Stability of 2 critical points in a system of DE's

In summary, the conversation discusses a system of differential equations involving a damped pendulum and the stability analysis of two critical points: (0,0) and (π,0). The person tries to analyze the stability by putting the system in matrix form and finding the eigenvalues, but faces difficulties. Another person provides guidance on how to analyze the stability at the critical points using linearization. After correcting a mistake, the person realizes that (0,0) behaves like an undamped oscillator.
  • #1
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Homework Statement


Basically I found the following system of DE's:
[itex]\frac{dx}{dt}=y[/itex]
[itex]\frac{dy}{dt}=-\frac{g}{l} \sin x - \frac{cy}{ml}[/itex]. (Damped pendulum)
I'm asked to analize the stability of the critical points [itex]x=0[/itex], [itex]y=0[/itex] and [itex]x=\pi[/itex], [itex]y=0[/itex].
Using intuition the first point is asymptotically stable while the second point is unstable.

Homework Equations


I tried to put the system under matrix form and then check out the eigenvalues of a matrix but I have some problems.

The Attempt at a Solution


[itex]\begin {bmatrix} \frac{dx}{dt} \\ \frac{dy}{dt} \end{bmatrix} =A \begin {bmatrix} x \\ y \end{bmatrix}[/itex] where [itex]A= \begin {bmatrix} a& b \\ c & d \end{bmatrix}[/itex].
I tried to determine the elements of the matrix A but was unable to perform this without making the assumption that [itex]\sin x \approx x[/itex] (for small x or x close to pi I guess?). Making that assumption I reached [itex]A\approx \begin {bmatrix} 0 &1 \\ -\frac{g}{l} & -\frac{c}{ml} \end{bmatrix}[/itex]. I found the eigenvalues to be [itex]\lambda _1 =- \frac{c}{2ml} + \sqrt {\frac{c^2}{ml^2} - \frac{4g}{l}}[/itex] and [itex]\lambda _2 =- \frac{c}{2ml} - \sqrt {\frac{c^2}{ml^2} - \frac{4g}{l}}[/itex].
So that I have a bunch of possible cases which doesn't look good at all to me. Furthermore I never used to information that the critical points are [itex](0,0)[/itex] and [itex](\pi , 0 )[/itex] yet.
Can someone make some comments so far? Thanks in advance.
 
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  • #2
Hello,

First of all, suppose you have a system in the general form X'=F(X), and let X_0 be a particular point. Then

$$ (X-X_0)' = F(X) ≈ dF_{X_0}(X-X_0) + F(X_0).$$

Being a critical point just means that F(X_0)=0, so you have a homogeneous linear term on the right side of your linear approximation.

$$ (X-X_0)' = A (X-X_0),$$
where [itex] A = dF_{X_0} [/itex].

You have analyzed A at X_0 = (0,0), now you just have to calculate the linearization at the other point and look at its eigenvalues.

See http://en.wikipedia.org/wiki/Stability_theory#Stability_of_fixed_points
 
  • #3
Hmm sorry I have no idea on what I've done. How do you know I "analyzed A at X_0 = (0,0)"? Where did I use the critical point (0,0)?
In another source I've read that [itex]\begin {bmatrix} x' \\ y' \end{bmatrix} =[/itex][itex] \begin {bmatrix} \frac{ \partial f (x_0, y_0 )}{\partial x } & \frac{ \partial f (x_0, y_0 )}{\partial y } \\ \frac{ \partial g (x_0, y_0 )}{\partial x } &\frac{ \partial g (x_0, y_0 )}{\partial y } \end{bmatrix}[/itex][itex] \begin {bmatrix} x \\ y \end{bmatrix}[/itex] where [itex]f(x,y)=y[/itex] and [itex]g(x,y)=-\frac{g}{l} \sin x - \frac{cy}{ml}[/itex]. Following this information I reach, for the critical point (0,0), [itex]A=\begin {bmatrix} 0 &1 \\ -\frac{g}{l} & 0 \end{bmatrix}[/itex] giving me the eigenvalues [itex]\pm i \sqrt {\frac{g}{l}}[/itex]. According to https://controls.engin.umich.edu/wiki/index.php/EigenvalueStability, this means that (0,0) behaves like an undamped oscillator because my 2 eigenvalues are complex with 0 as real part. This result makes no sense, I'm supposed to find an asymptotically critical point for (0,0)...

Edit: Nevermind, I made a mistake for A, I fall over the result in my first post again. Ok now I understand better. Thanks.
 
Last edited:

Related to Stability of 2 critical points in a system of DE's

1. What is the definition of a critical point in a system of differential equations (DEs)?

A critical point in a system of DEs is a point at which all of the derivatives of the variables are equal to zero. This means that the system is not changing at that point and the solution remains constant.

2. How do you determine the stability of a critical point in a system of DEs?

The stability of a critical point can be determined by analyzing the behavior of the solutions near the point. This can be done by linearizing the system of DEs and examining the eigenvalues of the resulting matrix. A critical point is stable if all of the eigenvalues have negative real parts, and unstable if any of the eigenvalues have positive real parts.

3. Can a critical point in a system of DEs be both stable and unstable?

No, a critical point can only be either stable or unstable. This is because the stability of a critical point is determined by the behavior of the solutions near that point, and the behavior cannot be both stable and unstable at the same time.

4. What are some real-world applications of analyzing the stability of critical points in a system of DEs?

The stability of critical points in a system of DEs is important in various fields such as physics, engineering, and biology. For example, in physics, analyzing the stability of critical points can help predict the behavior of a pendulum or a simple harmonic oscillator. In engineering, it can be used to design control systems for stable and efficient operation of machines. In biology, it can help understand the stability of ecological systems and population dynamics.

5. Are there any other methods for determining the stability of critical points in a system of DEs?

Yes, there are other methods such as using phase portraits, Lyapunov functions, and Poincaré-Bendixson theorem. These methods can provide more insights into the behavior of the system and its stability, but they are more complex and may require more computational resources.

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