Linear matrix inequality-based solution for memory static output-feedback control of discrete-time linear systems affected by time-varying parameters

摘要

This article investigates the problem of designing static output-feedback controllers for linear parameter-varying (LPV) discrete-time systems through the enrichment of the system dynamics. For this purpose, the past values of the measured outputs are included in the control law. Differently from the previous methods from the literature addressing memory control, a locally convergent iterative procedure based on linear matrix inequalities is proposed to solve the problem. As the main novelty, the procedure deals with the control gains as optimization variables of the problem (no change of variables is necessary), addressing state- and output-feedback in the same way, and allowing to cope with magnitude or structural constraints (such as decentralization) without introducing extra conservativeness. Numerical examples illustrate the effectiveness of the method, providing in general less conservative stabilization results than the existing methods when dealing with LPV systems.