Finding a Lyapunov function for modified quadratic form. I was hoping people might have some suggests on what types of equations to try. The system of n equations is given by: dotx=MD(x)Rx-g(x)

anraszbx

anraszbx

Answered question

2022-11-04

Finding a Lyapunov function for modified quadratic form
I am trying to construct a Lyapunov function to show global asymptotic stability for a somewhat difficult system of equations. I was hoping people might have some suggests on what types of equations to try. The system of n equations is given by:
x ˙ = M D ( x ) R x g ( x )
where M is a symmetric matrix, D ( x ) is a diagonal matrix with x on the diagonals, and g(x) is a positive-definite function that is linear in x. If M is the identity then this reduces to a standard quadratic form. But for M otherwise, I am unable to control this system. You can assume that M and R are full rank, and that M is positive definite.
I have been considering equations of the form:
V ( x ) = i ( B x ) i log ( ( B x ) i ( B x ) i )
such that:
V ˙ ( x ) = i ( B x ) i ( B x ) i ( B x ˙ ) i
for some matrix B. For example, if B is the identity matrix, then this gives:
V ˙ ( x ) = i x i x i x ˙ i
But I am starting to think that this general form is not an appropriate form to work with, as I cannot make any progress. My idea is that B should be related to M and/or R, but no luck.
Are there any obvious things I am missing or alternate Lyapunov functions that I should explore?

Answer & Explanation

Emma Singleton

Emma Singleton

Beginner2022-11-05Added 11 answers

Step 1
I assume you have linearized the system at a particular equilibrium point, which is the origin of your nonlinear differential equation. Note, that we only investigate the stability of equilibrium point of a nonlinear system and not the system as a whole.
If the linearized system is given by
Δ x ˙ = A Δ x .
Determine all the eigenvalues of A. By Lyapunov's indirect method we can distinguish three cases:
1. Case: All eigenvalues have a strictly negative real part. This implies that the equilibrium point of the nonlinear system is at least asymptotically stable.
2. Case: There exists at least one eigenvalue that has a strictly positive real part. This implies instability of the equilibrium point of the nonlinear system.
3. Case: All eigenvalues have a real part that is negative or equal to zero and there are eigenvalues with real part 0. This is the indecisive case by the indirect method.
Step 2
If you are in case one then you can invoke Lyapunov's converse theorems. This means that you can use the Lyapunov equation
P A + A T P = Q
in which P is a positive definite symmetric matrix and Q is a positive definite matrix. Often Q is chosen as the identity matrix I. By Lyapunov's converse theorem it is guaranteed that there exists a unique P such that
V ( Δ x ) = Δ x T P Δ x
is a Lyapunov function of the nonlinear system in a neighbourhood of the equilibrium point (which is shifted to the origin).

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