基于BP神经网络PID控制的BLDCM调速系统

The speed servo system of BLDCM based on improved BP neural network PID controller

在分析无刷直流电机(BLDCM)数学模型的基础上,采用改进型BP神经网络与传统PID相结合作为速度控制器,应用于无刷直流电机调速系统中。在电机初始运行阶段采用传统PID控制,网络学习一段时间后,切换到经过改进的BP神经网络在线自整定PID控制。仿真研究表明,应用这种新型控制方式的无刷直流电机调速系统具有良好的动态性能和稳态精度。

Based on the mathematic model of BLDC motor, a combination of an improved BP neural network and a general PID controller is used in its speed servo system. The general PID controller is used in the beginning several seconds, and then another adaptive PID controller based on neural network is converted to after training for seconds. Simulation experiments demonstrate that this control method can improve the dynamical performance and enhance the static precision of the speed servo system.