摘要
串联机器人大规模应用于工业生产中,提高机器人精度成为一个重要课题。在串联机器人中,各构件通过刚性铰链串联,铰链间隙对机器人运动精度的影响不可忽略。由于间隙对机器人运动的影响具有较强非线性,较难利用解析方法获得其逆运动学模型。利用遗传算法改进的神经网络建立含间隙串联机器人的逆运动学模型,并利用其构成内模控制,实现对含间隙串联机器人的控制。仿真结果证明,该控制方法具有一定的控制效果。
Series robots are widely used in industrial production,so it is an important task to improve the accuracy of robots.In the series robot,the components are connected in series by rigid hinges,and the influence of hinge clearance on the motion accuracy of the robot cannot be ignored.As the influence of clearance on robot motion is nonlinear,it is difficult to obtain its inverse kinematics model by analytical method.The inverse kinematics model of the series robot with clearance was established by using the improved neural network of genetic algorithm,and the internal model control was constructed to realize the control of the series robot with clearance.The simulation results show that it has a certain control effect.
作者
陈婵媛
杨丽新
张德福
肖桂英
CHEN Chanyuan;YANG Lixin;ZHANG Defu;XIAO Guiying(School of Mechanical and Electrical Engineering,Guangzhou Institute of Science and Technology,Guangzhou Guangdong 510540,China;School of Mechanical&Automotive Engineering,South China University of Technology,Guangzhou Guangdong 510540,China)
出处
《机床与液压》
北大核心
2021年第9期34-40,50,共8页
Machine Tool & Hydraulics
基金
广东省普通高校青年创新人才项目(2020KQNCX135)。
关键词
串联机器人
间隙
误差控制
神经网络
仿真分析
Serial robot
Clearance
Error control
Neural network
Simulation analysis
