Adaptive Robust Fuzzy Tracking Control for a Class of Nonlinear Systems

Abstract

The tracking control problem for a class of nonlinear systems with uncertain system function and uncertain gain function, which are the unstructured state-dependent (or non-repeatable) unknown nonlinear functions, is investigated in this paper. A fuzzy logic system is used to approximate the lumped non-repeatable state-dependent uncertain function, then the fuzzy system is used as the upper bound of uncertainty, and a novel of adaptive robust fuzzy tracking control (ARFTC), that can evaluate the bound parameter of uncertainty on line, is presented. For the proposed algorithm, there are two advantages: (1) the adaptive mechanism with one learning parameterization can be obtained by use of Lyapunov approach; (2) the possible controller singularity problem in some of the existing adaptive control schemes met with feedback linearization techniques can be removed. Finally, the proposed algorithm is verified through simulation.