Similarity transformation to get minimal realization

In summary, to find the transformation T for a minimal realization of system H, you can solve a set of linear equations using the values of A, B, C, L, and K.
  • #1
azizz
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I derived a LTI system H described in state space as

[tex] H=\left( \begin{array}{cc|c} A+BKC & -BLC & B \\ 0 & A & B \\ \hline KC & -LC & I \end{array} \right) [/tex]

system H is not of minimal realization, hence I should be able to find a similarity transformation T such that I get the minimal realization of H. MATLAB cofirms this for me when I just fill in some values for A, B, C, L, K and call the function minreal. I also found that the minimal realization of the system should be

[tex] H=\left( \begin{array}{cc} A+BKC & B \\ (K-L)C &I \end{array} \right) [/tex]

However, I cannot find the transformation T (matlab just gives me some numbers which I can not link to the original variables). So I need to find a T which satisfies

[tex] T^{-1} \begin{pmatrix} A+BKC & -BLC \\ 0 & A \end{pmatrix} T = \begin{pmatrix} A+BKC & 0 \\ 0 & X \end{pmatrix} [/tex]

[tex] T^{-1} \begin{pmatrix} B \\ B \end{pmatrix} = \begin{pmatrix} B \\ 0 \end{pmatrix} [/tex]

[tex] \begin{pmatrix} KC & -LC \end{pmatrix} T = \begin{pmatrix} (K-L)C & 0 \end{pmatrix} [/tex]

Where X can be anything.

Someone knows how I can find T?
 
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  • #2
You can find the transformation T by solving a set of linear equations. Consider the matrix equation in your first equation. You can rewrite it as A+BKC+T11=A+BKC and BLC+T12=0. This gives you two linear equations in two unknowns (T11 and T12). Similarly, you can consider the other two equations. Solving these four equations will give you the transformation matrix T.
 

1. What is a similarity transformation for minimal realization?

A similarity transformation is a mathematical operation that transforms a given system into a form that is minimally realized, meaning it has the fewest possible number of state variables. This is important in controlling the complexity of a system and simplifying its analysis.

2. How is a similarity transformation performed?

A similarity transformation is performed by finding a transformation matrix that maps the original system onto an equivalent system with minimal realization. This matrix is typically found by solving a set of linear equations.

3. What is the benefit of using similarity transformation for minimal realization?

The main benefit of using similarity transformation for minimal realization is that it simplifies the system and makes it easier to analyze and control. It reduces the number of state variables and therefore the complexity of the system, while maintaining its essential properties.

4. Can any system be transformed into a minimally realized form using similarity transformation?

No, not all systems can be transformed into minimally realized form using similarity transformation. The system must meet certain conditions, such as being controllable and observable, in order for the transformation to work.

5. Are there any limitations or drawbacks to using similarity transformation for minimal realization?

One limitation of similarity transformation is that it may not be able to fully reduce the complexity of a system, as some systems may have inherently high dimensionality. Additionally, the transformation may introduce numerical errors and round-off effects, which can affect the accuracy of the results.

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