LMIs in Control/Click here to continue/Controller synthesis/Quadratic Polytopic Stabilization

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Revision as of 13:30, 11 December 2021 by imported>Margav06 (Created page with "A Quadratic Polytopic Stabilization Controller Synthesis can be done using this LMI, requiring the information about <math>A</math>,<math>\Delta_{A(t)} </math> ,<math>B</math> and <math>\Delta_{B(t)} </math> matrices. == '''The System''' == :<math> \begin{align} \dot x(t)&=Ax(t)+Bu(t),\\ x(0)&=x_0, \end{align}</math> where <math>x(t)\in \R^n</math>, <math>u(t)\in \R^m</math>, at any <math>t\in \R</math>. <br> The system consist of uncertainties of the following form :...")
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A Quadratic Polytopic Stabilization Controller Synthesis can be done using this LMI, requiring the information about A,ΔA(t) ,B and ΔB(t) matrices.

The System

x˙(t)=Ax(t)+Bu(t),x(0)=x0,

where x(t)n, u(t)m, 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 Optimization and LMI:LMI for Controller Synthesis using the theorem of Polytopic Quadratic Stability

There exists a K such that

x˙(t)=(A+ΔA+(B+ΔB)K)x(t)

is quadratically stable for (ΔA,ΔB)C0((A1,B2),...,(Ak,Bk)) if and only if there exists some P>0 and Z such that

(A+Ai)P+P(A+Ai)T+(B+Bi)Z+ZT(B+Bi)T<0fori=1,...k.

Conclusion:

The Controller gain matrix is extracted as K=ZP1
Note that here the controller doesn't depend on Δ

  • If you want K to depend on Δ , the problem is harder.
  • But this would require sensing Δ in real-time.


Implementation

This implementation requires Yalmip and Sedumi. https://github.com/JalpeshBhadra/LMI/blob/master/quadraticpolytopicstabilization.m

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