基于改进型BP神经网络的无刷直流电机调速系统的应用研究

针对无刷直流电动机的速度问题,提出了一种基于改进型BP神经网络的无刷直流电机调速系统,即利用改进型BP神经网络来优化PID控制器的比例,积分,微分系数。所采用的BP神经网络的学习算法为粒子群算法,可以有效克服标准BP算法一般所存在收敛速度慢、存在局部极小值等问题,从而可以实现对无刷直流电动机的高精度的速度控制。最后,建立了仿真系统,其结果表明该算法效果良好。

Research of Brushless DC Motor Speed-Adjustment System Based on an Improved BP Neural Networks

Aimed at the speed problem of brushless DC motor,the article put forward a DC motor speed-adjustment system based on an improved BP Neural Networks,it exploit improved BP Neural Networks to optimize the proportional,integral,derivative coefficient of PID Controller. The Learning algorithm of BP neural networks is Particle Swarm Optimization,it can overcome the shortcoming of standard BP algorithm,such as slowly converging and easily immerging in partial minimum,consequently it can carry out high precision s...