Variable admittance time-delay control of an upper limb rehabilitation robot based on human stiffness estimation. (April 2023)

• Record Type: Journal Article
• Authors: Wu, Qingcong; Chen, Ying
• Is Part Of: Mechatronics. Volume 90(2023)
• Publication Date: 2023-04
• Subjects: Upper limb rehabilitation robot -- Variable admittance -- Time-delay control -- Human stiffness estimation -- Interaction compliance; Computer integrated manufacturing systems -- Periodicals; Flexible manufacturing systems -- Periodicals; Mechatronics -- Periodicals; Productique -- Périodiques; Fabrication, Systèmes flexibles de -- Périodiques; Mécatronique -- Périodiques; Computer integrated manufacturing systems; Flexible manufacturing systems; Mechatronics; Periodicals; 629.89
• DOI: 10.1016/j.mechatronics.2022.102935
• Languages: English
• ISSNs: 0957-4158

Abstract

Highlights: A variable admittance time-delay cooperative controller is developed for upper limb rehabilitation training. An iterative optimization algorithm is proposed to estimate human arm stiffness and adjust interaction compliance. The training trajectory is determined based on minimum jerk cost principle to ensure smoothness and continuity. The effectiveness is validated via trajectory tracking experiments with variable admittance regulation. Abstract: This paper proposes a new variable admittance time-delay control strategy based on human stiffness estimation for improving the effectiveness of robot-assisted cooperative rehabilitation training. This control strategy is developed and implemented on a planar upper limb rehabilitation robot. Given the minimum-jerk-based desired trajectories of human hand position, in the developed control strategy, a time-delay approximator is utilized to estimate the external disturbances and modeling errors without exact knowledge of dynamics parameters, a sliding mode admittance controller is applied to obtained objective admittance characteristics, and an iterative optimization algorithm is used to estimate human arm stiffness and adjust human-robot interaction compliance. The closed-loop stability of the proposed control method is demonstrated via Lyapunov function theory. Experimental investigations involving ten subjects are conducted to validate the feasibility of the proposed control scheme. The experimental results show that the interaction compliance during cooperative rehabilitation training can be accurately adjusted based on selected admittance parameters and human arm stiffness, and it contributes to satisfying the specific training requirements of patients with different weakness levels and promoting the effectiveness of the robot-assisted training.