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Passive hand rehabilitation training through robots: An iterative learning control approach

  • H. Long Cheng*
  • , Siyuan Liu
  • , Deyuan Meng
  • *Corresponding author for this work
  • CAS - Institute of Automation
  • University of Chinese Academy of Sciences
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Robots are widely used in the field of medical rehabilitation to assist patients to conduct rehabilitation training. Due to the repetition nature of the rehabilitation training, this paper proposes an iterative learning controller equipped with feedback mechanism for the passive hand rehabilitation training, which is based on a cable-driven hand exoskeleton robot. Thanks to the use of the information from previous iterations, the desired trajectory can be perfectly tracked over a finite duration. Moreover, the monotonic convergence of the proposed iterative learning controller can be achieved under a sufficient condition. In addition, our iterative learning controller is applied to the hand exoskeleton robot in both the simulation tests and the physical trajectory tracking experiments, which demonstrates its effectiveness and desired control performance.

Original languageEnglish
Title of host publication2021 6th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages651-656
Number of pages6
ISBN (Electronic)9780738133645
DOIs
StatePublished - 3 Jul 2021
Event6th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2021 - Chongqing, China
Duration: 3 Jul 20215 Jul 2021

Publication series

Name2021 6th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2021

Conference

Conference6th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2021
Country/TerritoryChina
CityChongqing
Period3/07/215/07/21

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