Improved Sampled-Data Controller Design for T–S Fuzzy Systems with an Adaptive Event-Triggered Mechanism

This paper investigates the problem of stability and stabilization for Takagi–Sugeno (T–S) fuzzy systems with adaptive event-triggered scheme (AETS) based on sampled-data control. AETS is used to relieve network congestion and save bandwidth resources. A novel Lyapunov–Krosovskii functional (LKF) is proposed by introducing the available information of fuzzy membership functions (FMFs) and sampling instant. The FMFs approach, extended reciprocal convex inequality technique and some slack matrices are fully utilized to deal with the derivative of the LKF. Then, an improved criterion with less conservatism is obtained to guarantee the stability of T–S fuzzy system. Moreover, the standard conditions are given in the form of linear matrix inequalities by the matrix decoupling technique. Finally, the feasibility and effectiveness of the proposed method can be demonstrated through a numerical simulation.