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DYNAMICS · 1

Flows and invariant sets

11 concepts · 21 questions

Flows and the group property, invariant and trapping sets, omega-limit sets and their properties, Lyapunov functions, LaSalle's invariance principle and basins of attraction.

Overview 1The plan of this section

Linearisation describes a system near one equilibrium. Dynamical systems asks about the long run: where do orbits end up, and how big is each basin?

  1. Flows (Def. 1.1) and the group property (Prop. 1.2); invariant sets (Def. 1.3).
  2. Omega-limit sets (Def. 1.4) and their properties (Prop. 1.5).
  3. Lyapunov's theorem (Thm 1.6), LaSalle's invariance principle (Thm 1.7), with the damped pendulum (Example 1.8), and basins of attraction (Cor. 1.9).

Long-term behaviour: limit sets, invariant sets, and Lyapunov functions that decrease along orbits.

Definition 1.1Flows

For x˙=f(x)\dot{\mathbf{x}} = \mathbf{f}(\mathbf{x}) with f\mathbf{f} locally Lipschitz, the flow φt(x0)\varphi_t(\mathbf{x}_0) is the value at time tt of the unique solution with x(0)=x0\mathbf{x}(0) = \mathbf{x}_0. The orbit of x0\mathbf{x}_0 is {φt(x0)}\{\varphi_t(\mathbf{x}_0)\} and the forward orbit {φt(x0):t≥0}\{\varphi_t(\mathbf{x}_0): t\ge0\}. Distinct orbits never cross.

φt(x0)\varphi_t(\mathbf{x}_0): where x0\mathbf{x}_0 is after time tt. Orbits never cross (uniqueness).

Proposition 1.2The group property

Wherever defined, φ0=id\varphi_0 = \mathrm{id} and φt+s=φt∘φs\varphi_{t + s} = \varphi_t\circ\varphi_s. Hence each φt\varphi_t is invertible with inverse φ−t\varphi_{-t}, and orbits are either equilibria, closed (periodic) orbits, or one-to-one images of an interval.

φt+s=φt∘φs\varphi_{t+s} = \varphi_t\circ\varphi_s; orbits are points, loops, or non-self-intersecting curves.

Proof

Definition 1.3Invariant and trapping sets

A set AA is invariant if φt(A)⊆A\varphi_t(A)\subseteq A for all tt, and positively invariant if this holds for t≥0t\ge0. A compact positively invariant set is a trapping region; one is found by checking f\mathbf{f} points inward (or along) on its boundary, e.g. ∇g⋅f≤0\nabla g\cdot\mathbf{f}\le0 on {g=c}\{g = c\} makes {g≤c}\{g\le c\} positively invariant.

Invariant: orbits stay in. Trapping region: compact, forward invariant; check the field points inward on the boundary.

Definition 1.4Omega- and alpha-limit sets

The omega-limit set of x\mathbf{x} is ω(x)={y:φtk(x)→y for some tk→∞}\omega(\mathbf{x}) = \{\mathbf{y}: \varphi_{t_k}(\mathbf{x})\to\mathbf{y}\text{ for some }t_k\to\infty\}; the alpha-limit set α(x)\alpha(\mathbf{x}) uses tk→−∞t_k\to-\infty. Equivalently ω(x)=⋂T≥0{φt(x):t≥T}‾\omega(\mathbf{x}) = \bigcap_{T\ge0}\overline{\{\varphi_t(\mathbf{x}): t\ge T\}}.

ω(x)\omega(\mathbf{x}): where the orbit accumulates as t→∞t\to\infty.

Proposition 1.5Properties of omega-limit sets

If the forward orbit of x\mathbf{x} lies in a compact set KK, then ω(x)\omega(\mathbf{x}) is non-empty, compact, connected and invariant, and dist⁡(φt(x),ω(x))→0\operatorname{dist}(\varphi_t(\mathbf{x}), \omega(\mathbf{x}))\to0 as t→∞t\to\infty.

Bounded forward orbit ⇒ ω(x)\omega(\mathbf{x}) non-empty, compact, connected, invariant, and attracts the orbit.

Proof

Theorem 1.6Lyapunov's stability theorem

Let x∗\mathbf{x}^* be an equilibrium and VV a C1C^1 function on a neighbourhood UU with V(x∗)=0V(\mathbf{x}^*) = 0, V>0V > 0 on U∖{x∗}U\setminus\{\mathbf{x}^*\}. If V˙=∇V⋅f≤0\dot V = \nabla V\cdot\mathbf{f}\le0 on UU, then x∗\mathbf{x}^* is stable; if V˙<0\dot V < 0 on U∖{x∗}U\setminus\{\mathbf{x}^*\}, it is asymptotically stable.

V>0V > 0, V˙≤0\dot V\le0 ⇒ stable; V˙<0\dot V < 0 ⇒ asymptotically stable.

Proof

Theorem 1.7LaSalle's invariance principle

Let KK be a trapping region and VV a C1C^1 function with V˙≤0\dot V\le0 on KK. Let MM be the largest invariant set contained in {x∈K:V˙(x)=0}\{\mathbf{x}\in K: \dot V(\mathbf{x}) = 0\}. Then every orbit starting in KK approaches MM as t→∞t\to\infty.

Only V˙≤0\dot V\le0 needed: orbits approach the largest invariant set where V˙=0\dot V = 0.

Proof

Example 1.8The damped pendulum

For θ¨+kθ˙+sin⁡θ=0\ddot\theta + k\dot\theta + \sin\theta = 0 (k>0k > 0), write ω=θ˙\omega = \dot\theta and V=12ω2+1−cos⁡θV = \frac12\omega^2 + 1 - \cos\theta. Then V˙=−kω2≤0\dot V = -k\omega^2\le0. On {ω=0}\{\omega = 0\} an invariant set needs ω˙=−sin⁡θ=0\dot\omega = -\sin\theta = 0, so near the origin M={(0,0)}M = \{(0, 0)\}. By LaSalle the hanging position is asymptotically stable, with basin containing {V<2}∩{∣θ∣<π}\{V < 2\}\cap\{|\theta| < \pi\}.

Energy decreases, and the only invariant set where it stops decreasing is the equilibrium: asymptotic stability by LaSalle.

Corollary 1.9Estimating basins of attraction

The basin of attraction of an asymptotically stable x∗\mathbf{x}^* is the set of x\mathbf{x} with φt(x)→x∗\varphi_t(\mathbf{x})\to\mathbf{x}^*. If Ωc={V≤c}\Omega_c = \{V\le c\} (the component containing x∗\mathbf{x}^*) is bounded, V˙<0\dot V < 0 on Ωc∖{x∗}\Omega_c\setminus\{\mathbf{x}^*\}, then Ωc\Omega_c lies in the basin.

Bounded sublevel sets of a strict Lyapunov function lie in the basin.

Proof

Check 1.10Check: proving stability without linearisation

  • Try energy-like VV: quadratic forms ax2+by2ax^2 + by^2 with a,ba, b chosen to cancel cross terms, or the physical energy.
  • V˙<0\dot V < 0 off the equilibrium: Lyapunov. Only V˙≤0\dot V\le0: find the largest invariant set in {V˙=0}\{\dot V = 0\} (LaSalle).
  • Basin: largest bounded sublevel set of VV on which V˙<0\dot V < 0.
  • Trap: VV must be positive definite near x∗\mathbf{x}^*; V˙≤0\dot V\le0 alone gives only stability.

Choose VV to kill cross terms; V˙≤0\dot V\le0 → LaSalle; sublevel sets estimate basins.