Zhang, M, Mcdaid, A, Veale, AJ et al. (2 more authors) (2019) Adaptive Trajectory Tracking Control of a Parallel Ankle Rehabilitation Robot With Joint-Space Force Distribution. IEEE Access, 7. pp. 85812-85820.
Abstract
This paper proposes an adaptive trajectory tracking control strategy implemented on a parallel ankle rehabilitation robot with joint-space force distribution. This device is redundantly actuated by four pneumatic muscles (PMs) with three rotational degrees of freedom. Accurate trajectory tracking is achieved through a cascade controller with the position feedback in task space and force feedback in joint space, which enhances training safety by controlling each PM to be in tension in an appropriate level. At a high level, an adaptive algorithm is proposed to enable movement intention-directed trajectory adaptation. This can further help to improve training safety and encourage human-robot engagement. The pilot tests were conducted with an injured human ankle. The statistical data show that normalized root mean square deviation (NRMSD) values of trajectory tracking are all less than 2.3% and the PM force tracking being always controlled in tension, demonstrating its potential in assisting ankle therapy.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019, Author(s). This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/ |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Funding Information: | Funder Grant number EPSRC EP/S019219/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 Aug 2019 12:30 |
Last Modified: | 09 Aug 2019 12:30 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ACCESS.2019.2925182 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:149511 |