Identification and control of rehabilitation robots with unknown dynamics: a new probabilistic algorithm based on a finite-time estimator

Alotaibi, Naif D., Jahanshahi, Hadi, Yao, Qijia, Mou, Jun and Bekiros, Stelios (2023) Identification and control of rehabilitation robots with unknown dynamics: a new probabilistic algorithm based on a finite-time estimator. Mathematics, 11 (17). ISSN 2227-7390

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Abstract

The control of rehabilitation robots presents a formidable challenge owing to the myriad of uncharted disturbances encountered in real-world applications. Despite the existence of several techniques proposed for controlling and identifying such systems, many cutting-edge approaches have yet to be implemented in the context of rehabilitation robots. This highlights the necessity for further investigation and exploration in this field. In light of this motivation, we introduce a pioneering algorithm that employs a finite estimator and Gaussian process to identify and forecast the uncharted dynamics of a 2-DoF knee rehabilitation robot. The proposed algorithm harnesses the probabilistic nature of Gaussian processes, while also guaranteeing finite-time convergence through the utilization of the Lyapunov theorem. This dual advantage allows for the effective exploitation of the Gaussian process’s probabilistic capabilities while ensuring reliable and timely convergence of the algorithm. The algorithm is delineated and the finite time convergence is proven. Subsequently, its performance is investigated through numerical simulations for estimating complex unknown and time-varying dynamics. The results obtained from the proposed algorithm are then employed for controlling the rehabilitation robot, highlighting its remarkable capability to provide precise estimates while effectively handling uncertainty.

Item Type:	Article
Official URL:	https://www.mdpi.com/journal/mathematics
Additional Information:	© 2023 The Authors
Divisions:	LSE Health
Subjects:	H Social Sciences > HV Social pathology. Social and public welfare. Criminology T Technology > T Technology (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Date Deposited:	21 May 2024 11:42
Last Modified:	21 Nov 2024 04:12
URI:	http://eprints.lse.ac.uk/id/eprint/123547

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