RBF Control Research Based on Fuzzy Neural Model

Abstract

RBF controller based on fuzzy neural network model is given in this paper, which applies field data to model the control object, and then uses the model to adjust the parameters of gauss basis function in RBF controller, such as the central value, the width, and the weights from hidden layer to output layer. In addition, the controller is applied to control the bed temperature of CFB boilers. By comparison with the traditional PID controllers, the simulation result shows that the given controller has shorter response time and better tracking performance.