LMIs in Control/pages/SSFP

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LMIs in Control/pages/SSFP
We are attempting to stabilizing The Static State-Feedback Problem

The System

Consider a continuous time Linear Time invariant system

x˙(t)=Ax(t)+Bu(t)

The Data

A,B are known matrices

The Optimization Problem

The Problem's main aim is to find a feedback matrix such that the system

x˙(t)=Ax(t)+Bu(t)

and

u(t)=Kx(t)


is stable Initially we find the K matrix such that (A+BK) is Hurwitz.

The LMI: Static State Feedback Problem

This problem can now be formulated into an LMI as Problem 1:

X(A+BK)+(A+BK)TX<0

From the above equation X>0 and we have to find K

The problem as we can see is bilinear in K,X

  • The bilinear in X and K is a common paradigm
  • Bilinear optimization is not Convex. To Convexify the problem, we use a change of variables.

Problem 2:

AP+BZ+PAT+ZTBT<0

where P>0 and we find Z
K=ZP1

The Problem 1 is equivalent to Problem 2

Conclusion

If the (A,B) are controllable, We can obtain a controller matrix that stabilizes the system.

Implementation

A link to the Matlab code for a simple implementation of this problem in the Github repository:

https://github.com/yashgvd/ygovada

Hurwitz Stability

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