Synthesis of Low-Order Controllers for LPV Systems Using LMIs and Evolutionary Search

A procedure for designing robust and gain-scheduled controllers for linear parameter-varying (LPV) systems is proposed that exploits known bounds on the rate of parameter variation to reduce conservatism. Recent results on stability analysis of LPV systems with known bounds on the rate of parameter change, using the concept of quadratic separators have been extended to compute a measure of worst-case performance of an LPV system by solving an LMI problem. The problem of synthesizing robust and gain-scheduled controllers leads to a bilinear matrix inequality, and a hybrid approach to solving this problem based on LMI solvers and genetic algorithms is proposed in this paper. Two design examples illustrate the efficiency of the proposed method