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基于迭代最优阻抗的人机物理交互控制方法

刘微容 魏子丰 晋振兵 孟家豪 王星琨 张浩琛

刘微容,魏子丰,晋振兵,等. 基于迭代最优阻抗的人机物理交互控制方法[J]. 北京航空航天大学学报,2025,51(6):1843-1851 doi: 10.13700/j.bh.1001-5965.2023.0314
引用本文: 刘微容,魏子丰,晋振兵,等. 基于迭代最优阻抗的人机物理交互控制方法[J]. 北京航空航天大学学报,2025,51(6):1843-1851 doi: 10.13700/j.bh.1001-5965.2023.0314
LIU W R,WEI Z F,JIN Z B,et al. Human-robot physical interaction control method based on iterative optimal impedance[J]. Journal of Beijing University of Aeronautics and Astronautics,2025,51(6):1843-1851 (in Chinese) doi: 10.13700/j.bh.1001-5965.2023.0314
Citation: LIU W R,WEI Z F,JIN Z B,et al. Human-robot physical interaction control method based on iterative optimal impedance[J]. Journal of Beijing University of Aeronautics and Astronautics,2025,51(6):1843-1851 (in Chinese) doi: 10.13700/j.bh.1001-5965.2023.0314

基于迭代最优阻抗的人机物理交互控制方法

doi: 10.13700/j.bh.1001-5965.2023.0314
基金项目: 

国家自然科学基金(62261032);中央引导地方科技发展资金项目(25ZYJA026);甘肃省重点人才项目;甘肃省高等学校创新基金(2022A-021)

详细信息
    通讯作者:

    E-mail:liuwr@lut.edu.cn

  • 中图分类号: TP242

Human-robot physical interaction control method based on iterative optimal impedance

Funds: 

National Nature Science Foundation of China (62261032); Central Government Guiding Funds for Local Science and Technology Development Program (25ZYJA026); Key Talent Project of Gansu Province; Gansu Education Science and Technology Innovation Fund (2022A-021)

More Information
  • 摘要:

    为提高人机物理交互的准确性和柔顺性,实现最优交互性能,针对基于迭代学习的阻抗控制方法需要多次重复同一任务的问题,借鉴迭代最优控制无需系统矩阵信息即可优化代价函数确定系统最优控制输入的机制,提出了基于迭代最优阻抗的人机物理交互控制方法。方法采用双环控制结构。面向任务的外环设计了迭代最优阻抗控制器(IOIC),将求取最优阻抗参数的问题描述成线性二次型调节器问题,利用迭代最优控制,求取最优反馈增益,使包括轨迹跟踪误差和交互力在内的代价函数最小化;同时引入软辅助函数,避免参数突变可能带来的机器人抖动问题。面向机器人的内环设计了非奇异终端滑模轨迹跟踪控制器(NTSMTC),使机器人实际轨迹跟踪外环输出的阻抗轨迹,通过饱和函数消减控制律的抖振。仿真结果证明:所提方法在人机协作任务中,仅利用一次任务初始阶段的交互信息即可求得最优阻抗参数,使任务过程中的轨迹跟踪误差和交互人所消耗的力最小化。

     

  • 图 1  基于迭代最优阻抗的人机物理交互控制方法结构

    Figure 1.  Structure of human-robot physical interaction control method based on iterative optimal impedance

    图 2  软辅助函数曲线

    Figure 2.  Soft auxiliary function curves

    图 3  人机物理交互场景示意图

    Figure 3.  Human-robot physical interaction scenario

    图 4  期望轨迹和阻抗轨迹

    Figure 4.  Desired trajectory and impedance trajectory

    图 5  期望轨迹跟踪误差

    Figure 5.  Desired trajectory tracking error

    图 6  机器人与人的实际交互力

    Figure 6.  Actual interaction force between robots and humans

    图 7  期望轨迹跟踪误差加速度

    Figure 7.  Desired trajectory tracking error acceleration

    图 8  PK矩阵迭代过程

    Figure 8.  P and K matrix iteration

    图 9  关节空间中的阻抗轨迹和实际轨迹

    Figure 9.  Impedance trajectory and actual trajectory in joint space

    图 10  关节空间中的阻抗轨迹跟踪误差

    Figure 10.  Impedance trajectory tracking error in joint space

    图 11  关节控制力矩

    Figure 11.  Joint control torque

    表  1  二连杆机器人物理参数

    Table  1.   Physical parameters of two-link robot

    参数 数值
    连杆1长度${l_1}$/m $1.0$
    连杆2长度${l_2}$/m $ 1.0 $
    连杆1质量${m_1}$/kg $1.5$
    连杆2质量${m_2}$/kg $1.5$
    连杆1惯性张量${I_1}$/(${\text{kg}} \cdot {{\text{m}}^2}$) $5.0$
    连杆2惯性张量${I_2}$/(${\text{kg}} \cdot {{\text{m}}^2}$) $5.0$
    重力常数$g$/($ {\text{m}}\cdot{{\text{s}}^{-2}} $) $ 9.81 $
    下载: 导出CSV
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出版历程
  • 收稿日期:  2023-06-05
  • 录用日期:  2023-10-16
  • 网络出版日期:  2023-11-24
  • 整期出版日期:  2025-06-30

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