[Trajectory planning and tracking control for upper limb traction rehabilitation training].

To solve the safety problems caused by the restriction of interaction space and the singular configuration of rehabilitation robot in terminal traction upper limb rehabilitation training, a trajectory planning and tracking control scheme for rehabilitation training is proposed. The human-robot safe interaction space was obtained based on kinematics modeling and rehabilitation theory, and the training trajectory was planned based on the occupational therapy in rehabilitation medicine. The singular configuration of the rehabilitation robot in the interaction space was avoided by exponential adaptive damped least square method. Then, a nonlinear controller for the upper limb rehabilitation robot was designed based on the backstepping control method. Radial basis function neural network was used to approximate the robot model information online to achieve model-free control. The stability of the controller was proved by Lyapunov stability theory. Experimental results demonstrate the effectiveness and superiority of the proposed singular avoidance control scheme.

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Publication Details

Journal
PubMed
Published
2025-04-25
DOI
https://doi.org/10.7507/1001-5515.202501049
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Controls
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article

[Trajectory planning and tracking control for upper limb traction rehabilitation training].

Qi Lu, Xiangyun Li, Peng Chen, Kang Li et al.
PubMed
Stroke Rehabilitation and Recovery
article

[Trajectory planning and tracking control for upper limb traction rehabilitation training].

Qi Lu, Xiangyun Li, Peng Chen, Kang Li, Shuang Luo
article en

Abstract

To solve the safety problems caused by the restriction of interaction space and the singular configuration of rehabilitation robot in terminal traction upper limb rehabilitation training, a trajectory planning and tracking control scheme for rehabilitation training is proposed. The human-robot safe interaction space was obtained based on kinematics modeling and rehabilitation theory, and the training trajectory was planned based on the occupational therapy in rehabilitation medicine. The singular configuration of the rehabilitation robot in the interaction space was avoided by exponential adaptive damped least square method. Then, a nonlinear controller for the upper limb rehabilitation robot was designed based on the backstepping control method. Radial basis function neural network was used to approximate the robot model information online to achieve model-free control. The stability of the controller was proved by Lyapunov stability theory. Experimental results demonstrate the effectiveness and superiority of the proposed singular avoidance control scheme.

PubMedVol. 42(2)
Sichuan University (CN), West China Medical Center of Sichuan University (CN)
Stroke Rehabilitation and Recovery
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