基于BP神经网络的直流电机PID控制系统研究

以直流电动机为控制对象,建立数学模型,并在传统PID的基础上结合神经网络算法,充分利用神经网络自学习功能,实现对PID参数的实时在线自整定.克服了PID控制参数难以确定和控制过程无法随环境等变化而自适应的缺点,体现了神经网络较好的智能性与较强的鲁棒性.利用Matlab软件进行仿真研究,结果表明神经网络PID较传统PID更精准,更具适应性,控制效果优越.

Research on DC Motor PID Control System Based on BP Neural Network

A mathematical model of DC motor as the controlled object is established;and then the neural network algorithms and PID control are conbimed.With the self-learning function of the neural network,the self-tunings for parameters of PID are realized.This method overcomes disadvantages of PID as parameters which are difficult to determine and control process which is hard to change self-adaptively,and embodying the better intelligence and robustness of the neural network.The simulation is researched by using Matlab software;and the results show that the neural network PID control is more accurate and adaptive than the traditional PID;and its effect is more superior.