Novel Adaptive Reaching Law for Sliding Mode Control of an Upper Limb Exoskeleton Robot∗

Brahim Brahmi, Khaled El-Monajjed, Mohammad Habibur Rahman, Tanvir Ahmed, Claude El-Bayeh, Mahfuzur Rahman Khan, Maarouf Saad

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

5 Scopus citations

Abstract

In this research, we propose a novel sliding mode controller (SMC) to control the nonlinear systems. The proposed control approach includes a modification of the reaching law that overcomes the major limitations of the SMC. The proposed reaching law, unlike the existing ones, provide high trajectory tracking performance by effectively reducing the undesirable chattering problem and faster converging the system trajectories to zero. Thus the proposed reaching law allows benefiting from its advantages (faster convergence, reduced chattering, and high trajectory tracking), as well as overcome the limitations of both conventional sliding mode control (SMC) and the exponential reaching law (ERL). To evaluate the performance of the proposed controller and validate our propositions in real-time, experiments have been carried out with a wearable upper extremity exoskeleton robot named ETS-MARSE. Further, the experimental results were compared to the results with the conventional SMC and ERL to demonstrate the better performance of the proposed controller.

Original languageEnglish
Title of host publication2020 IEEE Region 10 Symposium, TENSYMP 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1432-1437
Number of pages6
ISBN (Electronic)9781728173665
DOIs
StatePublished - 5 Jun 2020
Externally publishedYes

Publication series

Name2020 IEEE Region 10 Symposium, TENSYMP 2020

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • Adaptive reaching law
  • Rehabilitation robot
  • Sliding mode control

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Energy Engineering and Power Technology
  • Biomedical Engineering
  • Electrical and Electronic Engineering
  • Health Informatics

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