Adaptive optimal control for linear discrete time-varying systems

Abstract

In this paper, adaptive optimal control is proposed for time-varying discrete linear system subject to unknown system dynamics. The idea of the method is a direct application of the Q-learning adaptive dynamic programming for time-varying system. In order to derive the optimal control policy, a actor-critic structure is constructed and time-varying least square method is adopted for parameter adaptation. It has shown that the derived control policy can robustly stabilize the time varying system and guarantee an optimal control performance at the same time. As no particular system information is required throughout the process, the proposed techniques provide a potential feasible solution to a large variety of control application. The validity of the proposed method is verified through simulation studies