A Novel Adaptive Fuzzy-Dependent Event-Triggered Control Strategy for Aperiodic Sampled-Data T-S Fuzzy Systems

This paper focuses on designing an improved adaptive event-triggered mechanism with a novel structure to further alleviate the communication and computation burden during the stabilization process of aperiodic sampled-data Takagi-Sugeno (T-S) fuzzy systems. First, the fuzzy-related information, including the structural characteristics of fuzzy subsystems and the values of fuzzy membership functions (FMFs), are involved in the construction of the proposed fuzzy-dependent adaptive event-triggered scheme (FDAETS) to overcome the limitation that all the fuzzy subsystems share the same adaptive event-triggered rules. Moreover, a looped-typed Lyapunov-Krasovskii functional (LTLKF) is proposed to reduce the design conservatism caused by ignoring the available features of the system state during the whole sampling interval. Consequently, the asymptotic stability criterion and the event-triggered controller design method can be achieved with ideal communication efficiency and extra flexibility. Finally, the effectiveness and superiority of the proposed control scheme are demonstrated via a simulation example.