Liapunov’s Second Method proof

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In summary, Liapunov's Second Method provides a systematic approach to analyze the stability of dynamical systems without solving their differential equations. It involves constructing a Lyapunov function, which is a scalar function that decreases along the trajectories of the system. By demonstrating that this function satisfies certain conditions, such as being positive definite and having a negative definite derivative, one can conclude the stability of the equilibrium point. This method is particularly useful for nonlinear systems, offering insights into their behavior near equilibrium without the need for explicit solutions.
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Homework Statement
Please see below
Relevant Equations
Please see below
For this theorem,
1716878000582.png

I'm trying to prove why ## a > 0## and ##4ac - b^2 > 0## for the function to be positive definite.

My working is, ##V(x,y) = x(ax + by) + cy^2## (I try on write the function in alternative forms)

##V(x,y) = ax^2 + y(bx + cy)##

However, does anybody please know where to go from here?

Thanks!
 
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I suggest that you define ##k = x/y## (the case ##y = 0## trivially gives ##a > 0## as a requirement) and require that ##V(ky,y) \geq 0## regardless of ##k##.
 
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  • #3
Orodruin said:
I suggest that you define ##k = x/y## (the case ##y = 0## trivially gives ##a > 0## as a requirement) and require that ##V(ky,y) \geq 0## regardless of ##k##.
Thank you for your reply @Orodruin!

I think I also see another method we could use for the proof.

Wolfram Alpha tells me that another equivalent way of writing ##V(x,y)## other than the two previous ways I have done, is

##V(x,y) = \frac{(2ax + by)^2}{4a} - \frac{b^2y^2 - 4acy^2}{4a}##

However, does anybody please know to derive this expression? It seems to work when I expand it, however, I have never seen this sort of expression before derived from first principles. That expression also neatly solves the proof by making sure the second term is always positive ##\frac{y^2(b^2 - 4ac)}{2a}## so that negatives cancels which occurs when ##b^2 - 4ac <0## and ##a > 0##.

Thanks!
 
  • #4
looks like some sort application of the quadratic formula, 4ac -b^2 gives it away.
The algebra can be done by setting the equation equal to zero (subtract V(x,y) from both sides and treat as part of the c term), applying quadratic formula, then set it equal to V(x,y)
 
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  • #5
Complete the square in [itex]x[/itex].
 
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  • #6
The matrix representing this function is: [a,b/2];[b/2,c]
A matrix is positive definite whenever <Av,v>>0 when v is a vector different than zero.
And that happens when det(A)>0 and trace(A)>=0.

the determinant is ac-b^2/4>0 and the trace is a+c>0.

if a<0 then because ac>0, also c<0 which is impossible since then we would get: a+c<0, contrary to the fact that the trace is positive.

But in order to know all the above, you really need to know linear algebra 2.
 
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BTW, one should assume obviously that a,b,c are real numbers.
 
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FAQ: Liapunov’s Second Method proof

What is Liapunov's Second Method?

Liapunov's Second Method, also known as the Liapunov stability theorem, is a technique used in control theory and dynamical systems to assess the stability of equilibrium points in nonlinear systems. It involves constructing a Liapunov function, which is a scalar function that helps determine whether the system's trajectories converge to an equilibrium point or diverge away from it.

How do you construct a Liapunov function?

To construct a Liapunov function, you typically start by identifying an equilibrium point of the system. You then propose a scalar function, usually positive definite, that captures the energy or "distance" of the system's state from the equilibrium. Common choices for Liapunov functions include quadratic forms. The function must satisfy certain conditions, such as being continuously differentiable and having a negative derivative along the system's trajectories.

What are the key conditions for Liapunov's Second Method to prove stability?

The key conditions for Liapunov's Second Method to prove stability are: the Liapunov function must be positive definite in a neighborhood of the equilibrium point, and its time derivative along the system's trajectories must be negative definite or negative semi-definite. If these conditions are met, it can be concluded that the equilibrium point is stable or asymptotically stable.

What is the difference between stability and asymptotic stability in Liapunov's Second Method?

Stability in the context of Liapunov's Second Method refers to the property that trajectories starting close to an equilibrium point remain close to it for all future times. Asymptotic stability, on the other hand, not only requires stability but also that trajectories converge to the equilibrium point as time approaches infinity. In other words, all nearby trajectories must eventually settle down at the equilibrium point.

Can Liapunov's Second Method be applied to systems with time-varying parameters?

Yes, Liapunov's Second Method can be applied to systems with time-varying parameters. In such cases, the Liapunov function can still be constructed, and the analysis involves considering the time-varying nature of the system. The stability conditions may need to be adapted to account for the variations, but the fundamental principles of using a Liapunov function to assess stability remain applicable.

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