A novel approach to stability and stabilization of fuzzy sampled-data Markovian chaotic systems.

This paper studies the problems of stability and stabilization of a class of Markovian chaotic systems via fuzzy sampled-data control. Different from some existing results, the Markovian jumping with general uncertain transition rates is considered for such systems. A novel approach, i.e., input-delay-dependent vector approach, is proposed for the first time. Based on this approach, an input-delay-dependent Lyapunov–Krasovskii functional (LKF) with cubic function of input delay is successfully constructed, and the convex combination technique is used with ease to derive stability and stabilization criteria. Compared with some existing stability and stabilization criteria for chaotic systems, our results are not only less conservative but also with reduced calculation complexity. Finally, the superiorities of proposed results are illustrated by two numerical examples.