基于神经元网络PID整定的电液位置伺服系统

Electro-hydraulic Position Servo System Based on Neural Network PID Tuning

基于汽车疲劳试验机平台对转向机液压伺服系统进行研究,针对试验机运行过程中出现的控制精度不高、系统不稳定问题,设计了电液位置伺服系统。首先建立系统数学模型,推导相应的传递函数。接着利用Simulink软件对系统进行稳定分析,利用典型的PID参数整定策略对系统进行优化处理。最后采用神经元网络自学习算法,在simulink中设计单神经元PID自学习系统,对位置伺服系统进行参数优化整定。研究结果表明:采用单神经PID整定的电液位置伺服系统超调量比典型PID整定策略减少了90%以上,整定时间也缩短了一半以上。系统稳定性更强、精度更高,具有更好的鲁棒性。

This paper mainly studies the hydraulic servo system of steering gear based on the automobile fatigue testing machine of an enterprise as a platform.During the operation of the test machine,the control accuracy is not high and the system is unstable.According to the design requirements,the electro-hydraulic position servo system is designed at first.Then the stability of the system is analyzed by Simulink software,and the system is optimized by typical PID parameter tuning strategy.Finally,a single neuron PID self-learning system is designed in Simulink by using the self-learning algorithm of neuron network to optimize the parameters of the position servo system.The results show that the overshoot of electro-hydraulic position servo system tuned by single nerve PID is reduced by more than 90%and the setting time is shortened by more than half compared with the typical PID tuning strategy.The system has stronger stability,higher accuracy and stronger robustness.