下肢外骨骼机器人动力学参数辨识与步态跟踪

刘洋; 彭世国; 马宏志; 廖维新

doi:10.12052/gdutxb.220014

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下肢外骨骼机器人动力学参数辨识与步态跟踪

综合研究 | 更新时间：2026-05-27

- 下肢外骨骼机器人动力学参数辨识与步态跟踪
- Dynamic Parameter Identification and Gait Tracking of Lower Limb Exoskeleton Robot
- 广东工业大学学报 2022年39卷第6期页码：44-52
- 作者机构：
  
  1. 广东工业大学自动化学院,广东,广州,510006
  2. 香港中文大学机械与自动化系,香港,999077
- 作者简介：
  
  刘洋(1980–) ，男，讲师，博士研究生，主要研究方向为外骨骼机器人控制，E-mail：ly1705@sina.com
- 基金信息：
  
  国家自然科学基金资助项目(61976059);香港特别行政区研究项目(14201615);校企合作项目(21HK0259)
- DOI：10.12052/gdutxb.220014
  中图分类号： TP242
- 纸质出版：2022
- 稿件说明：
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刘洋, 彭世国, 马宏志, 廖维新. 下肢外骨骼机器人动力学参数辨识与步态跟踪[J]. 广东工业大学学报, 2022, 39(6): 44-52.

Liu Yang, Peng Shi-guo, Ma Hong-zhi, et al. Dynamic Parameter Identification and Gait Tracking of Lower Limb Exoskeleton Robot[J]. 2022, 39(6): 44-52.
刘洋, 彭世国, 马宏志, 廖维新. 下肢外骨骼机器人动力学参数辨识与步态跟踪[J]. 广东工业大学学报, 2022, 39(6): 44-52. DOI： 10.12052/gdutxb.220014.

Liu Yang, Peng Shi-guo, Ma Hong-zhi, et al. Dynamic Parameter Identification and Gait Tracking of Lower Limb Exoskeleton Robot[J]. 2022, 39(6): 44-52. DOI： 10.12052/gdutxb.220014.

摘要

为了提高下肢外骨骼机器人步态轨迹跟踪的精度，对于下肢外骨骼二连杆动力学模型，提出一种静态与动态结合的参数辨识的实验方法，并结合穿戴者人体参数，得到人机协同系统精确的动力学模型。采用基于模型上界的滑模控制，并引入低通滤波器，进行MATLAB步态跟踪仿真。经仿真表明，髋关节和膝关节转矩的实验测量值与理论计算值的波形基本一致，动力学参数辨识结果正确；基于滑模控制的人机协同系统能够实现髋关节和膝关节对参考步态轨迹的精准跟踪，低通滤波器能够有效减小滑模控制引起的高频抖振。这为下肢外骨骼动力学参数辨识提供了一种解决方案，为基于模型的控制方法提供了一种参考模型，为下肢外骨骼人机协同系统的步态轨迹精准跟踪提供了一种参考方法。

Abstract

To improve the tracking accuracy of the gait trajectory of the lower limb exoskeleton robot (LLER)

an experimental method of parameter identification is proposed for the LLER’s two-link dynamic model

including static and dynamic experiment. Combined with the wearer’s human parameters

the accurate dynamic model of the LLER human-machine collaborative system is deduced. The sliding mode control (SMC) with the upper bound of the model and a low-pass filter are adopted to track the gait trajectory precisely by MATLAB. The simulation shows that the waveforms of the hip and knee torques measured by experiment are basically consistent with the theoretical values by calculation

and the dynamic parameter identification results are correct. The human-machine collaborative system based on SMC can realize the accurate tracking of the reference gait trajectories of the hip and knee joints

and the low-pass filter can effectively reduce the high-frequency chattering caused by SMC. This research provides a solution for the identification of the dynamic parameters of LLER

a reference model for the model-based control method

and a reference method for precisely tracking the gait trajectory of LLER human-machine collaborative system

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Keywords

references

CHENG H, HUANG R, QIU J, et al . A survey of rehabilitation robot and its clinical applications [J ] . Robot, 2021, 43(5): 606-619.

HUO J Y, YU H L, WANG F, et al . Research of a wearable lower extremity assisted exoskeleton robot system [J ] . China Journal Rehabilitation Theory Practice, 2019, 25(4): 481-486.

WANG D, HUANG R Y, LI W Z, et al . A research on docking position optimization method of mobile robot for grasping task [J ] . Journal of Guangdong University of Technology, 2021, 38(6): 53-61.

XU J M, ZHAO S. Research on dynamic parameter identification and adaptive control method of industrial robot [J]. Journal of Zhejiang University of Technology, 2020, 48(4): 375-383.

SUN C G, MA X F, TAN J L. The calculation of robot manipulator interal parameter [J]. Robot, 1990, 12(2): 19-24.

WANG S X, ZHANG H G, HUANG T Q, et al . Research on dynamic parameter identification of robots [J ] . Transactions of mechanical Engnieering, 1999, 35(1): 23-26.

ZHONG K Q, LUC B, LIONEL B. A new approach to the dynamic parameter identification of robotic manipulators [J]. Robotica, 2010, 28: 539-547.

SWEVERS J, VERDONCK W, SCHUTTER J D. Dynamic model identification for industrial robots [J]. IEEE Control Systems Magazine, 2007, 27(5): 58-71.

DING Y D, CHEN B, WU H T, et al . An identification method of industrial robot’s dynamic parameters [J ] . Journal of South China University of Technology (Natural Science Edition), 2015, 43(3): 50-56.

WANG J S, LIU X F, DUAN L C, et al . Dynamic modeling and parameter identification of a space robot considering joint friction [J ] . Chinese Quarterly of Mechanics, 2015, 36(4): 594-601.

XI W Q, CHEN B, DING L, et al . Dynamic parameter identification for robot manipulators with nonlinear friction model [J ] . Transactions of the Chinese Society for Agricultural Machinery, 2017, 48((2): 393-399.

耿令波. 工业机器人动力学参数辨识方法研究[D]. 南京: 南京航空航天大学, 2013.

GAUTIER M, POINGNET P. Extended Kalman filtering and weighted least squares dynamic identification of robot [J]. Control Engineering Practice, 2001, 9(12): 1361-1372.

CHEN Y D, HU L X. Identification method of payload dynamic parameters of industrial robot [J]. Robot, 2020, 42(3): 325-335.

CHEN B, XIE B H, DING L, et al . Dynamical model identification for industrial robot with playload [J ] . Journal of Nanjing University of Aeronautics and Astronautics, 2016, 48(6): 835-840.

LIU Y, PENG S G, DU Y X, et al . Lower limb exoskeleton robot dynamic modeling and LQR control of gait tracking [J ] . Computer Simulation, 2021, 38(4): 296-301.

霍伟. 机器人动力学与控制[M]. 北京: 高等教育出版社, 2005: 87-97.

韩清凯, 罗忠. 机械系统多体动力学分析、控制与仿真[M]. 北京: 科学出版社, 2010: 98-100.

GHAN J, KAZEROONI H. System identification for the Berkeley lower extremity exoskeleton (BLEEX) [C]// Proceedings of the 2006 IEEE International Conference on Robotics and Automation. Orlando: IEEE, 2006: 3477-3484.

LIU Y, PENG S G, DU Y X, et al . Kinematics modeling and gait trajectory tracking for lower limb exoskeleton robot based on pd control with gravity compensation[C ] // Proceedings of the 38th Chinese Control Conference, Guangzhou: Science and Technology Press, 2018: 4504-4511.

TIAN H, SHI X K, SHI X Q, et al . The mass distribution of Chinese young males [J ] . Journal of the Jilin Military Medical College Fourth Military Medical University, 2001, 23(3): 127-128.

刘金琨. 机器人控制系统的设计与MATLAB仿真——基本设计方法[M]. 北京: 清华大学出版社, 2016: 216-219.

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