Robust adaptive fuzzy controller for nonlinear systems based on approximation errors

A stable adaptive fuzzy control method is proposed for single input and single output nonlinear systems. This method needs not the assumption that the state variables need full observability. And the state variables are estimated by designing an observer. These unknown nonlinearities are approximated by the fuzzy systems. The key assumption is that the approximation errors satisfy certain bounding conditions. The Lyapunov synthesis approach is used to analyse the fuzzy system to obtain the corresponding parameters adaptive laws. The overall control system guarantees that the tracking error converges into a small neighborhood of zero and that all signals involved are uniformly bounded. Simulation results show the validity and efficiency of the proposed method.