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Design and single-parameter adaptive fuzzy control of pneumatic lower limb exoskeleton with full state constraints

Published online by Cambridge University Press:  30 August 2022

Cheng Chen
Affiliation:
Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Jian Huang*
Affiliation:
Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Xikai Tu
Affiliation:
Department of Mechanical Engineering, Hubei University of Technology, Wuhan 430074, China
*
*Corresponding author. E-mail: huang_jan@mail.hust.edu.cn

Abstract

With the excellent characteristic of intrinsic compliance, pneumatic artificial muscle can improve the interaction comfort of wearable robotic devices. This paper resolves the safety tracking control problem of a pneumatically actuated lower limb exoskeleton system. A single-parameter adaptive fuzzy control strategy is proposed with high control precision and full state constraints for the safe gait training tasks. Based on the barrier Lyapunov function, all signals in the closed-loop system can be bounded in finite time, which guarantees the deviation of the exoskeleton’s moving trajectory within a bounded range. Furthermore, with the proposed single-parameter adaptive law, the computational burden and the complexity of the control are reduced significantly. Finally, numerical simulations, no-load tracking experiments, and passive and active gait training experiments with healthy subjects validate the effectiveness of the proposed method.

Type
Research Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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