Event-Triggered Decentralized Integral Sliding Mode Control for Input-Constrained Nonlinear Large-Scale Systems With Actuator Failures

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.

I. Introduction

In practical applications, many complex systems can be considered as large-scale (LS) systems, such as electrical power systems, mobile robots, and communication systems. The main feature of such systems lies in that they are composed of a set of low-dimensional interconnected subsystems. It is obvious that once a subsystem is affected by disturbances or actuator faults, its neighboring subsystems will also be affected through interconnections, thus the existing centralized control methods are not feasible to apply to LS systems [1]. To solve this problem, decentralized control strategy, which utilizes local states only, rather than overall system states, has drawn much attention [2]. Among existing decentralized control methods, the decentralized optimal control (DOC) problem which further improves the control performance is solved by constructing a set of appropriate performance index functions [3], [4]. The basic idea is to convert the decentralized control problem of LS systems into a set of optimal control (OC) problems of isolated systems, then, to solve algebraic Riccati equation or Hamilton–Jacobi–Bellman equation (HJBE) for the isolated linear systems or nonlinear systems, respectively.