Improved sampled-data controller design for T-S fuzzy systems with an
adaptive event-triggered mechanism
Abstract
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.