Adaptive robust fuzzy control of nonlinear systems

The problem of controlling a class of uncertain nonlinear systems to follow a reference trajectory is addressed. Fuzzy logic systems (FLSs) are used to approximate the unknown dynamics. Based on the a priori information, a nominal control implemented by FLSs is designed first, then a signal to compensate for both structured and unstructured uncertainties arising from the approximation is synthesized based on the Lyapunov method. The uncertainty bounds needed in the robust fuzzy control are adaptively tuned online. Exponential tracking to the reference trajectory up to a ultimately bounded error is achieved.