Relaxations of parameterized LMIs with control applications. (English) Zbl 0919.93028

Parameterized linear matrix inequalities (PLMI) are LMIs whose coefficients are functions of a parameter. LMIs are powerful tools in the analysis and synthesis of robust control problems. Unfortunately, parameterized LMIs are very hard to solve. In contrast, LMIs consist of convex constraints and can be solved by very efficient convex optimization interior-point methods with worst-case polynomial complexity. They offer more freedom and potential than the usual Riccati and Lyapunov tools and provide additional flexibility in control applications.
This paper deals with some effective relaxation techniques to replace PLMIs by a finite set of LMIs. The techniques and tools presented here are applied to Lyapunov-based stability and performance robustness analysis and to linear parameter-varying control. Illustrative examples are given. It is mentioned that the methods are also applicable to \(\mu\)-analysis.


93B40 Computational methods in systems theory (MSC2010)
93B35 Sensitivity (robustness)
15A39 Linear inequalities of matrices


LMI toolbox
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