Control Subspace of LTI System X = Ax + Bu: Nonzero Parameter Analysis

  • Thread starter ayham87
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In summary, the conversation discusses a given LTI system and its parameters, and the task of determining if the system is completely controllable. It is suggested to use the ctrb function in MATLAB, but it is found that the function does not handle symbolics. The alternative solution is to manually find the controllability using loops and other functions in MATLAB.
  • #1
ayham87
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Homework Statement



Given the LTI system X =Ax+Bu where

A =[ 0 1 0 0 0 0; a1 0 0 a2 0 0;0 0 0 1 0 0;0 a3 0 0 0 0; 0 0 0 0 0 1;0 0 0 0 a4 0];
B = [0 0 0 ;b1 0 0 ; 0 0 0 ;0 b2 0 ;0 0 0 ;0 0 b2];


and the parameters a1; a2; a3; a4; b1; b2 are all nonzero. Determine whether the system is completely controllable. If not, find the controllable subspace of the state space.






The Attempt at a Solution



I tried systematically but it seems to long so i try by MATLAB by the following code

syms a1 a2 a3 a4 b1 b2
A =[ 0 1 0 0 0 0; a1 0 0 a2 0 0;0 0 0 1 0 0;0 a3 0 0 0 0; 0 0 0 0 0 1;0 0 0 0 a4 0];
B = [0 0 0 ;b1 0 0 ; 0 0 0 ;0 b2 0 ;0 0 0 ;0 0 b2];

Co = ctrb(A,B)


Thanks in advanced
 
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  • #2
The variables A and B need not be symbolic variables. Just declare A and B as double floats and use ctrb function. It worked for me.
 
  • #3
Thanks for your response

actually "syms" not for A & B, its for the variables (a1 a2 b1 b2 a3 a4), I declare A & B as double float :

syms a1 b1 a2 a3 a4 b2
A =[ 0 1 0 0 0 0; a1 0 0 a2 0 0;0 0 0 1 0 0;0 a3 0 0 0 0; 0 0 0 0 0 1;0 0 0 0 a4 0];
B = [0 0 0 ;b1 0 0 ; 0 0 0 ;0 b2 0 ;0 0 0 ;0 0 b2];
A = float('double');
B = float('double');
Co = ctrb(A,B);


but i get the following error:

The following error occurred converting from struct to double:
Error using ==> double
Conversion to double from struct is not possible.

Error in ==> ctrb at 32
co(:,1:nu) = b;


can u help me again...thanks in advanced
 
  • #4
the ctrb function doesn't handle symbolics. Just do the steps to find out controllability "by hand" via matlab. Its not that long, I've done it already, just create a few loops and such. I can provide the code I used to do it before I figured out MATLAB had the functionality, if you'd like.
 
  • #5
for your response!

Based on the given system, the controllability matrix Co has a rank of 6, which is equal to the dimension of the state space. This indicates that the system is completely controllable. The nonzero parameters do not affect the controllability of the system.
 

1. What is a control subspace in an LTI system?

A control subspace in an LTI (linear time-invariant) system is the set of all possible inputs that can be applied to the system to produce a desired output. It is a subset of the entire input space and is determined by the system's dynamics and constraints.

2. How is the control subspace related to the system matrix A and input matrix B?

The control subspace is closely related to the system matrix A and input matrix B. The system matrix A determines the dynamics and stability of the system, while the input matrix B determines the controllability of the system. The control subspace is the intersection of the range of B and the reachable subspace, which is determined by the system matrix A.

3. What is nonzero parameter analysis in the context of control subspace?

Nonzero parameter analysis in control subspace refers to the study of how the control subspace changes when one or more parameters in the system are varied. This analysis is important for understanding how the system responds to changes in its parameters and can be used to design robust control strategies.

4. How is the control subspace affected by nonzero parameters in the LTI system?

The control subspace can be affected by nonzero parameters in different ways. In some cases, varying a parameter may not have any effect on the control subspace, while in other cases it may significantly change the size and shape of the control subspace. The extent of the effect depends on the specific parameters and the dynamics of the system.

5. How can nonzero parameter analysis be used in practical applications?

Nonzero parameter analysis is a useful tool for designing control strategies for LTI systems in practical applications. By understanding how the control subspace changes with different parameters, engineers can design robust control systems that can adapt to changes in the system. This analysis can also be used to optimize the system parameters for better performance and stability.

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