吊装机械臂末端吊具防摇控制的实验研究  

Experimental research on anti-sway control of hoisting manipulator end spreader

作　　者：卢凯 王挺[1,2] LU Kai;WANG Ting(State Key Laboratory of Robotics,Shenyang Institute of Automation(Chinese Academy of Sciences),Shenyang 110016,China;Institutes for Robotics and Intelligent Manufacturing,Chinese Academy of Sciences,Shenyang 110169,China;School of Mechanical Engineering and Automation,Northeastern University,Shenyang 110819,China)

机构地区：[1]中国科学院沈阳自动化研究所机器人学国家重点实验室,辽宁沈阳110016 [2]中国科学院机器人与智能制造创新研究院,辽宁沈阳110169 [3]东北大学机械工程与自动化学院,辽宁沈阳110819

出　　处：《机电工程》2022年第12期1776-1783,共8页Journal of Mechanical & Electrical Engineering

基　　金：国家自然科学基金联合基金项目(U20A20201)。

摘　　要：在起重机的吊装过程中,吊装机械臂吊重的摇摆会造成吊装装卸效率低下,同时也会带来极大的安全隐患,为此,以平面三连杆式吊装机械臂为例,对其运行过程中末端吊具的防摇问题进行了实验研究。首先,建立了平面三自由度机械臂的运动模型,推导了其末端的速度公式;然后,提出了一种常规PID与模糊神经网络相结合的控制方法,以此消减了吊载的摇摆;阐述了控制系统所采用的模糊神经网络控制器的结构和算法,运用BP算法的带动量因子调整参数和权值,提高了神经网络的学习速度;最后,在Simulink中对控制系统进行了仿真分析,并在某抓取机械臂实验平台上进行了实物防摇实验,对比分析了实验与仿真结果。研究结果表明:基于模糊神经网络控制的吊装机械臂防摇效果更好,能使吊具抓手定位精度更高;相对于常规PID控制,该方法超调量小,调节时间缩短了28.6%,吊具最大摆角降低了59.2%。Aiming at the low loading and unloading efficiency caused by the swing of the lifting load of the lifting manipulator and the great potential safety hazards,taking the plane three link lifting manipulator as an example,the experimental research on the running speed and motion attitude of the end of the manipulator was carried out.Firstly,the motion model of a planar three degree of freedom manipulator was established and its terminal velocity formula was derived.Then a control method combining conventional proportion-integral-derivative(PID)and fuzzy neural network was proposed to reduce the swing of suspended load.The structure and algorithm of the fuzzy neural network controller used in the control system were expounded.The driving factor of back propagation(BP)algorithm was used to adjust the parameters and weights,which improved the learning speed of neural network.Finally,the control system was simulated in Simulink and verified on the experimental platform of rescue grab manipulator.The experimental and simulation results were compared and analyzed.The research results show that the anti swing effect of the fuzzy neural network control method can make the positioning accuracy of the spreader gripper higher.Compared with the conventional PID control,this method has small overshoot,the adjustment time is accelerated by 28.6%,the maximum swing angle of the spreader is reduced by 59.2%,and the comprehensive control effect is ideal.

关 键 词：自行式起重机 平面三自由度机械臂 吊具防摇 模糊控制 神经网络 吊具抓手定位精度 

分 类 号：TH213[机械工程—机械制造及自动化]