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An adaptive seamless assist-as-needed control scheme for lower extremity rehabilitation robots

Zhang, Xiaodong and Yin, Gui and Li, Hanzhe and Dong, Runlin and Hu, Huosheng (2020) 'An adaptive seamless assist-as-needed control scheme for lower extremity rehabilitation robots.' Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering. ISSN 0959-6518

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Abstract

Most control methods deployed in lower extremity rehabilitation robots cannot automatically adjust to different gait cycle stages and different rehabilitation training modes for different impairment subjects. This article presents a continuous seamless assist-as-needed control method based on sliding mode adaptive control. A forgetting factor is introduced, and a small trajectory deviation from reference normal gait trajectory is used to learn the rehabilitation level of a human subject in real time. The assistance torque needed to complete the reference normal gait trajectory is learned through radial basis function neural networks, so that the rehabilitation robot can adaptively provide the assistance torque according to subject’s needs. The performance and efficiency of this adaptive seamless assist-as-needed control scheme are tested and validated by 12 volunteers on a rehabilitation robot prototype. The results show that the proposed control scheme could adaptively reduce the robotic assistance according to subject’s rehabilitation level, and the robotic assistance torque depends on the forgetting factor and the active participation level of subjects.

Item Type: Article
Uncontrolled Keywords: Assist-as-needed control, lower extremity rehabilitation robot, radial basis function neural networks, forgetting factor, trajectory deviation
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 03 Dec 2020 10:26
Last Modified: 03 Dec 2020 10:26
URI: http://repository.essex.ac.uk/id/eprint/29275

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