LMIs in Control/pages/LMI for Schur Stabilization

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LMIs in Control/pages/LMI for Schur Stabilization

The System

We consider the following system:

x(k+1)=Ax(k)+Bu(k)

where xnandur, are the state vector and the input vector, respectively. Moreover, the state feedback control law is defined as follows:

u(k)=Kx(k)

Thus, the closed-loop system is given by:

x(k+1)=(A+BK)x(k)

The Data

Given matricesAn×n,Bn×r, and the scalar0<γ1.

The Optimization Problem

Find a matrix Kr×n such that,

||A+BK||2<γ

According to the definition of the spectral norms of matrices, this condition becomes equivalent to:

(A+BK)T(A+BK)<γ2I

One can use the Lemma 1.2 in [1] page 14, the aforementioned inequality can be converted into:

[γI(A+BK)(A+BK)TγI]<0

The LMI: LMI for Schur stabilization

Title and mathematical description of the LMI formulation.

minγ:s.t.[γI(A+BK)(A+BK)TγI]<0

Conclusion:

This problem is a special case of Intensive Disk Region Design (page 230 in [1]). This problem may not have a solution even when the system is stabilizable. In other words, once there exists a solution, the solution is robust in the sense that when there are parameter perturbations, the closed-loop system's eigenvalues are not easy to go outside of a circle region within the unit circle [1].

Implementation

A link to Matlab codes for this problem in the Github repository:

https://github.com/asalimil/LMI-for-Schur-Stability

LMI for Hurwitz stability

A list of references documenting and validating the LMI.

  • [1] - LMI in Control Systems Analysis, Design and Applications

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