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.KeywordsFuzzy SystemTracking ErrorVersus Versus VersusVersus Versus Versus VersusUncertain SystemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.