LMIs in Control/pages/Quadratic Schur Stabilization

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LMI for Quadratic Schur Stabilization

A discrete-time system is said to be stable if all roots of its characteristic equation lie in the open unit disk. This provides a condition for the stability of discrete-time linear systems with polytopic uncertainties and a linear time-invariant system with this property is called a Schur stable system.


The System

Consider discrete time system

xk+1=Axk+Buk,

where xkn, ukm, at any t.
The system consist of uncertainties of the following form

ΔA(t)=A1δ1(t)+....+Akδk(t)ΔB(t)=B1δ1(t)+....+Bkδk(t)

where xm,un,Amxm and Bmxn

The Data

The matrices necessary for this LMI are A,ΔA(t)ieAi ,B and ΔB(t)ieBi

The LMI:

There exists some X > 0 and Z such that

[XAX+BZ(AX+BZ)TX]+[0AiX+BiZ(AiX+BiZ)T0]>0i=1,......,k

The Optimization Problem

The optimization problem is to 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

Using the Lemma 1.2 in LMI in Control Systems Analysis, Design and Applications (page 14), the aforementioned inequality can be converted into:

[γI(A+BK)(A+BK)TγI]<0

Conclusion:

The Controller gain matrix is extracted as F=ZX1
uk=Fxk

xk+1=Axk+Buk,=Axk+BFxk=(A+BF)xk

It follows that the trajectories of the closed-loop system (A+BK) are stable for any ΔC0(Δ1,...,Δk)

Implementation

https://github.com/JalpeshBhadra/LMI/blob/master/quadratic_schur_stabilization.m

Schur Complement
Schur Stabilization

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