Title: Adaptive iterative learning-based gait tracking control for paediatric exoskeleton during passive-assist rehabilitation

Authors: Jyotindra Narayan; Mohamed Abbas; Santosha K. Dwivedy

Addresses: Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Assam, 781039, India ' Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Assam, 781039, India; Department of Design and Production, Al-Baath University, Homs, Syria ' Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Assam, 781039, India

Abstract: The design of a robust control scheme is considered a benchmark problem to address the uncertain dynamic parameters and un-modelled disturbances of the exoskeleton system. This work proposes a robust adaptive iterative learning (AIL) control (AILC) scheme for a paediatric exoskeleton system. Primarily, the mechanical description of the exoskeleton system is briefly presented along with the input parameters. Thereafter, the dynamic relation, invoking kinetic and potential energy of the system, is formulated via the Euler-Lagrange principle. The stability of the AILC scheme is ascertained using the Lyapunov analysis. The robustness is validated by incorporating the parametric uncertainties (varied mass) and un-modelled disturbances (trigonometric and random noises). Thereafter, the controller's performance is compared with classical iterative learning control (ILC) and exponential reaching law- sliding mode control (ERL-SMC) schemes. Finally, it is observed from simulation runs that the AIL controller has enough potential to track the desired gait trajectory accurately.

Keywords: robust control; AIL; adaptive iterative learning; paediatric exoskeleton; Lyapunov; parametric uncertainties; un-modelled disturbances.

DOI: 10.1504/IJIEI.2021.10046403

International Journal of Intelligent Engineering Informatics, 2021 Vol.9 No.6, pp.507 - 532

Received: 16 Mar 2021
Accepted: 05 Aug 2021

Published online: 25 Apr 2022 *

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