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Proof of the LaSalle Invariance Principle 📂Dynamics

Proof of the LaSalle Invariance Principle

Principle

Buildup

Let’s consider a vector field given by the following differential equation for space XX and function f:XXf : X \to X. x˙=f(x) \dot{x} = f(x) Let’s call the compact positively invariant set under the flow ϕt()\phi_t \left( \cdot \right) as MRn\mathcal{M} \subset \mathbb{R}^{n}.

When a Lyapunov function V:MRV : \mathcal{M} \to \mathbb{R} is defined as in M\mathcal{M}, consider the following two sets. E:={xM:V(x)=0} E := \left\{ x \in \mathcal{M} : V ' (x) = 0 \right\} The set MM defined as follows for EE is called the Positively Invariant Part. M:={The union of all trajectories that start in E and remain in E for all t>0} M:=\left\{ \text{The union of all trajectories that start in E and remain in E for all } t >0 \right\}

Lasalle Invariance Principle

For all xMx \in \mathcal{M}, when tt \to \infty then it is ϕt(x)M\phi_{t} (x) \to M.

Proof 1

Strategy: Mainly uses the definition of Lyapunov function and properties of omega limit sets.

Definition of Lyapunov function: Let’s consider a vector field given by the following differential equation for space XX and function f:XXf : X \to X. x˙=f(x) \dot{x} = f(x) Given a point x0Xx_{0} \in X in such an autonomous system, a scalar function VC1(N(x0),R)V \in C^{1} \left( \mathcal{N} (x_{0}) , \mathbb{R} \right) defined in the neighborhood N(x0)\mathcal{N} \left( x_{0} \right) of x0x_{0} is called a Liapunov Function if it satisfies the following conditions:

  • (i): If V(x0)=0V(x_{0}) = 0 and xx0x \ne x_{0}, then V(x)>0V(x) > 0
  • (ii): In xN(x0){x0}x \in \mathcal{N} \left( x_{0} \right) \setminus \left\{ x_{0} \right\}, it is V(x)0V ' (x) \le 0

Properties of Omega Limit Sets: Assuming the whole space is the Euclidean space X=RnX = \mathbb{R}^{n} and given a point pMp \in \mathcal{M} of the compact positively invariant set M\mathcal{M} under the flow ϕt()\phi_{t} ( \cdot ):

  • [1]: ω(p)\omega (p) \ne \emptyset
  • [2]: ω(p)\omega (p) is a closed set.
  • [3]: ω(p)\omega (p) is invariant under the flow. In other words, ω(p)\omega (p) is a union of orbits.
  • [4]: ω(p)\omega (p) is a connected space.

First, let’s show that in the omega limit set ω(x)\omega (x), VV becomes a constant function V=χV = \chi. xω(x)χ=V(x) \overline{x} \in \omega (x) \\ \chi = V \left( \overline{x} \right) If we assume that, then VV does not increase according to the flow ϕt\phi_{t}. In other words, for titti+1t_{i} \le t \le t_{i+1}, V(ϕti(x))V(ϕt(x))V(ϕti+1(x)) V \left( \phi_{t_{i}} (x) \right) \ge V \left( \phi_{t} (x) \right) \ge V \left( \phi_{t_{i+1}} (x) \right) it is, and due to the continuity of Lyapunov function VV, χ\chi becomes the greatest lower bound, namely the infimum, of {V(ϕt(x)):t0}\left\{ V \left( \phi_{t} (x) \right) : t \ge 0 \right\}. Since the omega limit set ω(x)\omega (x) is invariant under the flow, ϕt(x)\phi_{t} ( \overline{x} ) also becomes an omega limit point of ϕt(x)\phi_{t}(x). Since χ\chi was the infimum of {V(ϕt(x)):t0}\left\{ V \left( \phi_{t} (x) \right) : t \ge 0 \right\} as mentioned above, V(ϕt(x))=χ V \left( \phi_{t} \left( \overline{x} \right) \right) = \chi χ\chi is constant, so in ω(x)\omega (x), it is V=0V’ = 0, and according to the definition of EE, it is ω(x)E\omega (x) \subset E. Meanwhile, since ω(x)\omega (x) is an invariant set and according to the definition of MM, it is also ω(x)M\omega (x) \subset M. Thus, when tt \to \infty, it is ϕt(x)M\phi_{t} (x) \to M.


  1. Wiggins. (2003). Introduction to Applied Nonlinear Dynamical Systems and Chaos Second Edition(2nd Edition): p111. ↩︎