Speed control of BLDCM Based on Compensated Fuzzy Neural Network
Aiming at the multivariable,nonlinearity,strong coupling,time-variable characteristics of speed control system of brushless DC motor(BLDCM),the CFNNC algorithm is proposed to obtain high precision speed controlling.This algorithm combines compensative fuzzy logic and neural network,adjust the input and output of fuzzy membership functions,and optimize the fuzzy inference dynamically according to the logic compensation algorithm.The fault tolerance,stability and working speed of the network are improved greatly due to the introduction of fuzzy neuron.The simulation and experiment results of DSP –based control system prove that this method have rapid response and robustness,and its dynamic characteristic is much better than that of traditional PID controller.
BLDCM CFNNC Position servo system Mathematical model DSP
Gu Deying Zhang Jinquan
School of Control Engineering,Northeastern University at Qinhuangdao,Qinhuangdao 066004
国际会议
长沙
英文
4541-4544
2014-05-31（万方平台首次上网日期，不代表论文的发表时间）