Experience Replay‐Based Dynamic Event‐Triggered Optimal Control for Nonlinear Switched Systems With State Constraints

ABSTRACT This paper proposes an optimal event‐triggered alternative control (ETAC) strategy for switched systems with state constraints. First, the optimal control problem with state constraints is transformed into an unconstrained OCP by incorporating a barrier function into the cost function. Meanwhile, a dynamic event‐triggering mechanism (ETM) is introduced to the controller to reduce communication burden and computation load. Then, to obtain the solutions of the optimal ETAC problems, the adaptive dynamic programming (ADP) method is utilized to solve the event‐triggered Hamilton‐Jacobi‐Bellman equations (HJBEs), and a single‐layer critic neural network (NN) is constructed to approximate the cost function. Moreover, the experience replay technique is introduced in the weight tuning law to relax the persistence of excitation (PE) condition. The stability analysis proves that both the system state and the weight vector converge to an uniformly ultimately bounded (UUB) area. Finally, we provide a simulation example to show the effectiveness of the proposed ETAC strategy.