Proving Lyapunov Stability for \(\dot{x} = Ax + B(t)x\)

In summary, the conversation is about a question regarding the stability of the solution (y, y') = (0,0) for the equation \ddot{y} - \frac{2}{t}\dot{y} + y = 0. The speaker mentions that they believe it is true but are struggling to prove it. They suggest rewriting the equation as a system of equations in matrix form, but are unable to find an eigenvalue with a positive real part. They are unsure if they have made a mistake or if there is another theorem that can prove the trivial solution is unstable.
  • #1
motherh
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A question I am doing hints that the solution (y,[itex]\dot{y}[/itex]) = (0,0) of [itex]\ddot{y}[/itex] - [itex]\frac{2}{t}[/itex][itex]\dot{y}[/itex] + y = 0 is unstable. I believe (although I am not 100% sure) that is true however I am struggling to prove it.

I can rewrite the equation as a system of equations in matrix form to get

[itex]\dot{x}[/itex] = Ax + B(t)x,

where A = [{0,1},{-1,0}], B(t) = [{0,0},{0,[itex]\frac{2}{t}[/itex]}].

This the form of all the theorems I appear to have. But all my theorems require me to find an eigenvalue of A with positive real part - which I can't here.

So basically have I made a mistake already or is there another theorem anybody knows of that can tell me the trivial solution is unstable?
 
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Anybody?
 

FAQ: Proving Lyapunov Stability for \(\dot{x} = Ax + B(t)x\)

What is Lyapunov stability?

Lyapunov stability is a concept in control theory that refers to the stability of a dynamical system. It is a measure of how a system responds to small perturbations or disturbances, and whether it will eventually return to its original state or diverge away from it.

What is the importance of proving Lyapunov stability?

Proving Lyapunov stability is important because it provides a mathematical guarantee of the stability of a system. This is crucial in the design and analysis of control systems, as it ensures that the system will behave in a predictable and desirable manner.

How is Lyapunov stability proven for \(\dot{x} = Ax + B(t)x\)?

The most common method for proving Lyapunov stability for \(\dot{x} = Ax + B(t)x\) is to use the Lyapunov direct method. This method involves finding a Lyapunov function, which is a scalar function that decreases along the trajectories of the system. If a valid Lyapunov function can be found, then the system is proven to be stable.

What are the assumptions for proving Lyapunov stability?

The assumptions for proving Lyapunov stability include continuity and differentiability of the system dynamics, and the existence of a continuously differentiable Lyapunov function. Additionally, the system must have a unique equilibrium point and satisfy a local Lipschitz condition.

Can Lyapunov stability be proven for nonlinear systems?

Yes, Lyapunov stability can be proven for both linear and nonlinear systems. However, the techniques for proving stability may differ for nonlinear systems, as the Lyapunov functions may be more difficult to find. Nonlinear systems may also have multiple equilibrium points, which can complicate the stability analysis.

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