Security control of T-S fuzzy systems with adaptive event-triggered and hybrid attacks

This study investigates the security control for Takagi–Sugeno (T-S) fuzzy systems subject to deception attacks, non-periodic Denial of Service (DoS) attacks, and external disturbances, utilizing an adaptive event-triggered control (AETC). First, a hybrid attack model is developed that comprehensively considers the effects of deception and DoS attacks on T-S fuzzy systems. Specifically, the DoS attacks employ a non-periodic attack strategy, which more realistically simulates the attack mode in actual networks. Second, an AETC is proposed to effectively mitigate the performance degradation and redundant data transmission caused by network attacks. This mechanism can dynamically adjust the triggering thresholds based on changes in system states, thus ensuring system performance while reducing communication frequency. Furthermore, the closed-loop system is modeled as a switched system with artificial state delays. A novel time-varying piecewise Lyapunov–Krasovskii functional (LKF) is constructed, incorporating a fuzzy membership function, an extended reciprocal convex inequality, and relaxed matrix techniques to derive the exponential stability and H ∞ performance of the system under attack conditions. Finally, the controller gain parameters are obtained by solving linear matrix inequalities (LMIs). Numerical simulations verify the effectiveness and robustness of the proposed method against various network attacks.