Sosa Méndez, Deira, Bedolla-Martínez, David, Saad, Maarouf, Kali, Yassine, García Cena, Cecilia E. and Álvarez, Ángel L..
2025.
« Upper-limb robotic rehabilitation: Online sliding mode controller gain tuning using particle swarm optimization ».
Robotics, vol. 14, nº 4.
Compte des citations dans Scopus : 3.
Preview |
PDF
Saad-M-2025-30889.pdf - Published Version Use licence: Creative Commons CC BY. Download (5MB) | Preview |
Abstract
Two primary challenges in controlling robotic rehabilitation devices are the uncertainties in dynamic models and, more importantly, the need for controllers capable of adapting to external disturbances due to human–robot interaction. To address these issues, this paper proposes the particle swarm optimization (PSO) algorithm for the real-time gain tuning in the sliding mode controller (SMC) based on the exponential reaching law (ERL). The proposed approach was designed for a seven-degrees-of-freedom (DOF) robotic exoskeleton used in upper-limb physical rehabilitation. The optimization algorithm aims to minimize tracking errors in rehabilitation exercises through the robust ERL controller applied to nonlinear systems with external disturbances. The proposed method was validated through experimental tests conducted on two healthy subjects, and the outcomes indicated a reduction of over 20% in tracking errors compared to heuristically tuned gains. Mathematical analyses of dynamic modeling and algorithm convergence are shown
| Item Type: | Peer reviewed article published in a journal |
|---|---|
| Professor: | Professor Saad, Maarouf |
| Affiliation: | Génie électrique |
| Date Deposited: | 08 May 2025 15:06 |
| Last Modified: | 12 May 2025 18:05 |
| URI: | https://espace2.etsmtl.ca/id/eprint/30889 |
Actions (login required)
 |
View Item |