Fuzzy-Model-Based Nonfragile Guaranteed Cost Control of Nonlinear Markov Jump Systems

This paper investigates the problem of nonfragile guaranteed cost control for discrete-time Takagi–Sugeno fuzzy Markov jump systems with time-varying delays. With the help of the parallel distributed compensation, a nonfragile fuzzy controller is designed. Then via Lyapunov–Krasovskii functional approach, sufficient conditions are obtained ensuring that the resulting closed-loop system is asymptotically stable with an upper bound of the guaranteed cost index. The optimal upper bound of the guaranteed cost index and the controller gain can be achieved via the optimization technique. Finally, an example is presented to show the effectiveness of the proposed new design techniques.