吉林大学学报(信息科学版) ›› 2021, Vol. 39 ›› Issue (4): 389-396.

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基于迭代学习的三自由度机械臂轨迹跟踪控制

王 刚1 , 宋英杰1,2 , 唐武生2 , 赵 强1 , 周露露2 #br#   

  1. 1. 白城师范学院 机械与控制工程学院, 吉林 白城 137000; 2. 长春大学 机械与车辆工程学院, 长春 130022
  • 收稿日期:2020-08-24 出版日期:2021-07-24 发布日期:2021-07-26
  • 作者简介:王刚(1980— ), 男, 吉林榆树人, 白城师范学院教授, 博士, 硕士生导师, 主要从事图像与视频处理、 机器人与系统控制研究, (Tel)86-19904365656(E-mail)wgzh198081@ 163. com
  • 基金资助:
    吉林省教育厅科技研究基金资助项目(JJKH20210004KJ)

Trajectory Tracking Control of Three-Degree-of-Freedom Manipulator Based on Iterative Learning

WANG Gang1 , SONG Yingjie1,2 , TANG Wusheng2 , ZHAO Qiang1 , ZHOU Lulu2   

  1. 1. School of Mechanical and Control Engineering, Baicheng Normal University, Baicheng 137000, China; 2. School of Mechanical and Vehicle Engineering, Changchun University, Changchun 130022, China
  • Received:2020-08-24 Online:2021-07-24 Published:2021-07-26

摘要: 针对用于三自由度机械臂各关节末端轨迹跟踪控制的非线性系统在扰动存在的情况下跟踪效率较低的问题, 提出一种变增益迭代学习控制律。 利用拉格朗日法建立动力学方程, 设计三自由度机械臂结构的变增益迭代学习控制器并进行收敛性分析, 通过 Matlab 的 Simulink 仿真模块, 构建三自由度机械臂控制系统仿真图,进行闭环定常 PD(Proportion Differentiation)型和闭环变增益 PD 型迭代学习控制器的三自由度机械臂对比仿真试验。 仿真结果显示, 基于变增益迭代学习的三自由度机械臂在干扰的状态下, 能较短时间内收敛到期望轨迹。

关键词: 变增益迭代学习; , 拉格朗日法; , Simulink 仿真

Abstract: A variable gain iterative learning control law is proposed to solve the problem that the tracking efficiency of nonlinear 3-DOF(three-Degree-Of-Freedom) manipulator's trajectory tracking control system is low in the presence of disturbance. First, the Lagrangian method is used to establish the kinetic equation. Then, the variable gain iterative learning controller with three degrees of freedom manipulator structure is designed and its convergence is analyzed. Finally, through Matlab Simulink simulation module, the three-degree-of-freedom manipulator control system simulation diagram is constructed, and the comparative simulation test of closed-loop fixed constant and closed-loop variable gain PD(Proportion Differentiation) iterative learning control is carried out. Simulation results show that the three-degree-of-freedom manipulator based on variable gain iterative learning can converge to the desired trajectory in a short time in the presence of interference.

Key words: variable gain iterative learning, Lagrangian method, Simulink simulation

中图分类号: 

  • TP241