Iterative Impedance Learning Control for Ankle Rehabilitation

Kun Qian; Zhiqiang Zhang; Samit Chakrabarty; Shengquan Xie

doi:10.1109/M2VIP49856.2021.9665027

Iterative Impedance Learning Control for Ankle Rehabilitation

Kun Qian
, Zhiqiang Zhang
, Samit Chakrabarty
, Shengquan Xie

University of Leeds

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

In this paper, impedance learning control is investigated for conducting robot-aided ankle rehabilitation. Under repetitive interaction tasks, the ankle dynamic is described as a time-varying iterative system with unknown mechanical impedance parameters. The gradient following approach and iterative learning algorithm are employed to obtain a desired impedance model. With learned parameters, an inner torque controller with robot dynamic compensation is implemented for tracking the modified trajectory. Experimental results with an ankle rehabilitation robot prototype validate the efficacy of proposed method.

Original language	English
Title of host publication	2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	492-497
Number of pages	6
ISBN (Electronic)	9781665431538
DOIs	https://doi.org/10.1109/M2VIP49856.2021.9665027
State	Published - 2021
Externally published	Yes
Event	2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021 - Shanghai, China Duration: 26 Nov 2021 → 28 Nov 2021

Publication series

Name	2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021

Conference

Conference	2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021
Country/Territory	China
City	Shanghai
Period	26/11/21 → 28/11/21

Access to Document

10.1109/M2VIP49856.2021.9665027

Cite this

Qian, K., Zhang, Z., Chakrabarty, S., & Xie, S. (2021). Iterative Impedance Learning Control for Ankle Rehabilitation. In 2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021 (pp. 492-497). (2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/M2VIP49856.2021.9665027

Qian, Kun ; Zhang, Zhiqiang ; Chakrabarty, Samit et al. / Iterative Impedance Learning Control for Ankle Rehabilitation. 2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 492-497 (2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021).

@inproceedings{a54dc1e9a2b54b479a0db1298a7fba6f,

title = "Iterative Impedance Learning Control for Ankle Rehabilitation",

abstract = "In this paper, impedance learning control is investigated for conducting robot-aided ankle rehabilitation. Under repetitive interaction tasks, the ankle dynamic is described as a time-varying iterative system with unknown mechanical impedance parameters. The gradient following approach and iterative learning algorithm are employed to obtain a desired impedance model. With learned parameters, an inner torque controller with robot dynamic compensation is implemented for tracking the modified trajectory. Experimental results with an ankle rehabilitation robot prototype validate the efficacy of proposed method.",

author = "Kun Qian and Zhiqiang Zhang and Samit Chakrabarty and Shengquan Xie",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021 ; Conference date: 26-11-2021 Through 28-11-2021",

year = "2021",

doi = "10.1109/M2VIP49856.2021.9665027",

language = "英语",

series = "2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "492--497",

booktitle = "2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021",

}

Qian, K, Zhang, Z, Chakrabarty, S & Xie, S 2021, Iterative Impedance Learning Control for Ankle Rehabilitation. in 2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021. 2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021, Institute of Electrical and Electronics Engineers Inc., pp. 492-497, 2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021, Shanghai, China, 26/11/21. https://doi.org/10.1109/M2VIP49856.2021.9665027

Iterative Impedance Learning Control for Ankle Rehabilitation. / Qian, Kun; Zhang, Zhiqiang; Chakrabarty, Samit et al.
2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 492-497 (2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Iterative Impedance Learning Control for Ankle Rehabilitation

AU - Qian, Kun

AU - Zhang, Zhiqiang

AU - Chakrabarty, Samit

AU - Xie, Shengquan

PY - 2021

Y1 - 2021

N2 - In this paper, impedance learning control is investigated for conducting robot-aided ankle rehabilitation. Under repetitive interaction tasks, the ankle dynamic is described as a time-varying iterative system with unknown mechanical impedance parameters. The gradient following approach and iterative learning algorithm are employed to obtain a desired impedance model. With learned parameters, an inner torque controller with robot dynamic compensation is implemented for tracking the modified trajectory. Experimental results with an ankle rehabilitation robot prototype validate the efficacy of proposed method.

AB - In this paper, impedance learning control is investigated for conducting robot-aided ankle rehabilitation. Under repetitive interaction tasks, the ankle dynamic is described as a time-varying iterative system with unknown mechanical impedance parameters. The gradient following approach and iterative learning algorithm are employed to obtain a desired impedance model. With learned parameters, an inner torque controller with robot dynamic compensation is implemented for tracking the modified trajectory. Experimental results with an ankle rehabilitation robot prototype validate the efficacy of proposed method.

UR - https://www.scopus.com/pages/publications/85124793857

U2 - 10.1109/M2VIP49856.2021.9665027

DO - 10.1109/M2VIP49856.2021.9665027

M3 - 会议稿件

AN - SCOPUS:85124793857

T3 - 2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021

SP - 492

EP - 497

BT - 2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021

Y2 - 26 November 2021 through 28 November 2021

ER -

Qian K, Zhang Z, Chakrabarty S, Xie S. Iterative Impedance Learning Control for Ankle Rehabilitation. In 2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 492-497. (2021 27th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2021). doi: 10.1109/M2VIP49856.2021.9665027

Iterative Impedance Learning Control for Ankle Rehabilitation

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