基于BP神经网络的电缆输送装置恒张力控制研究  

Research on Constant Tension Control of Cable Conveyor Based on BP Neural Network

作　　者：曹小华[1] 宋景祥 CAO Xiaohua;SONG Jingxiang(School of Logistics Engineering,Wuhan University of Technology,Wuhan 430063,China)

机构地区：[1]武汉理工大学物流工程学院,武汉430063

出　　处：《武汉理工大学学报（交通科学与工程版）》2021年第6期1190-1194,共5页Journal of Wuhan University of Technology（Transportation Science & Engineering）

基　　金：国家重点研发计划项目(2018YFC1407405)。

摘　　要：港口岸电电缆输送装置控制系统具有非线性、时滞性以及时变性等特点,且易受外界干扰,常规PID方法对电缆的恒张力控制效果不理想.针对这种情况,在建立电缆输送装置张力控制模型的基础上,提出了基于BP神经网络PID的电缆张力控制方法,以实现对岸电电缆的恒张力控制.结果表明,电缆张力控制系统采用BP神经网络PID控制算法相较于常规PID算法具有超调量小、响应速度快、控制精度高等优点,能够实现对电缆恒张力的有效控制,使电缆输送装置能够适应复杂的运行工况.The control system of port power cable transmission device has the characteristics of nonlinearity,time delay and time variation,and is vulnerable to external interference.The effect of constant tension control of cable by conventional PID method is not ideal.In view of this situation,on the basis of establishing the tension control model of cable conveying device,a cable tension control method based on BP neural network PID was proposed to realize the constant tension control of shore power cable.The results show that the cable tension control system using BP neural network PID control algorithm has the advantages of small overshoot,fast response speed and high control precision compared with conventional PID algorithm,which can effectively control the constant cable tension and enable the cable conveying device to adapt to complex operating conditions.

关 键 词：岸电 电缆输送装置 张力控制 BP神经网络 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]