Application of Fuzzy Neural Network Predictive Control in Material Proportioning System

In accordance with the technique features of material proportioning belt system in the cement production, e.g., inertia, time lag, non-linearity and frequent disturbance in work field, a fuzzy neural network predictive controller based on neural network prediction model is designed. By combining fuzzy control, neural network and predictive control, it can enhance self-studying, tracking and anti-interference capabilities of the algorithm, and the neural network can compensate with the limitation of conventional predictive control that based on linear model. With this algorithm the weigh belt is controlled, and the simulation experimental curves show that the control effect of the material flow is effective, and the precision of ingredient proportion has evidently improved