Robust fuzzy control for a class of nonlinear systems with uncertainty

This paper considers the problem of controlling a class of nonlinear systems expressed in the canonical form to follow a reference trajectory in the presence of uncertainties. Fuzzy logic systems (FLSs) are used to approximate the unknown dynamics of the system. Based on the a priori information, the premise part of the FLS as well as a nominal weight matrix are designed first and are fixed. A signal to compensate the structured uncertainty arising from the weight matrix error and the unstructured uncertainty arising from the function reconstruction error is designed based on the Lyapunov analysis. By running online an estimator for each uncertainty bound the implementation of the proposed controller needs no a priori information on these bounds. Exponential tracking to the reference trajectory up to a uniformly and ultimately bounded error is achieved with the proposed control. The effectiveness of this control is demonstrated through simulation results. The results also show that by incorporating a priori informations about the system, the fuzzy logic control can result good tracking behavior using a few fuzzy IF-THEN rules.