Control of linear parameter-varying systems using dynamic parameter measurement

This paper extends existing results on a technique for gain-scheduled, L₂-gain control of linear parameter-varying (LPV) systems with bounded rates of variation. Specifically, it introduces the use of both memoryless and dynamic (i.e., filtered) parameter measurements when the parameters´ accelerations are bounded. Information from the filtered parameter signal can be used to reduce the conservatism of LPV controllers when the parameter variations are slow relative to their worst-case bounds; under such circumstances, the closed-loop performance is closer to that of H_∞-optimal point designs. The synthesis results are illustrated by a simulation example