神经网络PID在电机调速中的应用

Application of Nerve Network and PID Controller in Speed Regulation

针对传统PID控制器参数不能随直流电机转速变化而适时整定的缺点,将常规PID控制器与具有自学习功能的神经网络相结合,提出了基于BP神经网络的PID控制算法。通过工控机与PLC之间的通信,实现用户自行开发的神经网络对PID参数的适时整定,其控制效果已经通过实验进行了充分验证,较传统参数固定式PID调速器具有更快的调节速度和更高的调节精度。

In allusion to the disadvantage that traditional PID controller parameter cant be adjusted timely,this paper introduces a PID control algorithm based on the BP network by melting the regular PID controller and the self-automatic learning nerve network. Through the communication between industrial control computer and PLC, the nerve network developed by users can adjust the PID controller parameter and achieve the function of regulating speed of electric motor with higher speed and less errors.