Event-Triggered Decentralized Integral Sliding Mode Control for Input-Constrained Nonlinear Large-Scale Systems With Actuator Failures
Shunchao Zhang, Bo Zhao, Derong Liu, Yongwei Zhang
Abstract
In this article, an event-triggered decentralized integral sliding mode control (ETDISMC) method is investigated for a class of input-constrained nonlinear large-scale systems with actuator failures based on adaptive dynamic programming (ADP). An integral sliding mode control method is developed to maintain the subsystem trajectories on the sliding mode surface, eliminate the effect of actuator failures, and obtain the sliding mode dynamics (SMDs). Then, the control problem is transformed into an optimal control (OC) problem for the nominal form of the SMDs by constructing a modified local value function. To obtain the event-triggered OC law, a critic-only structure is applied to approximate the local optimal value function of the nominal subsystem for solving the event-triggered Hamilton–Jacobi–Bellman equation. An event-triggered ADP control method is developed to decrease the updating frequency of the OC law and to reduce the computational burden. In addition, an experience replay-based weight updating policy is presented to relax the persistence of excitation condition. Furthermore, we prove that the developed method can guarantee the closed-loop system to be asymptotically stable by using Lyapunov’s direct method. Finally, a numerical example and a practical system are employed for simulation to demonstrate the effectiveness of the proposed ETDISMC scheme.