LMIs in Control/Matrix and LMI Properties and Tools/Congruence Transformation

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LMIs in Control/Matrix and LMI Properties and Tools/Congruence Transformation


This methods uses change of variable and some matrix properties to transform Bilinear Matrix Inequalities to Linear Matrix Inequalities. This method preserves the definiteness of the matrices that undergo the transformation.

Theorem

Consider Q𝕊n,Wn×n, where rank(W)=n. The matrix inequality Q<0 is satisfied if and only if WQWT<0 or equivalently, WTQW<0.

Example

Consider An×n,Bn×m,Km×p,CTn×p,P𝕊n and V𝕊p, where P>0 and V>0. The matrix inequality given by


 Q=[ ATP+PAPBK+CTV *2V] <0,


is linear in variable V and bilinear in the variable pair (P.K). Choose the matrix diag(P1,V1) to obtain the equivalent BMI given by


 WQWT=[ P1AT+AP1BKV1+P1CT *2V1] <0,


Using a change of variable X=P1,U=V1 and F=KV1, the above equation becomes

 WQWT=[ XAT+AXBF+XCT *2U] <0,


which is an LMI of variables X,U and F. The original variable K is recovered by doing a reverse change of variable K=FU1.

Conclusion

A congruence transformation preserves the definiteness of a matrix by ensuring that Q<0 and WTQW<0 are equivalent. A congruence transformation is related, but not equivalent to a similarity transformation TQT1, which preserves not only the definiteness, but also the eigenvalues of a matrix. A congruence transformation is equivalent to a similarity transformation in the special case when WT=W1.

A list of references documenting and validating the LMI.


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