Event-Triggered Adaptive Dynamic Programming Based Guaranteed Cost Tracking Controller for Uncertain Nonlinear Systems

This paper addresses the robust guaranteed cost tracking control problem of nonlinear matched uncertain systems using event-based adaptive dynamic programming (ADP). By constructing an augmented system and using a discounted cost function, the guaranteed cost control problem is transformed into an optimal control problem of the nominal augmented system. The ADP framework is utilized to approximate the solution of the Hamilton-Jacobi-Bellman (HJB) equation associated with the optimal control problem. The event-based guaranteed cost is derived, and its relation with the time-based one is discussed. Furthermore, it is proven that the derived event-based controller can make the tracking error uniformly ultimately bounded (UUB). The applicability of the suggested technique is exhibited using a simulation study.