• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2016, Vol. 52 ›› Issue (15): 8-14.doi: 10.3901/JME.2016.15.008

• 机构学及机器人 • 上一篇    下一篇

基于阻抗辨识和混杂控制的机器人辅助抗阻训练方法*

徐国政1, 陈雯1, 高翔1, 宋爱国2   

  1. 1. 南京邮电大学自动化学院 南京 210023
    2.东南大学远程测控技术江苏省重点实验室 南京 210096
  • 出版日期:2016-08-05 发布日期:2016-08-05
  • 作者简介:

    徐国政(通信作者),男,1980年出生,博士,副教授,硕士研究生导师。主要研究方向为康复机器人传感与网络化控制、助老助残智能移动服务机器人。

    E-mail:xugz@njupt.edu.cn

    E-mail:a.g.song@seu.edu.cn

  • 基金资助:
    * 国家自然科学基金(61305095)、江苏省重点研发计划(BE2015701)和江苏省自然科学基金(BK20141426)资助项目; 20150724收到初稿,20160322收到修改稿;

Robot-aided Resistance Training Method based on Impedance Identification and Hybrid Control

XU Guozheng1, CHEN Wen, SONG Aiguo2   

  1. 1. College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023
    2. Jiangsu Province Key Laboratory of Remote Measuring and Control, Southeast University, Nanjing 210096
  • Online:2016-08-05 Published:2016-08-05

摘要:

现有机器人辅助抗阻训练方法大多是运用易受噪声干扰的患肢主动作用力或表面肌电信号直接进行治疗控制器设计,且在设计过程中未能同时将机器人连续变量运动控制与医师离散事件决策控制这种混杂特性融于统一框架内,具有一定的局限。针对上述问题,提出一种基于阻抗辨识和混杂控制的机器人辅助抗阻训练方法,该方法首先根据患肢主动作用力和实际运动位置在线辨识患肢时变生物阻抗;其次,运用混杂控制理论建立机器人辅助抗阻过程系统模型,根据患肢生物阻抗变化分别定义连续系统区域切换离散事件及离散系统控制状态,并基于混杂自动机设计离散事件决策控制器;最后,选用美国Barrett 公司WAMTM柔顺机械臂构建康复试验系统,对所设计控制器进行有效性验证。试验结果验证了阻抗辨识和混杂控制理论应用于机器人辅助抗阻训练过程的有效性和实用性。

关键词: 混杂控制, 抗阻训练, 阻抗辨识, 康复机器人

Abstract:

:A certain limitation still exists in the current robot-aided resistance training method, in which the therapeutic controller is mainly designed based on the impaired limb’s active force and electromyogram signal which is vulnerable to noise impact, and further it does not incorporate continuous variable motion control and discrete event decision control into a unified framework. To solve the aforementioned problem, a therapy control method based on impedance identification and hybrid modeling is proposed. Firstly, the impaired limb’s time-variant bio-impedance is online identified by using the impaired limb’s active force and actual position. Secondly, the robot-aided resistance training system model is built using hybrid control theory, in which the discrete events for continuous dynamic system is defined according to the identified impaired limb’s bio-impedance changes, moreover, the discrete control states and the discrete event supervisory controller based on hybrid automation are also given for discrete dynamic system. Finally, the experimental system platform is constructed by using the WAMTM compliant manipulator of Barrett Inc., and the experimental results verify the effectiveness and practicability for the applications to robot-aided resistance training using impedance identification and hybrid control theory.

Key words: hybrid control, impedance identification, resistance training, rehabilitation robot