Research on a Vibrating Mill Control System Based on a Fuzzy Neural Network

Vibrating mills play an important role in the field of preparation of ultrafine powder.The purpose of a vibrating mill load control system is to increase productivity and ensure the mill runs smoothly.In this paper,we first summarized prior knowledge of control rules on the basis of analysis after repeated experiments,and realized fuzzy automation taking advantage of fuzzy theory.Since fuzzy control systems not only over rely on experience but also lack a self-learning function,we design a fuzzy neural network control system (FNNC) in order to improve the control system self-learning function and adaptive capacity while working conditions change.We adjust and optimize network performance using a back propagation(BP) algorithm.Simulation results show the control system dynamic performance is significantly improved,overshoot reduced from 23% to 8% and rise time shortened 0.4 min.