基于神经网络PID控制的注塑机压力控制系统

Pressure control system in injection molding machine based on neural network PID

设计了一种基于神经网络比例积分微分(PID)控制的伺服驱动液压注塑机压力恒定控制系统。通过径向基函数(RBF)神经网络实现PID参数的自适应在线调整,使PID控制效果达到最优,并进行了仿真分析。结果表明:与传统PID控制算法相比,RBF神经网络PID控制算法具有超调量小,响应速度快及自适应能力强等优点,能够满足伺服驱动液压注塑机控制系统的要求。

A pressure constant control system used for servo-driven hydraulic injection machine based on neural network proportional-integral-differential(PID)was designed.Radical basis function(RBF)neural network was used to realize the adaptive online adjustment of the PID parameters,so that the PID control effect can be optimized.The simulation analysis was carried out at last.The results show that the RBF neural network PID control algorithm has the advantages of small overshoot,fast response speed and strong adaptiveness energy compared with the traditional PID control algorithm,meeting the requirements of control system in servo-driven hydraulic injection machine.