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Differential Equation Definition. A differential equation is an equation which contains one or more terms and the derivatives of one variable (i.e., dependent variable) with respect to the other variable (i.e., independent variable) dy/dx = f (x) Here “x” is an independent variable and “y” is a dependent variable. For example, dy/dx = 5x.
How important really is differential equations?
Differential equations are equations that contains one or more terms involving derivatives of one variable (dependent variable) with respect to another variable (independent variable) or we can say that these are equations involving derivatives of a function or functions. They have a remarkable ability to predict the world around us.
Theory of Ordinary Differential Equations
Theory of Ordinary Differential Equations
CHRISTOPHERP. GRANT
Brigham Young University
Contents
Contentsi
1 Fundamental Theory1
1.1 ODEs and Dynamical Systems . . . . . . . . . . . . . . . . . . 1
1.2 Existence of Solutions . . . . . . . . . . . . . . . . . . . . . . 6
1.3 Uniqueness of Solutions . . . . . . . . . . . . . . . . . . . . . 9
1.4 Picard-Lindel¨of Theorem . . . . . . . . . . . . . . . . . . . . . 13
1.5 Intervals of Existence . . . . . . . . . . . . . . . . . . . . . . . 15
1.6 Dependence on Parameters . . . . . . . . . . . . . . . . . . . . 18
2 Linear Systems25
2.1 Constant Coefficient Linear Equations . . . . . . . . . . . . . . 25
2.2 Understanding the Matrix Exponential . . . . . . . . . . . . . . 27
2.3 Generalized Eigenspace Decomposition . . . . . . . . . . . . . 31
2.4 Operators on Generalized Eigenspaces . . . . . . . . . . . . . . 34
2.5 Real Canonical Form . . . . . . . . . . . . . . . . . . . . . . . 37
2.6 Solving Linear Systems . . . . . . . . . . . . . . . . . . . . . . 39
2.7 Qualitative Behavior of Linear Systems . . . . . . . . . . . . . 46
2.8 Exponential Decay . . . . . . . . . . . . . . . . . . . . . . . . 50
2.9 Nonautonomous Linear Systems . . . . . . . . . . . . . . . . . 52
2.10 Nearly Autonomous Linear Systems . . . . . . . . . . . . . . . 56
2.11 Periodic Linear Systems . . . . . . . . . . . . . . . . . . . . . 59
3 Topological Dynamics65
3.1 Invariant Sets and Limit Sets . . . . . . . . . . . . . . . . . . . 65
3.2 Regular and Singular Points . . . . . . . . . . . . . . . . . . . 69
3.3 Definitions of Stability . . . . . . . . . . . . . . . . . . . . . . 72
3.4 Principle of Linearized Stability . . . . . . . . . . . . . . . . . 77
3.5 Lyapunov's Direct Method . . . . . . . . . . . . . . . . . . . . 82
iCONTENTS
3.6 LaSalle's Invariance Principle . . . . . . . . . . . . . . . . . . 85
4 Conjugacies91
4.1 Hartman-Grobman Theorem: Part 1 . . . . . . . . . . . . . . . 91
4.2 Hartman-Grobman Theorem: Part 2 . . . . . . . . . . . . . . . 92
4.3 Hartman-Grobman Theorem: Part 3 . . . . . . . . . . . . . . . 95
4.4 Hartman-Grobman Theorem: Part 4 . . . . . . . . . . . . . . . 98
4.5 Hartman-Grobman Theorem: Part 5 . . . . . . . . . . . . . . . 101
4.6 Constructing Conjugacies . . . . . . . . . . . . . . . . . . . . . 104
4.7 Smooth Conjugacies . . . . . . . . . . . . . . . . . . . . . . . 107
5 Invariant Manifolds113
5.1 Stable Manifold Theorem: Part 1 . . . . . . . . . . . . . . . . . 113
5.2 Stable Manifold Theorem: Part 2 . . . . . . . . . . . . . . . . . 116
5.3 Stable Manifold Theorem: Part 3 . . . . . . . . . . . . . . . . . 119
5.4 Stable Manifold Theorem: Part 4 . . . . . . . . . . . . . . . . . 122
5.5 Stable Manifold Theorem: Part 5 . . . . . . . . . . . . . . . . . 125
5.6 Stable Manifold Theorem: Part 6 . . . . . . . . . . . . . . . . . 129
5.7 Center Manifolds . . . . . . . . . . . . . . . . . . . . . . . . . 132
5.8 Computing and Using Center Manifolds . . . . . . . . . . . . . 134
6 Periodic Orbits139
6.1 Poincar´e-Bendixson Theorem . . . . . . . . . . . . . . . . . . 139
6.2 Lienard's Equation . . . . . . . . . . . . . . . . . . . . . . . . 143
6.3 Lienard's Theorem . . . . . . . . . . . . . . . . . . . . . . . . 147
ii 1Fundamental Theory
1.1 ODEs and Dynamical Systems
Ordinary Differential Equations
An ordinary differential equation (or ODE) is an equation involving derivatives of an unknown quantity with respect to a single variable. More precisely, suppose j;n2N,Eis a Euclidean space, andFWdom.F/?R?
Then annth order ordinary differential equationis an equation of the formF.t;x.t/;Px.t/;Rx.t/;x
.3/.t/;???;x.n/.t//D0:(1.2) IfI?Ris an interval, thenxWI!Eis said to bea solution of(1.2)onIif xhas derivatives up to ordernat everyt2I, and those derivatives satisfy (1.2). Often, we will use notation that suppresses the dependence ofxont. Also, there will often be side conditions given that narrow down the set of solutions. In these notes, we will concentrate oninitial conditionswhich prescribex .`/.t0/for some fixedt02R(called theinitial time) and some choices of`2 f0;1;:::;ng. Some
ODE texts examinetwo-point boundary-value problems, in which the value of a function and its derivatives at two different points are required to satisfy given algebraic equations, but we won't focus on them in this one. 11. FUNDAMENTALTHEORY
First-order Equations
Every ODE can be transformed into an equivalent first-order equation. In partic- ular, givenxWI!E, suppose we define y 1WDx y2WD Px
y3WD Rx
y nWDx.n?1/; and letyWI!E nbe defined byyD.y1;:::;yn/. ForiD1;2;:::;n?1, define G iWR?En?En!E by G1.t;u;p/WDp1?u2
G2.t;u;p/WDp2?u3
G3.t;u;p/WDp3?u4
G n?1.t;u;p/WDpn?1?un; and, givenFas in (1.1), defineG nWdom.Gn/?R?En?En!Rjby G n.t;u;p/WDF.t;u1;:::;un;pn/; where dom.G n/D°.t;u;p/2R?En?En.t;u1;:::;un;pn/2dom.F/?:
LettingGWdom.G
n/?R?En?En!En?1?Rjbe defined byGWD0BBBBB@G
1 G2 G3::: G n 1 C C C C C A; we see thatxsatisfies (1.2) if and only ifysatisfiesG.t;y.t/;Py.t//D0. 2ODEs and Dynamical Systems
Equations Resolved with Respect to the Derivative
Consider the first-order initial-value problem (or IVP) 8 :F.t;x;Px/D0 x.t 0/Dx0Px.t0/Dp0;(1.3)
whereFWdom.F/?R?R n?Rn!Rn, andx0;p0are given elements ofRn satisfyingF.t0;x0;p0/D0. The Implicit Function Theorem says that typically the solutions.t;x;p/of the (algebraic) equationF.t;x;p/D0near.t0;x0;p0/
form an.nC1/-dimensional surface that can be parametrized by.t;x/. In other words, locally the equationF.t;x;p/D0is equivalent to an equation of the formpDf.t;x/for somefWdom.f /?R?R n!Rnwith.t0;x0/in the interior of dom.f /. Using thisf, (1.3) is locally equivalent to the IVPPxDf.t;x/
x.t0/Dx0:
Autonomous Equations
LetfWdom.f /?R?Rn!Rn. The ODE
PxDf.t;x/(1.4)
isautonomousiffdoesn't really depend ont,i.e., if dom.f /DR??for some ??R nand there is a functiongW?!Rnsuch thatf.t;u/Dg.u/for every t2Rand everyu2?. Every nonautonomous ODE is actually equivalent to an autonomous ODE.To see why this is so, givenxWR!R
n, defineyWR!RnC1byy.t/D .t;x1.t/;:::;xn.t//, and givenfWdom.f /?R?Rn!Rn, define a new
functionQfWdom.Qf /?R nC1!RnC1by Q f .p/D0BBB@1 f1.p1;.p2;:::;pnC1//
f n.p1;.p2;:::;pnC1//1CCCA wherefD.f1;:::;fn/Tand
dom.Qf /D°p2R nC1.p1;.p2;:::;pnC1//2dom.f /?:
Thenxsatisfies (1.4) if and only ifysatisfiesPyDQf .y/. 31. FUNDAMENTALTHEORY
Because of the discussion above, we will focus our study on first-order au- tonomous ODEs that are resolved with respect to the derivative. This decision is not completely without loss of generality, because by converting other sorts of ODEs into equivalent ones of this form, we may be neglecting some special structure that might be useful for us to consider. This trade-off between abstract- ness and specificity is one that you will encounter (and have probably already encountered) in other areas of mathematics. Sometimes, when transforming the equation would involve too great a loss of information, we'll specifically study higher-order and/or nonautonomous equations.Dynamical Systems
As we shall see, by placing conditions on the functionfW??Rn!Rnand the pointx02?we can guarantee that the autonomous IVP
PxDf.x/
x.0/Dx0(1.5)
has a solution defined on some intervalIcontaining0in its interior, and this so- lution will be unique (up to restriction or extension). Furthermore, it is possible to "splice" together solutions of (1.5) in a natural way, and, in fact, get solu- tions to IVPs with different initial times. These considerations lead us to study a structure known as adynamical system.Given??R
n, a continuous dynamical system (or aflow) on?is a function 'WR??!?satisfying:1.'.0;x/Dxfor everyx2?;
2.'.s;'.t;x//D'.sCt;x/for everyx2?and everys;t2R;
3.'is continuous.
Iffand?are sufficiently "nice" we will be able to define a function'WR??!?by letting'.?;x
0/be the unique solution of (1.5), and this defi-
nition will make'a dynamical system. Conversely, any continuous dynamical system'.t;x/that is differentiable with respect totis generated by an IVP.Exercise 1
Suppose that:
???R n; 4ODEs and Dynamical Systems
?'WR??!?is a continuous dynamical system; @'.t;x/ @texists for everyt2Rand everyx2?; ?xquotesdbs_dbs17.pdfusesText_23[PDF] theory of public debt management pdf
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