中国机械工程

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SCARA机器人的自适应迭代学习轨迹跟踪控制

张铁1;李昌达1;覃彬彬1;刘晓刚2   

  1. 1.华南理工大学 机械与汽车工程学院,广州,510000
    2.桂林航天工业学院,桂林,541004
  • 出版日期:2018-07-25 发布日期:2018-07-27
  • 基金资助:
    国家科技重大专项(2015ZX04005006);
    广东省科技重大专项(2014B090921004,2015B010918002);
    广州市科技重大项目(201604040009)
    National Science and Technology Major Project (No. 2015ZX04005006)
    Guangdong Provincial Science and Technology Major Project (No. 2014B090921004,2015B010918002)

Adaptive Iterative Learning Control of Trajectory Tracking of SCARA Robots

ZHANG Tie1;LI Changda1;QIN Binbin1;LIU Xiaogang2   

  1. 1.School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou,510000
    2.Guilin University of Aerospace Technology,Guilin,Guangxi,541004
  • Online:2018-07-25 Published:2018-07-27
  • Supported by:
    National Science and Technology Major Project (No. 2015ZX04005006)
    Guangdong Provincial Science and Technology Major Project (No. 2014B090921004,2015B010918002)

摘要: 为了减小执行重复运动任务机器人的末端位置误差,提出了自适应迭代学习轨迹跟踪控制算法。根据拉格朗日方程得到SCARA机器人的动力学模型,设计了控制力矩的迭代算法,利用Lyapunov函数对该算法的稳定性进行了理论证明,搭建了具有典型机械结构的SCARA机器人实验平台。通过实验验证了自适应迭代学习控制算法能有效减小SCARA机器人的末端位置误差,具有较强的可执行性。

关键词: 机器人, 自适应控制, 迭代, 轨迹

Abstract: In order to reduce the end position errors of robots performing repetitive motion tasks,an adaptive iterative learning control algorithm of trajectory tracking was proposed.The dynamics model of SCARA robot was obtained through Lagrange equation,and the iterative algorithm of control torque was designed.The stability of the algorithm was proved by Lyapunov function.An experimental platform of SCARA robot with typical mechanical structure was built.The experimental results show that the adaptive iterative learning control algorithm effectively reduce the end position errors of the SCARA robot to 1.61% of the original one with strong performability.

Key words: robot, adaptive control, iteration, trajectory

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