A Self-Organizing Fuzzy Controller Using Neural Networks
Wei Li, Zuowei Wu · 1994
Abstract This paper presents a self-organizing fuzzy logic control scheme based on neural networks, which consists of a traditional fuzzy logic (FL) controller and a conventional derivative (D) controller. Since membership functions regarding change-in-error ė represent the feedback of velocity they strongly affect transient behaviors of a system. In the proposed scheme, therefore, such membership functions are parameterized by the use of the cubic splines. Then, neural networks are adopted to optimize them 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.