439, 459 [15] Hilbert, D. 7, 8, 74 [16]; 223, 236 [37]; 314, 349 [34] Hirsch, M.W. 242, 247, 249, 250, 254–256, 258, 264, 265, 269, 271, 272, 275, 281, 291, 292, 296, 297, 299, 300, 302, 317, 319, 349 [16]; 349 [17]; 351 [66]; 351 [67]; 351 [68]; 351 [69]; 351 [70]; 351 [71]; 351 [72]; 351 [73]; 351 [74]; 351 [75]; 351 [76]; 351 [77]; 351 [78]; 351 [79]; 351 [80] Hobson, E.W. 175, 236 [56] Hofbauer, J. 301, 302, 351 [81]; 351 [82] Hofer, H. 80, 113, 115, 125, 144 [50]; 144 [51]; 144 [52] Holmes, P. 80, 138, 142, 144 [47] Hopf, H. 315, 348 [2] Howard, P. 156, 236 [57] Hsu, S.-B. 302, 320, 332, 351 [83]; 351 [84] Il’in, V. 470, 555 [43]; 555 [44] Infante, G. 532, 542, 555 [45]; 555 [46]; 555 [47] Ishii, H. 70, 75 [18]; 75 [19]; 223, 236 [58] Isidori, A. 3, 75 [25] Izydorek, M. 121, 124, 144 [53]; 144 [54] Jeanjean, L. 133, 144 [55] Jentzsch, R. 315, 351 [85] Jiang, J. 265, 296, 314, 319, 332, 351 [86]; 351 [87]; 351 [88]; 351 [89]; 351 [90]; 352 [120]; 352 [121]; 356 [229]; 356 [230]; 356 [231] Jurdjevic, V. 3, 67, 75 [26]

561

Kamke, E. 223, 237 [59]; 241, 285, 351 [91] Karakostas, G.L. 542, 547, 556 [48]; 556 [49]; 556 [50]; 556 [51]; 556 [52]; 556 [53] Kato, T. 274, 275, 351 [92] Keller, H.B. 314, 351 [93]; 352 [94]; 352 [95] Kenmochi, N. 181, 237 [60] Kerman, E. 110, 144 [45] Kerscher, W. 352 [96] Kneser, H. 219, 221, 237 [61] Kobayashi, J. 213, 237 [62] Kolmogorov, A. 297, 352 [97] Krasnosel’skii, M.A. 88, 144 [56]; 314, 323, 324, 352 [98]; 352 [99]; 352 [100]; 352 [101]; 363, 411, 459 [16]; 519, 556 [54] Krause, U. 315, 323, 324, 327, 352 [102]; 352 [103] Krein, M.G. 274, 315, 352 [104] Krisztin, T. 303, 313, 352 [105]; 352 [106]; 352 [107]; 352 [108] Kryszewski, W. 95, 106, 121, 136, 144 [57]; 144 [58] Kucia, A. 190, 237 [63] Kunisch, K. 305, 352 [109] Kunze, H. 289, 352 [110]; 352 [111]; 352 [112] Kuznetsov, Y.A. 328, 352 [113] Ladyzhenskaya, L. 314, 352 [100]; 352 [114] Lakshmikantham, V. 465, 489, 519, 525, 536, 554 [12]; 554 [21]; 555 [31] LaSalle, J.P. 316, 352 [116] Lasry, J.M. 115, 121, 143 [20]; 143 [35]; 190, 235 [10] Lassoued, L. 115, 143 [34] Lazer, A.C. 332, 350 [64]; 439, 459 [2]; 459 [3]; 459 [15] Ledyaev, Yu.S. 175, 226, 228, 236 [33]; 236 [34]; 237 [64] Legget, R. 536, 548, 556 [55] Lemmens, B. 315, 352 [117] Lemmert, R. 284, 352 [118] Leung, A.W. 352 [119] Levinson, N. 16, 74 [15]; 349 [28] Li, G. 96, 144 [59] Li, M. 301, 352 [115] Li, S.J. 83, 86, 91, 106, 118, 121, 144 [60]; 144 [61]; 144 [62] Li, W. 301, 357 [237] Li, Y. 54, 75 [36] Li, Y.Q. 92, 144 [63] Liang, X. 314, 332, 352 [120]; 352 [121] Lieb, E.H. 129, 144 [64] Lions, J.-L. 3, 75 [27] Lions, P.-L. 68, 70, 74 [17]; 75 [18]; 75 [19]; 75 [20]; 95, 129, 144 [65]; 233, 236 [39]

562

Author Index

Liu, B. 516, 517, 525, 529, 532, 541, 556 [56]; 556 [57]; 556 [58]; 556 [59]; 556 [60]; 556 [61]; 556 [62] Liu, C.G. 115, 144 [67] Liu, J.Q. 83, 91, 106, 121, 124, 144 [60]; 144 [61]; 144 [66] Liu, X. 541, 542, 547, 554 [22]; 556 [63]; 556 [64] Liu, Y. 542, 553, 556 [65]; 556 [66] Loewy, R. 353 [122] Long, Y. 80, 106, 115, 118, 121, 144 [67]; 145 [68]; 145 [69]; 145 [70]; 145 [71] López-Gómez, J. 363, 384, 390, 392, 394–397, 404, 411, 438, 439, 452, 458, 459 [10]; 459 [11]; 459 [12]; 459 [13]; 459 [17]; 459 [18]; 459 [19]; 459 [20]; 459 [21]; 459 [22]; 459 [23]; 459 [24]; 459 [25]; 459 [26] Loss, M. 129, 144 [64] Lui, R. 315, 353 [123] Lunardi, A. 332, 334, 339–342, 345, 353 [124] Lupo, D. 92, 94, 124, 144 [42] Lupulescu, V. 154, 237 [65] Lyapunov, A.M. 106, 145 [72] Ma, R. 475, 525, 532, 533, 535, 540–542, 556 [67]; 556 [68]; 556 [69]; 556 [70]; 556 [71]; 556 [72]; 556 [73]; 556 [74]; 557 [75]; 557 [76]; 557 [77]; 557 [78]; 557 [79] Manasevich, R. 554, 554 [17] Mancini, G. 115, 121, 143 [20] Marano, S. 481, 489, 557 [80]; 557 [81] Marsden, J.E. 6, 19, 75 [28] Martin, R.H. 305, 332, 335–338, 343, 353 [125]; 353 [126]; 353 [127]; 353 [128]; 353 [129]; 353 [130] Martin, R.H., Jr. 153, 154, 237 [66] Matano, H. 247, 314, 320, 321, 332, 348 [3]; 349 [23]; 353 [131]; 353 [132]; 353 [133]; 353 [134]; 353 [135] Matzeu, M. 115, 144 [46] Mawhin, J. 80, 89, 124, 144 [40]; 145 [73]; 363, 459 [27]; 460 [28]; 474, 476, 477, 486, 490, 491, 498, 557 [82] May, R. 315, 353 [136] McDuff, D. 80, 145 [74] McShane, E.J. 293, 353 [137] Meyer, K.R. 80, 145 [75] Michael, E. 212, 229, 237 [67]; 237 [68] Mierczyński, J. 265, 280, 296, 327, 328, 353 [138]; 353 [139]; 353 [140]; 353 [141]; 353 [142]; 353 [143] Miller, R.K. 320, 357 [236] Mincheva, M. 345, 353 [144]; 353 [145] Mischaikow, K. 353 [146]

Mishchenko, E.F. 29, 75 [30]; 223, 237 [83] Moiseev, E. 470, 555 [43]; 555 [44] Molina-Meyer, M. 363, 390, 459 [21]; 459 [22]; 459 [23]; 459 [24] Monteiro Marques, M.D.P. 190, 227, 228, 231, 235 [21]; 235 [22]; 235 [23] Mora, X. 332, 340, 353 [147] Mordukhovich, B.S. 153, 237 [69] Moreau, J. 13, 75 [29] Moser, J. 106, 107, 145 [76] Moshinsky, M. 470, 557 [83] Muldowney, J. 301, 352 [115] Müller, M. 241, 285, 353 [148] Murty, K. 475, 557 [84] Nagel, R. 352 [96] Nagumo, M. 151, 166, 237 [70] Necula, M. 154, 163, 178, 231, 233, 235 [24]; 237 [65]; 237 [71]; 237 [72]; 237 [73]; 237 [74] Neumann, M. 282, 284, 286–289, 349 [18] Ni, X. 554, 557 [85] Nicolaenko, B. 350 [43] Ntouyas, S.K. 469, 481, 494, 497, 505, 513, 555 [32]; 555 [33]; 555 [34]; 555 [35]; 555 [36]; 557 [86] Nussbaum, R.D. 315, 327, 352 [102]; 352 [117]; 354 [149]; 354 [150]; 354 [151] Ohta, Y. 305, 354 [152] Olian Fannio, L. 121, 143 [28] Ono, K. 125, 144 [41] Ortega, R. 302, 354 [153]; 439, 447, 458, 459 [5]; 459 [10]; 459 [25]; 460 [30] Oster, G. 315, 353 [136] Oxtoby, J. 257, 354 [154] Palamides, P.K. 547, 557 [87] Palmer, K.J. 138, 140, 145 [77] Pao, C.V. 341, 343, 354 [155] Pardo, R. 458, 459 [26] Pavel, N.H. 230–232, 234, 235 [5]; 237 [75]; 237 [76]; 237 [77]; 237 [78]; 237 [79] Pazy, A. 333, 354 [156] Peano, G. 149, 237 [80] Peixoto, M. 246, 354 [157] Perron, O. 223, 237 [81]; 315, 354 [158] Pituk, M. 313, 354 [159] Plaskacz, S. 190, 227, 228, 236 [45]; 237 [82] Plemmons, R. 287–289, 349 [19] Poláˇcik, P. 280, 281, 314, 320, 329, 332, 343, 345, 349 [22]; 350 [65]; 354 [160]; 354 [161]; 354 [162]; 354 [163]; 354 [164]; 354 [165] Pontryagin, L.S. 29, 75 [30]; 223, 237 [83] Post, W.M. 242, 350 [39]

Author Index Precupanu, Th. 11, 47, 74 [6] Protter, M.H. 346, 354 [166] Przeradski, B. 557 [88] Qian, C. 542, 554 [18] Qiu, J. 541, 542, 547, 554 [22]; 556 [64] Quincampoix, M. 161, 237 [84] Rabinowitz, P.H. 79, 80, 82, 87, 88, 99, 100, 109, 111, 118, 121, 136, 138, 139, 143 [19]; 143 [21]; 143 [26]; 143 [36]; 145 [78]; 145 [79]; 145 [80]; 145 [81]; 363, 371, 392, 395–397, 404, 407, 459 [6]; 460 [31] Raffoul, Y. 535, 557 [89] Ramos, M. 92, 94, 124, 144 [42] Ranft, P. 323, 324, 327, 352 [103] Ratiu, T.S. 6, 19, 75 [28] Raugel, G. 354 [167] Redheffer, R. 153, 154, 237 [85] Rescigno, A. 297, 354 [168] Richardson, I. 297, 354 [168] Rishel, R.W. 3, 73, 75 [22] Robinson, C. 349 [13]; 354 [169] Robinson, J. 354 [170] Rockafellar, R.T. 11, 14, 47, 75 [31]; 75 [32] Roxin, E. 174, 237 [86] Rubin, J.E. 156, 236 [57] Rudin, W. 306, 354 [171] Ruelle, D. 354 [172] Ruf, B. 115, 121, 143 [20] Rutman, M.A. 274, 315, 352 [104]; 354 [173] Rybicki, S. 107, 109, 143 [27] Rze˙zuchowski, T. 190, 228, 236 [45] Sachkov, Y.L. 3, 16, 18, 57, 67, 74 [2] Sacker, R. 332, 354 [174] Salamon, D. 80, 145 [74] Samarskii, A. 470, 554 [8] Sánchez, L. 302, 354 [153] Sandholm, W. 302, 351 [81] Sandstede, B. 314, 349 [22] Saperstone, S.H. 246, 354 [175] Sattinger, D. 314, 354 [176] Schappacher, W. 305, 352 [109] Schiaffino, A. 314, 329–331, 350 [42]; 438, 454, 460 [29] Schneider, H. 282, 284, 286, 301, 353 [122]; 354 [177] Schuur, I.D. 227, 235 [6] Schwartz, J.T. 201, 234, 236 [40] Scorza Dragoni, G. 190, 237 [87]; 237 [88] Secchi, S. 135, 145 [82]

563

Selgrade, J. 297, 315, 354 [178]; 355 [179]; 355 [180]; 355 [181] Sell, G. 332, 354 [174] Séré, E. 126, 135, 139, 140, 142, 143 [25]; 145 [83] Severi, F. 159, 222, 237 [89]; 238 [90] Shan, W. 541, 555 [23] Shi, S.Z. 231, 232, 238 [91] Siegel, D. 289, 345, 352 [110]; 352 [111]; 352 [112]; 353 [145] Sivasundaram, S. 475, 557 [84] Sleeman, B.D. 332, 357 [246] Slemrod, M. 327, 350 [35] Smale, S. 294, 297, 351 [80]; 355 [182] Smith, H.L. 242, 247, 249, 250, 255, 266, 267, 269, 271, 272, 281, 293, 296, 297, 299, 301, 302, 304, 305, 311–315, 318, 320, 327–329, 332, 337, 343, 345, 346, 350 [41]; 351 [83]; 353 [129]; 353 [130]; 353 [146]; 355 [183]; 355 [184]; 355 [185]; 355 [186]; 355 [187]; 355 [188]; 355 [189]; 355 [190]; 355 [191]; 355 [192]; 355 [193]; 355 [194]; 355 [195]; 355 [196]; 355 [197]; 355 [198]; 355 [199]; 355 [200]; 355 [201]; 355 [202]; 355 [203]; 357 [248]; 439, 460 [32]; 460 [33] Smith, R.A. 302, 355 [204] Smoller, J. 345, 355 [205] So, J.W.-H. 301, 351 [82] Somolinos, A.S. 314, 329, 332, 350 [60]; 439, 459 [14] Sontag, E.D. 3, 75 [33] Spanier, E.H. 83, 145 [84] Staicu, V. 233, 235 [17] Stanczy, R. 557 [88] Stern, R.J. 175, 226, 236 [33]; 236 [34]; 282, 284–289, 349 [18]; 355 [206] Stewart, H. 355 [207] Struwe, M. 87, 113, 145 [85]; 145 [86] Stuart, C.A. 126, 131, 135, 145 [82]; 145 [87] Suárez, A. 438, 459 [11] Szlenk, W. 142, 145 [88] Szulkin, A. 86, 90, 92, 95, 96, 106, 109, 115, 118, 121, 124, 129, 135, 136, 138, 142 [6]; 144 [57]; 144 [58]; 144 [59]; 144 [62]; 145 [89]; 145 [90]; 145 [91]; 145 [92]; 145 [93]; 145 [94] Takáˇc, P. 274, 281, 315, 316, 318, 321, 322, 327, 328, 332, 350 [45]; 350 [46]; 356 [208]; 356 [209]; 356 [210]; 356 [211]; 356 [212]; 356 [213]; 356 [214]; 356 [215]; 356 [216] Takahashi, T. 181, 237 [60] Tallos, P. 228, 238 [92] Tanaka, K. 135, 145 [95]

564

Author Index

Tang, M. 350 [50] Temam, R. 350 [43] Terešˇcák, I. 329, 354 [164]; 354 [165]; 356 [217] Thieme, H.R. 247, 250, 255, 266, 267, 269, 271, 272, 281, 304, 313, 315, 320, 332, 353 [146]; 355 [197]; 355 [198]; 355 [199]; 355 [200]; 355 [201]; 356 [218] Thompson, A.C. 324, 356 [219] Tikhomirov, V.M. 4, 75 [34] Timoshenko, S. 470, 557 [90] Tineo, A. 296, 356 [220]; 439, 447, 458, 459 [25]; 460 [30]; 460 [34]; 460 [35] Travis, C.C. 242, 350 [39] Treiman, J.S. 166, 238 [93] Trofimchuk, S. 494, 495, 555 [37]; 555 [38]; 555 [39]; 555 [40] Tsamatos, P.Ch. 469, 481, 494, 497, 505, 513, 542, 547, 555 [32]; 555 [33]; 555 [34]; 555 [35]; 555 [36]; 556 [48]; 556 [49]; 556 [50]; 556 [51]; 556 [52]; 556 [53]; 557 [86]

Wang, Z.-Q. 125, 143 [14]; 143 [15]; 144 [39] Wax, N. 297, 348 [1] Wa˙zewski, T. 227, 238 [107] Webb, J.R.L. 497, 505, 532, 542, 554 [15]; 554 [16]; 555 [46]; 555 [47]; 557 [92] Weinberger, H.F. 315, 346, 354 [166]; 356 [232] Weinstein, A. 106, 107, 111, 146 [98]; 146 [99] Wiggins, S. 138, 140, 146 [100] Wilder, R. 322, 356 [233] Willem, M. 80–82, 89, 90, 92, 94, 99, 124, 127, 129, 132, 135, 140, 143 [16]; 143 [31]; 144 [42]; 145 [73]; 146 [101]; 146 [102] Williams, L. 536, 548, 556 [55] Wolenski, P.R. 226, 236 [34] Wolkowicz, H. 285, 355 [206] Wu, J. 303, 313, 320, 352 [105]; 352 [106]; 352 [107]; 352 [108]; 356 [234]; 356 [235]; 357 [236] Wysocki, K. 115, 144 [50]

Uhl, R. 282, 356 [221] Ursescu, C. 151, 152, 154, 158, 161, 162, 166, 175, 176, 210, 213, 222, 225, 227, 228, 234, 235 [25]; 235 [26]; 237 [77]; 238 [94]; 238 [95]; 238 [96]; 238 [97]; 238 [98]; 238 [99]; 238 [100]; 238 [101] Uryson, P.S. 314, 356 [222]

Xiao, D. 301, 357 [237] Xu, J.-M. 489, 554 [1] Xu, X. 118, 135, 138, 145 [70]; 146 [103]

van den Driessche, P. 296, 301, 356 [223] van Duijn, C. 349 [27] Verduyn Lunel, S.M. 302, 303, 305, 307, 309, 315, 350 [61]; 352 [117] Vespri, V. 340, 349 [29] Vidyasagar, M. 282, 284, 286, 301, 354 [177] Vinter, R.B. 73, 74 [14]; 223, 236 [35] Viterbo, C. 113, 115, 145 [96]; 146 [97] Volkmann, P. 282, 284, 352 [118]; 356 [224] Vrabie, I.I. 21, 75 [35]; 151, 152, 154, 171, 173, 174, 177, 178, 228, 230–234, 235 [24]; 235 [27]; 235 [28]; 237 [74]; 237 [78]; 237 [79]; 238 [102]; 238 [103]; 238 [104]; 238 [105]; 238 [106] Vulikh, B. 338, 356 [225] Walcher, S. 282, 356 [226] Walter, W. 282, 289, 343, 356 [227]; 356 [228] Walther, H.-O. 303, 313, 352 [105] Waltman, P. 249, 302, 320, 332, 343, 351 [83]; 351 [84]; 355 [202]; 355 [203] Wang, H.Z. 54, 75 [36]; 532, 557 [79] Wang, J. 533, 553, 557 [91]; 557 [94]; 557 [95] Wang, Y. 296, 314, 332, 356 [229]; 356 [230]; 356 [231]

Yang, B. 542, 554 [18] Yorke, J.A. 151–154, 217, 220, 238 [108]; 238 [109] Yoshizawa, T. 216, 238 [110] Yosida, S. 47, 75 [37] Yu, J. 516, 556 [61]; 556 [62] Yu, S. 265, 319, 351 [90] Zabczyk, J. 3, 67, 75 [38] Zabreiko, P.P. 314, 352 [101] Zanolin, F. 332, 357 [238]; 439, 460 [36] Zaremba, S.C. 227, 238 [111] Zeeman, E.C. 296, 301, 357 [239]; 357 [240]; 357 [241]; 357 [242] Zeeman, M.L. 296, 301, 356 [223]; 357 [240]; 357 [241]; 357 [242]; 357 [243] Zehnder, E. 80, 104, 106, 113, 115, 121, 124, 125, 142 [3]; 142 [4]; 143 [24]; 144 [50]; 144 [51]; 144 [52] Zeidler, E. 274, 357 [244] Zhang, M. 482, 557 [93] Zhang, Z. 533, 557 [94]; 557 [95] Zhao, X.-Q. 314, 332, 357 [245]; 357 [246] Zheng, D. 553, 557 [91] Zhu, C. 115, 144 [67]; 145 [71] Zhu, H.-R. 302, 357 [247]; 357 [248] Ziehe, M. 315, 355 [181] Zou, W. 121, 135, 145 [93]; 145 [94]

Subject Index τ -topology, 95

component of coexistence states, 404 component of positive solutions, 394 concave functional, 536 conditionally completely continuous map, 266 cone, 536 – conjugate, 163 – contingent, 160 – in the sense of Bony, 162 – normal, 11, 15 – proximal normal, 161 – tangent, 15 conjugate mapping, 141 conjugate point, 8, 67 Conley–Zehnder index, 106 contingent derivative, 227 contraction, 325 control, 9 – bang-bang, 9, 47 – closed loop, 62 – constraints, 9 – feedback, 62 – open loop, 62 – optimal, 9, 55, 62 convergent, 246, 317 cooperative map, 329 cost functional, 9 critical orbit, 88 crossing number, 393 curve of change of stability, 376–378 curve of neutral stability, 376, 377

accessible point, 244 adapted space, 335 admissible pair, 9 Arnold conjecture, 125 asymptotically order stable, 262 attainable set, 55 attract, 245 attractor, 245 axiom – of choice, 156 – of countable choice, 156 – of dependent choice, 156 Banach lattice, 338 basin, 258 Bernoulli shift, 140 Bochner integral, 21 Bolza problem, 9, 30, 40, 56 Brezis–Browder ordering principle, 157 C0 -semigroup, 229 Carathéodory function, 471 Cartan formula, 24 Cerami sequence, 96 chain recurrent, 293 chronological exponential – left, 22 – right, 19 classical solution, 468 closed loop system, 62 closed order interval, 244 cocycle identities, 333 coexistence state, 361, 401 compact map, 335 comparison property – Carathéodory, 198 – of a function, 180 – of a multifunction, 212 competing species, 379, 438 competitive map, 329 completely continuous map, 266

deformation lemma, 81 derivation, 18 derivative – contingent, 227 – Dini right lower, 175 – right directional – – of the norm, 162 diameter, 258 directional derivative, 11, 14 domain, 149 doubly accessible point, 257 dual cone, 281 565

566 eigenvalue, 393 Ekeland variational principle, 15 entire orbit, 320 equation – Bellman, 63 – dynamic programming, 63 – eikonal, 72 – Euler–Lagrange, 5 – generalized Bellman, 224 – Hamilton, 6, 27 – Hamilton–Jacobi, 7, 63 – semilinear differential, 230 equilibrium, 245, 316 equivariant mapping, 87 escape time, 334 eventually strongly monotone, 247 eventually strongly monotone map, 316 extremal, 5 falling interval, 249, 317 five functional fixed point theorem, 548 fixed point, 316 – index, 393 – index theorem, 525 – set, 87 Floquet multipliers, 375, 377, 415 flow, 17, 245 – Hamiltonian, 27 function – Carathéodory comparison, 197 – comparison, 154 – conjugate, 12 – convex, 10 – effective domain, 10 – epigraph, 10 – integrable, 21 – locally Lipschitz, 14 – lower semicontinuous, 10 – of Carathéodory type, 190 – positively sublinear, 173 – proper, 10 – regulated, 229 – Severi differentiable, 222 – strongly measurable, 21 – synthesis, 63 – weakly measurable, 21 functional ordering, 245 fundamental matrix, 414 generalized gradient, 14 genus, 86 geometrically distinct homoclinic solutions, 128 geometrically distinct periodic solutions, 100 global attractor, 246

Subject Index global process, 333 group representation, 87 Hamiltonian, 6, 27 Hamiltonian lift, 28 high intensity competition, 384 homoclinic solutions, 126 – geometrically distinct, 128 hyperbolic point solution, 126 hysteresis point, 431 index, 88 infimum, 244 infinitesimal generator, 229 invariant, 245 – forward, 152 – local, 152 – locally right, 152 – mapping, 87 – right, 152 – set, 87 invariantly connected set, 316 isometric group representation, 87 k-bump solution, 138 K-competitive, 289 K-cooperative, 285 K-irreducible matrix, 288 K-positive matrix, 284 Krasnoselskii’s fixed point theorem, 519 Krein–Rutman operator, 274 Lagrange problem, 9, 56 Lebesgue point, 34 Legendre transform, 6, 12 Legget–Williams fixed point theorem, 536 lemma of Cârj˘a–Ursescu, 177, 210 limit genus, 92 limit index, 92 Liouville formula, 414 Lipschitz system, 292 local linking, 83 local semiflow, 251 locally closed, 335 locally closed set, 86 locally Hölder map, 333 locally Lipschitz map, 333 locally monotone map, 290 locally strongly monotone map, 290 logistic equation, 364 Lotka–Volterra periodic system, 362 low intensity competition, 384 lower boundary, 244

Subject Index M-maximal element, 157 m-point BVP, 470 mapping – positively sublinear, 208 Maslov index, 106 maximal element, 244 Mayer problem, 9, 56 mild solution, 334, 468 minimal element, 244 minimal set, 269 monotone map, 316 monotone system, 282 multi-point BVP, 470 multibump solution, 138 multifunction, 164 – l.s.c. at a point, 200 – l.s.c. on a set, 200 – u.s.c. at a point, 200 – u.s.c. on a set, 200 necessary conditions, 5, 29 – Jacobi, 8 – Legendre, 6 – Weierstrass–Erdmann, 6 negative semiorbit, 289 non-cooperative periodic system, 456 nonexpansive map, 325 nonlocal BVP, 470 nonlocal condition, 463 nonlocal initial value problem, 465 nonresonance, 489 nonwandering set, 319 normality constant, 259 normally ordered space, 259 omega limit set, 246 open order interval, 244 operator pencil, 393 optimal control problem, 9 optimal pair, 9 optimal state, 9 orbit, 87, 245, 333 – of a set, 266 order bounded, 244 order compact, 322 order neighborhood, 261 order norm, 261 order related, 244 order stable, 262 order topology, 261 ordered Banach space, 245 ordered space, 243 ordered subspace, 244

p-convex, 245 Palais–Smale condition, 81 Palais–Smale sequence, 81 period, 245 periodic, 245, 316 periodic solutions – geometrically distinct, 100 Poincaré map, 377, 414, 417, 441 point dissipative, 329 Poisson bracket, 27 polyhedral, 281 positive operator, 316 positive semiorbit, 289 positive solution, 519 positively invariant, 245, 333 positivity properties, 364 predator–prey model, 386, 455 preorder, 176 – closed, 176 principal characteristic exponent, 428, 449 principal eigenvalue, 417 problem – abnormal, 30 – normal, 30 – of local invariance, 152 process, 333 projection – subordinated to V, 158 proposition – Roxin, 174 proximal neighborhood, 158 (PS)-attractor, 96 (PS)c -condition, 81 (PS)∗ -condition, 91 (PS)∗ -sequence, 91 pseudo-gradient vector field, 82 pseudo-symmetric function, 547 quasi-cooperative system, 440 quasiconvergent, 246, 317 quasiderivative map, 273 quasimonotone condition, 282 quasimonotone condition (QMD), 304 reachable set, 55 reaction–diffusion systems, 339 recurrence, 293 regularization, 13 relation – preorder, 156 relative Morse index, 105, 106 representation – diffeomorphisms, 18

567

568 – points, 18 – tangent vectors, 18 – vector fields, 18 reproducing cone, 322 resolvent operator, 366 resonance, 489 rising interval, 249, 317 sectorial, 333 semi-trivial positive state, 361 semiconjugate mapping, 141 semiflow, 245 semiorbit, 251 set – reachable, 224 – target, 224 Severi differential – at x, 222 – at x in the direction u, 222 singular value of an operator pencil, 393 solution – ε-approximate, 168, 206 – Carathéodory, 190 – contingent, 227, 233 – flow, 245 – global, 172 – mild, or C 0 , 229 – noncontinuable, 172, 207 – of a differential inclusion, 202 – of inequality, 224 – process, 335 – right funnel, 219 – semigroup, 229 – to a differential equation, 149 spectral radius, 274 stable fixed point, 320 stable from above, 258 stable from below, 258 standard cone, 245 state of the system, 9 strictly monotone, 246 strictly monotone map, 316 strong approximation, 265 strong maximum principle, 393 strong ordering, 244 strongly accessible, 265 strongly increasing, 370 strongly monotone, 246 strongly negative, 366 strongly order-preserving, 246 strongly order-preserving (SOP) map, 316 strongly positive, 366 strongly positive operator, 316 strongly sublinear map, 324

Subject Index sub-critical turning point, 431 subdifferential, 11 subgradient, 11 sublinear map, 323 subset – Carathéodory invariant, 197 – Carathéodory locally invariant, 197 – closed relative to D, 151 – flow invariant, 153 – invariant, 178, 210 – locally closed, 151, 158 – locally invariant, 178, 210 – right viable with respect to f , 149 – right viable with respect to F , 202 – viable, 166 subsolution, 367, 368 super-critical turning point, 431 superlinear indefinite model, 388 supersolution, 367, 368 supremum, 244 symbiotic species, 387, 411 synthesis problem, 63 system – strongly decreasing, 226 – weakly decreasing, 226 t -cross-section of Fτ,ξ , 219 theorem – Bony, 153 – Brezis–Browder, 157 – Hukuhara, 220 – Kneser, 221 – Nagumo, 151, 166 – Pavel, 231 – Peano, 149 – Redheffer, 154 – Scorza Dragoni, 190 – Shi, 232 – Vitali, 234 – Yorke, 217, 220 – Yoshizawa, 216 topological degree, 393 topologically equivalent, 292 totally competitive, 294 totally ordered arc, 255 trajectory, 245, 333 transversality conditions, 7, 30, 61 trivial state, 361 uniform global attractor, 321 unilateral bifurcation theorem, 397 unordered, 244 unstable from above, 268

Subject Index unstable from below, 269 upper boundary, 244 variation of constants formula, 24 variation of parameters method, 24 vector – metric normal to K at ξ , 153, 161 – tangent in the sense of – – Bony, 162 – – Bouligand–Severi, 159 – – Clarke, 163

569

– – Federer, 161 vector field – complete, 17 – Hamiltonian, 27 – nonautonomous, 16 vector ordering, 245 very strongly order preserving (VSOP) process, 336 viability, 149 Yosida approximation, 13


Ordinary Differential Equations

Differential Equation Ordinary Differential Equations

Differential Equation - Ordinary Differential Equations