Event-triggered constrained robust control for partly-unknown nonlinear systems via ADP

Abstract

This paper proposes a constrained robust control algorithm for some continuous nonlinear systems with partly-unknown dynamics using an adaptive dynamic programming (ADP) method based on event-triggered (ET) mechanism. First, the constrained robustness of partly-unknown systems problems can be transformed into event-triggered optimal control problems with a suitable value function. Second, the identifier network and the critic network are applied to approximate the partly-unknown system and the cost function, respectively. In addition, the stability proof of the closed-loop system is addressed by Lyapunov theory with an appropriate triggering condition and the uniformly ultimately boundedness (UUB) of the closed-loop system is proved under the event-triggered mechanism. Moreover, the simulation experiments results show the superiority of the event-triggered mechanism via adaptive dynamic programming. The optimal control pair are only updated at the aperiodic sampling times determined by the event triggering condition, which can greatly improve the efficiency of communication resource utilization and save computing storage space.