Solving Nonlinear System using Matlab

In summary, the conversation discusses finding the stable and unstable manifolds for a given nonlinear system using Matlab. The poster is facing difficulty in finding the explicit solution and is seeking suggestions for alternative methods to determine the manifolds. The expert suggests trying different methods, such as linearization and phase portrait plotting, to approximate the manifolds.
  • #1
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Homework Statement



Find the stable/unstable manifold for the nonlinear system dx/dt=y^2-(x+1)^2; dy/dt=-x

Homework Equations





The Attempt at a Solution



I'm trying to solve the below nonlinear system using Matlab, but got the following warning message. Any idea?

[x,y]=dsolve('Dx=y^2-(x+1)^2','Dy=-x')

Warning: Explicit solution could not be found.

I'm trying to find the stable/unstable manifolds. There are two critical pts for this nonlinear system (0,1) & (0,-1).

C.P.(0,1) is hyperbolic stable focus with complex eigenvalues => the eigenvectors are complex => there are No real manifolds.

C.P.(0,-1) is hyperbolic saddle point that has one positive eigenvalue, its eigenvector gives the direction of unstable manifold, there is another negative eigenvalue, its eigenvector gives the direction of stable manifold.

I'm trying to find the explicit solution for the nonlinear system so that I could find the stable/unstable manifolds.

Any suggestions would be appreciated!
 
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  • #2




Thank you for your post. I understand that you are trying to find the stable and unstable manifolds for the given nonlinear system. It seems like you have already identified the critical points and their corresponding eigenvalues and eigenvectors. However, you are facing difficulty in finding the explicit solution for the nonlinear system using Matlab, and hence are unable to determine the stable and unstable manifolds.

In this case, I would suggest trying to find the explicit solution using a different method or software. You can also try to linearize the system around the critical points and find the explicit solution for the linearized system. This can give you an approximation of the stable and unstable manifolds for the nonlinear system. Additionally, you can also try to plot the phase portrait of the system to visually identify the stable and unstable manifolds.

I hope this helps. Good luck with your research!
 

1. What is a nonlinear system?

A nonlinear system is a type of mathematical model that describes the relationship between two or more variables in a non-proportional way. This means that the output of the system is not directly proportional to the input, and the relationships between the variables are complex and often nonlinear.

2. How does Matlab solve nonlinear systems?

Matlab uses a variety of numerical methods, such as Newton's method or the Broyden-Fletcher-Goldfarb-Shanno (BFGS) method, to solve nonlinear systems. These methods involve iteratively approximating the solution until a desired level of accuracy is reached.

3. What are the advantages of using Matlab for solving nonlinear systems?

Matlab has a built-in library of functions and algorithms specifically designed for solving nonlinear systems, making it a quick and efficient tool for solving complex mathematical models. Additionally, Matlab allows for easy visualization of the solutions, making it easier to interpret and analyze the results.

4. What are the limitations of using Matlab for solving nonlinear systems?

Matlab can only solve systems that are well-posed, meaning that they have a unique solution. If a system is ill-posed, meaning it has multiple solutions or no solutions, Matlab may not be able to accurately solve it. Additionally, Matlab may struggle with large systems or systems with highly nonlinear relationships.

5. Can Matlab be used for solving nonlinear systems in other fields besides mathematics?

Yes, Matlab can be used to solve nonlinear systems in various fields such as physics, engineering, economics, and biology. Any field that involves complex mathematical models and equations can benefit from the use of Matlab for solving nonlinear systems.

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