System simplification through state space

AI Thread Summary
The discussion centers on the challenges of simplifying a non-linear system by separating its linear and non-linear components. The user successfully obtained the state space representation of the linear part using Matlab's linmod command but seeks clarity on deriving output from the state space matrices. There is a consensus that simplification through transfer functions is possible but may depend on specific assumptions about the system. The non-linear part, modeled by a variable capacitor, allows for a clear separation into linear and non-linear series systems. Overall, the focus is on reducing the linear system using state space methods for better analysis.
Guillem
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Hi guys!

I study Electrical Engineering and, don't-know-why, I don't know anything about state space. Now I'm working on a project where I have a non-linear system. The first task in the project is to separate the linear and the non-linear part of this system, and then obtain the state space for the linear part in order to "simplify" it (that is at least what I understood).

So... I obtained the state space of the system (using linmod command in Matlab, easy) but now I wonder how I'm supposed to get the output (of the linear system) from the space state matrices.

· Would it be a reduction/simplification if I use the transfer function?
· Or I misunderstood something and it's impossible to simplify the system by its space state representation?

Thank you very much.

Guillem
 
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How exactly is the problem worded? In general one cannot separate the linear part from the nonlinear part unless one is told to make certain assumptions.
 
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In this case is easy, because the nonlinear part is modeled by a variable capacitor. So, the whole system can be separates in two series system, the first one linear, and the second one the capacitor with nonlinear respone.
Once separates I've to focus on reduce, using the state space, the linear system
 
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