Fuzzy-approximator-based adaptive tracking controller design for a class of nonlinear system

This paper presents a novel adaptive tracking fuzzy control scheme for a class of nonlinear system. Takagi-Sugeno (T-S) fuzzy model is employed to approximate the unknown system function. Moreover, only one parameter is necessary to be tuned online such that the complexity of the controller is reduced dramatically. All the signals in the closed-loop system is shown to be ultimately uniformly bounded, and the tracking error converges to a small neighborhood. Smooth function are contained in the control law to avoid the use of saturation function. There is no need of exact knowledge of low bound or upper bound of control gain function. Finally, the effectiveness of the proposed scheme is verified through simulation results in inverted pendulum on a cart system.