Robust Guaranteed Cost Sampled-Data Fuzzy Control for Uncertain Nonlinear Time-Delay Systems

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.