Adaptive optimal control of switched linear systems with input constraints

Abstract

In this paper, an adaptive optimal control scheme is proposed for a class of switched linear systems with input constraints and unknown dynamics. Firstly, in the case that the system dynamics is known, the optimal controller and optimal switching condition are determined by introducing a non-quadratic cost function and employing the embedding transformation technique. After that, an adaptive algorithm is established for estimating the unknown dynamics of the switched linear systems. Then, when the system dynamics is unknown, the adaptive optimal controller and optimal switching condition are deduced by resorting to the certainty equivalent principle. A common Lyapunov function is constructed, by using which, it is proved that the closed-loop system is globally uniformly asymptotically stable. Simulations are finally conducted to further illustrate the effectiveness of the proposed method.