基于神经网络模糊PID控制的无刷直流电机控制系统研究

针对电动汽车行驶工况的要求,为了使电机能够有良好的启动特性和稳态特性,在Simulink中建立了无刷直流电机转速-电流双闭环控制系统仿真模型,转速控制神经网络和模糊控制对PID控制参数进行在线整定;电流环采用电流滞环控制,并对控制模型进行空载启动后加载实验。实验结果表明,本文设计的控制系统响应速度快,无静差,抗干扰能力强。

Research on Brushless DC Motor Control System Based on Neural Network Fuzzy PID Control

In response to the requirements of electric vehicle driving conditions,in order to enable the motor to have good starting characteristics and steady-state characteristics,a brushless DC motor speed-current double closed-loop control system simulation model,speed control neural network and fuzzy control system are established in Simulink.The control performs online tuning of PID control parameters;the current loop adopts current hysteresis control,and the control model is loaded after no-load startup.The experimental results show that the control system designed in this paper has fast response speed,no static error,and strong anti-interference ability.