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Sensors 2018, 18(1), 66; https://doi.org/10.3390/s18010066

Disturbance-Estimated Adaptive Backstepping Sliding Mode Control of a Pneumatic Muscles-Driven Ankle Rehabilitation Robot

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1,2,3,* , 1,2
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1
School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China
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Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan University of Technology, Wuhan 430070, China
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School of Electronic and Electrical Engineering, University of Leeds, Leeds LS2 9JT, UK
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Faculty of Engineering, Environment and Computing, Coventry University, Coventry CV1 5FB, UK
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Author to whom correspondence should be addressed.
Received: 1 November 2017 / Revised: 25 December 2017 / Accepted: 26 December 2017 / Published: 28 December 2017
(This article belongs to the Special Issue Assistance Robotics and Biosensors)
Full-Text   |   PDF [3263 KB, uploaded 28 December 2017]   |  

Abstract

A rehabilitation robot plays an important role in relieving the therapists’ burden and helping patients with ankle injuries to perform more accurate and effective rehabilitation training. However, a majority of current ankle rehabilitation robots are rigid and have drawbacks in terms of complex structure, poor flexibility and lack of safety. Taking advantages of pneumatic muscles’ good flexibility and light weight, we developed a novel two degrees of freedom (2-DOF) parallel compliant ankle rehabilitation robot actuated by pneumatic muscles (PMs). To solve the PM’s nonlinear characteristics during operation and to tackle the human-robot uncertainties in rehabilitation, an adaptive backstepping sliding mode control (ABS-SMC) method is proposed in this paper. The human-robot external disturbance can be estimated by an observer, who is then used to adjust the robot output to accommodate external changes. The system stability is guaranteed by the Lyapunov stability theorem. Experimental results on the compliant ankle rehabilitation robot show that the proposed ABS-SMC is able to estimate the external disturbance online and adjust the control output in real time during operation, resulting in a higher trajectory tracking accuracy and better response performance especially in dynamic conditions. View Full-Text
Keywords: parallel robot; ankle rehabilitation; pneumatic muscles; disturbance estimation; adaptive sliding mode control parallel robot; ankle rehabilitation; pneumatic muscles; disturbance estimation; adaptive sliding mode control
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Ai, Q.; Zhu, C.; Zuo, J.; Meng, W.; Liu, Q.; Xie, S.Q.; Yang, M. Disturbance-Estimated Adaptive Backstepping Sliding Mode Control of a Pneumatic Muscles-Driven Ankle Rehabilitation Robot. Sensors 2018, 18, 66.

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