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Lyapunov Function 📂Dynamics

Lyapunov Function

Definition1

Given a space XX and a function f:XXf : X \to X, suppose the following vector field is given by a differential equation. x˙=f(x) \dot{x} = f(x) For a point x0Xx_{0} \in X in the above 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): V(x0)=0V(x_{0}) = 0, and for xx0x \ne x_{0}, then V(x)>0V(x) > 0
  • (ii): At xN(x0){x0}x \in \mathcal{N} \left( x_{0} \right) \setminus \left\{ x_{0} \right\}, V(x)0V ' (x) \le 0

  • C1(A,B)C^{1}(A,B) denotes the set of functions whose domain is AA and codomain is BB, which are differentiable and have continuous derivatives.
  • VV belonging to C1(N(x0),R)C^{1} \left( \mathcal{N} (x_{0}) , \mathbb{R} \right) means that VV is a scalar function defined in the neighborhood of x0x_{0}, differentiable, and vv ' is continuous.

Explanation

A Liapunov function may exist depending on the given system x˙=f(x)\dot{x} = f(x), and it can be considered especially to check the stability of a fixed point x0=xx_{0} = \overline{x} when X=RnX = \mathbb{R}^{n}. The existence of a Liapunov function implies stability, and VV should be appropriately defined according to the system ff. vv ' literally refers to the derivative with respect to time tt, and when differentiating VV, terms related to x˙\dot{x} emerge, revealing the relationship with ff.

From the above explanation, it may seem that a Liapunov function is a universal tool for understanding nonlinear systems, but as nonlinear systems are inherently difficult, finding this Liapunov function is not simple. There is no general method to find a Liapunov function, and in fact, finding it even for a single important system can be a challenging research topic.

Example

Let’s take a look at a very simple example of finding a Liapunov function: x˙=x+4yy˙=xy3 \begin{align*} \dot{x} =& -x + 4y \\ \dot{y} =& -x - y^{3} \end{align*} This system has a fixed point (0,0)(0,0). As mentioned, there is no general method for finding a Liapunov function, so intuition must be employed. As one gets used to finding Liapunov functions, the process becomes faster. Here, we assume that V(x,y)=x2+ay2V(x,y) = x^{2} + a y^{2} is a Liapunov function and will find it by specifying the value of a0a \ge 0.


Part 1.

Given V(0,0)=0V(0,0) = 0, and for (x,y)(0,0)(x,y) \ne (0,0), V(x,y)>0V(x,y) > 0 holds. From (0,0)(0,0), V=0V = 0, and assuming aa is non-negative, V>0V > 0.


Part 2.

From (x,y)N((0,0)){(0,0)}(x,y) \in \mathcal{N} \left( (0,0) \right) \setminus \left\{ (0,0) \right\}, V(x,y)0V ' (x,y) \le 0. Differentiating VV with respect to tt gives: dVdt=2xx˙+2ayy˙=2x(x+4y)+2ay(xy3)=2x2+(82a)xy2ay2 \begin{align*} {{ d V } \over { d t }} =& 2 x \dot{x} + 2 a y\dot{y} \\ =& 2x(-x+4y) + 2ay \left( -x-y^{3} \right) \\ =& -2x^{2} + (8-2a)xy - 2ay^{2} \end{align*} If a=4a=4, then V<0V ' <0.

Thus, given the fixed point (0,0)(0,0), we can guarantee the existence of a Liapunov function as V(x,y)=x2+4y2V(x,y) = x^{2} + 4 y^{2}, and it follows that (0,0)(0,0) possesses Liapunov stability based on its existence.


  1. Strogatz. (2015). Nonlinear Dynamics And Chaos: With Applications To Physics, Biology, Chemistry, And Engineering (2nd Edition): p201. ↩︎