Robust Reliable Fuzzy Control for Uncertain Markovian Jump Singular Systems

This paper deals with the problem of robust reliable control for Markovian jump nonlinear singular systems with Wiener process via a fuzzy-control approach. The Takagi-Sugeno (T-S) fuzzy model is employed to represent a nonlinear singular system with norm-bounded parameter uncertainties and Markovian jump parameters. The objective is to design a state feedback fuzzy controller such that, for all admissible uncertainties as well as normal and different actuator failure cases, the resulting closed-loop system is robustly stochastically stable. Based on linear matrix inequality (LMI) techniques, stochastic Lyapunov function method is adopted to establish sufficient condition of existence and design method of robust reliable fuzzy controller in terms of stability theory for stochastic differential equations.