Infinite horizon predictive control of constrained continuous-time linear systems (Q1571074)

A control law and an algorithm for receding horizon predictive control of constrained continuous-time linear systems is presented. Necessary and sufficient conditions characterizing all prediction classes are developed using basic results of input-output stability. The nominal stability of the receding horizon control law is ensured through the stable input and output predictions, and a guarantee of the feasibility of the related constrained infinite horizon optimization problem is obtained. The optimization is made tractable by restricting the input predictions to a finite-dimensional subset of the admissible class and by minimizing a continuous-time cost at a set of discrete instants. The chosen numerical example demonstrates the advantages of proposed algorithm over discrete-time predictive control laws.