LMIs in Control/pages/Quadratic Polytopic Hinf- Optimal State Feedback Control

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Quadratic Polytopic Full State Feedback Optimal H Control

For a system having polytopic uncertainties, Full State Feedback is a control technique that attempts to place the system's closed-loop system poles in specified locations based off of performance specifications given. H methods formulate this task as an optimization problem and attempt to minimize the H norm of the system.

The System

Consider System with following state-space representation.

x˙(t)=Ax(t)+B1q(t)+B2w(t)p(t)=C1x(t)+D11q(t)+D12w(t)z(t)=C2x(t)+D21q(t)+D22w(t)

where xm , qn , wg, Amxm, B1mxn, B2mxg, pp , C1pxm, D11pxn, D12pxg, zs, C2sxm, D21sxn , D22sxg for any t.

Add uncertainty to system matrices

A,B1,B2,C1,C2,D11,D12

New state-space representation

x˙(t)=(A+Ai)x(t)+(B1+Bi)q(t)+(B2+Bi)w(t)p(t)=(C1+Ci)x(t)+(D11+Di)q(t)+(D12+Di)w(t)z(t)=C2x(t)+D21q(t)+D22w(t)

The Optimization Problem:

Recall the closed-loop in state feedback is:
S(P,K)=

[A+B2FB1C1+D12FD11]

This problem can be formulated as H optimal state-feedback, where K is a controller gain matrix.

The LMI:

An LMI for Quadratic Polytopic H Optimal State-Feedback Control ||S(P(Δ),K(0,0,0,F))||Hγ
Y>0

[Y(A+Ai)T+(A+Ai)Y+ZT(B2+B1,i)T+(B2+B1,i)Z*T*T(B1+B1,i)TγI*T(C1+C1,i)Y+(D12+D12,i)Z(D11+D11,i)γI]<0


Conclusion:

The H Optimal State-Feedback Controller is recovered by F=ZY1
Controller will determine the bound γ on the H norm of the system.

Implementation:

https://github.com/JalpeshBhadra/LMI/tree/master

Full State Feedback Optimal H Controller

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