Event-Triggered Switching-Type Fault Detection and Isolation for Fuzzy Control Systems Under DoS Attacks

This article investigates the memory adaptive event-triggered fault detection and isolation (FDI) problem for nonlinear networked control systems under periodic denial-of-service (DoS) attacks, where the nonlinear systems are described by Takagi-Sugeno (T-S) fuzzy models with unknown membership functions. First, a novel event-triggered mechanism is proposed to save communication resources. The triggering threshold is adaptively adjusted by multiple previous sampled data, not only depending on the latest triggering data. Second, taking DoS attacks, and event-triggered mechanism into consideration, a switching state-feedback controller is established, and the exponential stability is derived. Meanwhile, the controller, and the event-triggered mechanism are simultaneously developed based on a piecewise Lyapunov function. Then, a set of switching T-S fuzzy observers are constructed to realize FDI under DoS attacks. Besides, a switching variable method is introduced to address the asynchronous premise variables problem caused by the event-triggered mechanism. Finally, simulation cases are given to demonstrate the validity, and merit of the proposed FDI scheme.