Resilient Adaptive Event-Triggered Fuzzy Tracking Control and Filtering for Nonlinear Networked Systems Under Denial-of-Service Attacks

Abstract

This article addresses the event-triggered tracking control and filtering problem for Takagi–Sugeno fuzzy-approximation-based discrete-time nonlinear networked systems subject to the effect of denial-of-service attacks. First, the unreliability of the communication channel between the sensor and the actuator/filter is considered, and the packet loss caused by denial-of-service attacks is characterized by the binary Markov chain. Second, two novel resilient adaptive event-triggered mechanisms are proposed to resist the impact of denial-of-service attacks and discard unnecessary data packets, in which the dynamic threshold variable is designed to adjust the event-triggered condition adaptively. A problem caused by the event-triggered mechanism is that the controller or filter cannot receive the system mode signal during the trigger interval. To surmount this problem, this article designs an estimator to compensate for the unavailable system mode. Then, an adaptive event-triggered controller or filter related to the estimated mode is designed to track the desired signal. Under this framework, by constructing a membership-function-dependent Lyapunov function, the conservativeness of the stability criterion is relaxed. Finally, two examples are used to validate the applicability of the proposed approaches.