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机械臂变长度误差跟踪迭代学习控制

陈强 陈凯杰 施卉辉 孙明轩

陈强, 陈凯杰, 施卉辉, 孙明轩. 机械臂变长度误差跟踪迭代学习控制. 自动化学报, 2023, 49(12): 2594−2604 doi: 10.16383/j.aas.c200701
引用本文: 陈强, 陈凯杰, 施卉辉, 孙明轩. 机械臂变长度误差跟踪迭代学习控制. 自动化学报, 2023, 49(12): 2594−2604 doi: 10.16383/j.aas.c200701
Chen Qiang, Chen Kai-Jie, Shi Hui-Hui, Sun Ming-Xuan. Error-tracking iterative learning control for robot manipulators with iteration varying lengths. Acta Automatica Sinica, 2023, 49(12): 2594−2604 doi: 10.16383/j.aas.c200701
Citation: Chen Qiang, Chen Kai-Jie, Shi Hui-Hui, Sun Ming-Xuan. Error-tracking iterative learning control for robot manipulators with iteration varying lengths. Acta Automatica Sinica, 2023, 49(12): 2594−2604 doi: 10.16383/j.aas.c200701

机械臂变长度误差跟踪迭代学习控制

doi: 10.16383/j.aas.c200701
基金项目: 国家自然科学基金(62222315, 61973274, 62073291), 教育部重点实验室开放项目基金(GDSC202010)资助
详细信息
    作者简介:

    陈强:浙江工业大学信息工程学院教授. 主要研究方向为自适应控制与学习控制. E-mail: sdnjchq@zjut.edu.cn

    陈凯杰:浙江工业大学信息工程学院硕士研究生. 主要研究方向为自适应控制与学习控制. E-mail: chenkaijie0528@163.com

    施卉辉:浙江工业大学信息工程学院博士研究生. 主要研究方向为自适应控制与学习控制. E-mail: shidemelei@163.com

    孙明轩:浙江工业大学信息工程学院教授. 主要研究方向为自适应控制与学习控制. 本文通信作者. E-mail: mxsun@zjut.edu.cn

Error-Tracking Iterative Learning Control for Robot Manipulators With Iteration Varying Lengths

Funds: Supported by National Natural Science Foundation of China (62222315, 61973274, 62073291) and Ministry of Education Key Laboratory Open Project Fund (GDSC202010)
More Information
    Author Bio:

    CHEN Qiang Professor at the College of Information Engineering, Zhejiang University of Technology. His research interest covers adaptive control and learning control

    CHEN Kai-Jie Master student at the College of Information Engineering, Zhejiang University of Technology. His research interest covers adaptive control and learning control

    SHI Hui-Hui Ph.D. candidate at the College of Information Engineering, Zhejiang University of Technology. Her research interest covers adaptive control and learning control

    SUN Ming-Xuan Professor at the College of Information Engineering, Zhejiang University of Technology. His research interest covers adaptive control and learning control. Corresponding author of this paper

  • 摘要: 针对任意初始状态下机械臂轨迹跟踪问题, 提出一种变长度误差跟踪迭代学习控制(Iterative learning control, ILC)方法. 首先, 构造不依赖于期望轨迹的双曲余弦型期望误差轨迹, 放宽经典迭代学习控制初始状态要求严格一致的条件. 由于该误差轨迹只需设置一个常数项, 因而能够有效减少计算量, 使得期望误差轨迹的设计更为简单. 其次, 考虑机械臂运行区间随迭代次数变化的问题, 构建虚拟误差变量补偿机制, 通过定义虚拟误差变量对未运行区间进行信息补偿, 放宽经典迭代学习控制的迭代长度不变条件. 在此基础上, 基于Lyapunov-like理论设计迭代学习控制器和全限幅学习律, 实现机械臂关节位置在指定区间上跟踪给定的期望轨迹和保证未知参数估计值的有界性. 最后, 仿真结果验证了所提方法的有效性.
  • 图  1  期望误差轨迹

    Fig.  1  Desired error trajectory

    图  2  状态修正轨迹

    Fig.  2  State rectifying trajectory

    图  3  关节位置$q_{11,k}$和期望位置信号$q_{d1}$

    Fig.  3  Joint position $q_{11,k}$ and desired position signal $q_{d1}$

    图  11  关节位置误差$\tilde q_{12,30}$收敛过程对比

    Fig.  11  The comparison of the error $\tilde q_{12,30}$ convergence processes

    图  4  关节位置$q_{12,k}$和期望位置信号$q_{d2}$

    Fig.  4  Joint position $q_{12,k}$ and desired position signal $q_{d2}$

    图  5  误差轨迹$\tilde q_{11,k}$ 和期望误差轨迹$\tilde q_{11,k}^*$

    Fig.  5  Error trajectory $\tilde q_{11,k}$ and desired error trajectory $\tilde q_{11,k}^*$

    图  6  误差轨迹$\tilde q_{12,k}$和期望误差轨迹$\tilde q_{12,k}^*$

    Fig.  6  Error trajectory $\tilde q_{12,k}$ and desired error trajectory $\tilde q_{12,k}^*$

    图  7  性能指标

    Fig.  7  Performance index

    图  8  关节位置$q_{11,k}$跟踪性能对比

    Fig.  8  The comparison of joint position $q_{11,k}$ tracking performance

    图  9  关节位置$q_{12,k}$跟踪性能对比

    Fig.  9  The comparison of joint position $q_{12,k}$ tracking performance

    图  10  关节位置误差$\tilde q_{11,30}$收敛过程对比

    Fig.  10  The comparison of the error $\tilde q_{11,30}$ convergence processes

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出版历程
  • 收稿日期:  2020-08-29
  • 录用日期:  2021-04-29
  • 网络出版日期:  2021-06-22
  • 刊出日期:  2023-12-27

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