Robust Guaranteed Cost Sampled-Data Fuzzy Control for Uncertain Nonlinear Time-Delay Systems
针对带有参数不确定性和时滞的Takagi-Sugeno模糊系统，设计了一种鲁棒保性能采样数据模糊控制器，通过构造时间依赖的Lyapunov泛函将存在条件转化为线性矩阵不等式，并优化成本函数上界。
This paper presents a robust guaranteed cost sampled-data fuzzy control (GCSDFC) design for Takagi-Sugeno fuzzy systems with parametric uncertainties and time-delay. Initially, a robust guaranteed cost sampled-data fuzzy controller is developed to stabilize exponentially the closed-loop fuzzy system while providing an upper bound for the quadratic cost function. In order to make full information of the actual sampling pattern, a novel time-dependent Lyapunov functional is subsequently constructed to derive the condition for the existence of the proposed controller which is given in terms of linear matrix inequalities (LMIs). Then, to minimize the upper bound of the cost function, a suboptimal robust GCSDFC problem can be formed as an LMI optimization problem. Finally, two examples are given to illustrate the effectiveness of the proposed method.