Fuzzy-Model-Based Nonfragile Guaranteed Cost Control of Nonlinear Markov Jump Systems
针对离散时间Takagi-Sugeno模糊马尔可夫跳变系统，设计非脆弱模糊控制器，通过Lyapunov-Krasovskii方法得到闭环系统渐近稳定且保性能指标有上界的充分条件，并用优化技术求解最优上界和控制器增益。
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.