基于神经元控制的桥式起重机吊重防摆系统

摘要

重物在吊运过程中由于存在惯性不可避免的产生摆动,传统减摆方法是当出现摆动后,靠负载自重使摆动幅度自然减弱后再继续操作,这样往往付出了降低工作效率的代价.为提高工作效率和减小作业风险,对桥式起重机吊重摆动问题进行研究,通过建立其Lagrange动力学微分方程,对吊重摆动规律和影响因素进行分析.同时,提出一种单神经元PID控制策略,分别对小车的位置和吊重的摆角进行控制,利用神经网络自学习功能克服传统PID控制参数无法在线整定的局限.分析结果表明,与传统方法相比,单神经元PID控制策略可有效实现小车精确定位和快速消除吊重摇摆,鲁棒性好,为实际应用提供理论依据.%In order to improve the working efficiency and reduce the operating risk,the crane swing problem is studied,and a Lagrange dynamic equation is established.At the same time,a single neuron PID control strategy is proposed to control the position of the car and the swing angle of the crane.The use of neural network can overcome the limitation of the traditional PID control that parameters cannot be adjusted online.The results show that compared with the traditional method,the single neuron PID control strategy can realize the precise positioning of the car and the rapid elimination of the swing of the crane,and provide a theoretical basis for the practical application.