Optimization of a fuzzy controller using neural network

This paper presents a strategy for optimization of a fuzzy logic controller based on a control scheme, which consists of a fuzzy logic controller and a conventional derivative controller. For this purpose, we first choose a set of membership functions regarding change-in-error e/spl dot/, which represent the feedback of velocity. Then we optimize them using neural network in self-organizing process. To demonstrate the effectiveness of the proposed method, we report a number of simulation results involving both step and tracking control of a nonlinear plant.<>