摘要
液压绞磨在铁塔组立施工中起重要作用,为此该文提出一种智能集成式轻小型落地抱杆的液压绞磨自动化控制方法。以实际牵引速度与期望牵引速度以及两者的偏差作为输入值,通过BP神经网络运算得出PID最优组合的控制参数,以实际牵引力和目标牵引力的偏差以及偏差变化率作为模糊控制的输入,通过模糊PID的计算,得到PID精确的更新参数;将两方面输出控制结果作用于执行器,进行液压绞磨参数调节,实现牵引速度和牵引力控制。实验结果表明,该方法控制的液压绞磨性能参数与目标参数吻合性高,动态性能平稳,在平衡方面控制效果也很显著。
Hydraulic grinding plays an important role in the erection of iron tower,so an intelligent integrated hydraulic grinding automatic control method of light and small landing pole holding is proposed.Taking the actual traction speed,the expected traction speed and the deviation of both as input values,the control parameters of the optimal PID combination are obtained through BP neural network operation.The deviation of the actual traction force and the target traction force and the deviation change rate are taken as the input of fuzzy control.The two output control results are applied to the actuator,the hydraulic grinding parameters are adjusted,and the traction speed and traction force are controlled.The results show that the performance parameters of the hydraulic grinding controlled by this method are in good agreement with the target parameters,the dynamic performance is stable,and the control effect is remarkable in terms of balance.
作者
邹麒
牛硕
刘帅
徐强
ZOU Qi;NIU Shuo;LIU Shuai;XU Qiang(Suqian Power Supply Company,State Grid Jiangsu Electric Power Co.,Ltd.,Suqian 223800,China)
出处
《自动化与仪表》
2024年第6期120-123,共4页
Automation & Instrumentation
基金
国网江苏省电力有限公司孵化项目(JF2022023)。
关键词
智能集成
落地抱杆
液压绞磨
自动化控制
BP神经网络
PID控制
intelligent integration
landing pole
hydraulic grinding
automatic control
BP neural network
PID control