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To study the design problem of robust reliable guaranteed cost controller for nonlinear singular stochas-tic systems,the Takagi-Sugeno (T-S) fuzzy model is used to represent a nonlinear singular stochastic system with norm-bounded parameter uncertainties and time delay.Based on the linear matrix inequality (LMI) techniques and stability theory of stochastic differential equations,a stochastic Lyapunov function method is adopted to design a state feedback fuzzy controller.The resulting closed-loop fuzzy system is robustly reliable stochastically stable,and the corresponding quadratic cost function is guaranteed to be no more than a certain upper bound for all admissible uncertainties,as well as different actuator fault cases.A suffcient condition of existence and design method of robust reliable guaranteed cost controller is presented.Finally,a numerical simulation is given to illustrate the effectiveness of the proposed method.
To study the design problem of robust reliable cost controller for nonlinear singular stochastic-tic systems, the Takagi-Sugeno (TS) fuzzy model is used to represent a nonlinear singular stochastic system with norm-bounded parameter uncertainties and time delay. linear matrix inequality (LMI) techniques and stability theory of stochastic differential equations, a stochastic Lyapunov function method is adopted to design a state feedback fuzzy controller. The resulting closed-loop fuzzy system is robustly reliable stochastically stable, and the corresponding quadratic cost function is guaranteed to be no more than certain certain bound for all admissible uncertainties, as well as different actuator fault cases. A suffcient condition of existence and design method of robust reliable guaranteed cost controller is presented. Finally, a numerical simulation is given to illustrate the effectiveness of the proposed method.