Control of Soft Wearable Robots for Elbow Assistance and Rehabilitation: A Simplified Solution Using Disturbance Observer and Nonsmooth Feedback

Soft wearable robots present a promising approach for elbow assistance and rehabilitation. However, most existing devices rely on open-loop control strategies, which renders individual customization cumbersome and incapable of adapting to dynamic interactions. The challenges in implementing closed-l...

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Published inIEEE transactions on neural systems and rehabilitation engineering Vol. 33; pp. 2988 - 2999
Main Authors Wang, Jiajin, Xu, Baoguo, Wang, Xin, Lai, Jianwei, Wei, Xiangshan, Zhao, Zishuo, Lu, Ye, Shen, Ying, Wang, Hongxing, Song, Aiguo
Format Journal Article
LanguageEnglish
Published United States IEEE 2025
Subjects
Actuators
Adult
Algorithms
Analytical models
Bending
Biomechanical Phenomena
composite controller
Computer Simulation
disturbance observer
Elbow
Elbow Joint
Equipment Design
Exoskeleton Device
Feedback
Feedforward systems
Humans
Male
Medical diagnostic imaging
Nonlinear Dynamics
Pneumatic systems
rehabilitation robotics
Robot sensing systems
Robotics - instrumentation
Soft robotics
Stroke Rehabilitation - instrumentation
Wearable Electronic Devices
Wearable robotics
Wearable robots
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Abstract Soft wearable robots present a promising approach for elbow assistance and rehabilitation. However, most existing devices rely on open-loop control strategies, which renders individual customization cumbersome and incapable of adapting to dynamic interactions. The challenges in implementing closed-loop control arise from the complex nonlinearities of soft robots and the unpredictable external disturbances encountered during human-robot interactions. To achieve closed-loop control of elbow soft wearable robots, this paper proposes a disturbance observer (DO)-based nonsmooth feedback (NSF) method. Specifically, a tailored DO is designed to enhance feedforward compensation by analyzing the unique characteristics of the disturbances encountered in practical systems. A nonrecursive NSF is employed to suppress residual disturbances and nonlinearities, with the finite-time stability of the closed-loop system rigorously guaranteed. The proposed method balances efficacy and simplicity by leveraging the concise models of both the system and disturbances to enhance performance while avoiding intricate modeling. Moreover, its nonrecursive design results in a straightforward control law and facilitates implementation. Extensive comparison and ablation experiments validate the superiority of the proposed method over existing approaches. Human trials involving 8 healthy subjects and 7 stroke patients demonstrate that our method enhances task performance, reduces muscle strain during elbow assistance scenarios, and significantly improves elbow motor function in rehabilitation training.
AbstractList Soft wearable robots present a promising approach for elbow assistance and rehabilitation. However, most existing devices rely on open-loop control strategies, which renders individual customization cumbersome and incapable of adapting to dynamic interactions. The challenges in implementing closed-loop control arise from the complex nonlinearities of soft robots and the unpredictable external disturbances encountered during human-robot interactions. To achieve closed-loop control of elbow soft wearable robots, this paper proposes a disturbance observer (DO)-based nonsmooth feedback (NSF) method. Specifically, a tailored DO is designed to enhance feedforward compensation by analyzing the unique characteristics of the disturbances encountered in practical systems. A nonrecursive NSF is employed to suppress residual disturbances and nonlinearities, with the finite-time stability of the closed-loop system rigorously guaranteed. The proposed method balances efficacy and simplicity by leveraging the concise models of both the system and disturbances to enhance performance while avoiding intricate modeling. Moreover, its nonrecursive design results in a straightforward control law and facilitates implementation. Extensive comparison and ablation experiments validate the superiority of the proposed method over existing approaches. Human trials involving 8 healthy subjects and 7 stroke patients demonstrate that our method enhances task performance, reduces muscle strain during elbow assistance scenarios, and significantly improves elbow motor function in rehabilitation training.
Soft wearable robots present a promising approach for elbow assistance and rehabilitation. However, most existing devices rely on open-loop control strategies, which renders individual customization cumbersome and incapable of adapting to dynamic interactions. The challenges in implementing closed-loop control arise from the complex nonlinearities of soft robots and the unpredictable external disturbances encountered during human-robot interactions. To achieve closed-loop control of elbow soft wearable robots, this paper proposes a disturbance observer (DO)-based nonsmooth feedback (NSF) method. Specifically, a tailored DO is designed to enhance feedforward compensation by analyzing the unique characteristics of the disturbances encountered in practical systems. A nonrecursive NSF is employed to suppress residual disturbances and nonlinearities, with the finite-time stability of the closed-loop system rigorously guaranteed. The proposed method balances efficacy and simplicity by leveraging the concise models of both the system and disturbances to enhance performance while avoiding intricate modeling. Moreover, its nonrecursive design results in a straightforward control law and facilitates implementation. Extensive comparison and ablation experiments validate the superiority of the proposed method over existing approaches. Human trials involving 8 healthy subjects and 7 stroke patients demonstrate that our method enhances task performance, reduces muscle strain during elbow assistance scenarios, and significantly improves elbow motor function in rehabilitation training.Soft wearable robots present a promising approach for elbow assistance and rehabilitation. However, most existing devices rely on open-loop control strategies, which renders individual customization cumbersome and incapable of adapting to dynamic interactions. The challenges in implementing closed-loop control arise from the complex nonlinearities of soft robots and the unpredictable external disturbances encountered during human-robot interactions. To achieve closed-loop control of elbow soft wearable robots, this paper proposes a disturbance observer (DO)-based nonsmooth feedback (NSF) method. Specifically, a tailored DO is designed to enhance feedforward compensation by analyzing the unique characteristics of the disturbances encountered in practical systems. A nonrecursive NSF is employed to suppress residual disturbances and nonlinearities, with the finite-time stability of the closed-loop system rigorously guaranteed. The proposed method balances efficacy and simplicity by leveraging the concise models of both the system and disturbances to enhance performance while avoiding intricate modeling. Moreover, its nonrecursive design results in a straightforward control law and facilitates implementation. Extensive comparison and ablation experiments validate the superiority of the proposed method over existing approaches. Human trials involving 8 healthy subjects and 7 stroke patients demonstrate that our method enhances task performance, reduces muscle strain during elbow assistance scenarios, and significantly improves elbow motor function in rehabilitation training.
Author Wang, Jiajin
Song, Aiguo
Wei, Xiangshan
Wang, Xin
Lai, Jianwei
Zhao, Zishuo
Shen, Ying
Xu, Baoguo
Lu, Ye
Wang, Hongxing
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Snippet Soft wearable robots present a promising approach for elbow assistance and rehabilitation. However, most existing devices rely on open-loop control strategies,...
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SubjectTerms Actuators
Adult
Algorithms
Analytical models
Bending
Biomechanical Phenomena
composite controller
Computer Simulation
disturbance observer
Elbow
Elbow Joint
Equipment Design
Exoskeleton Device
Feedback
Feedforward systems
Humans
Male
Medical diagnostic imaging
Nonlinear Dynamics
Pneumatic systems
rehabilitation robotics
Robot sensing systems
Robotics - instrumentation
Soft robotics
Stroke Rehabilitation - instrumentation
Wearable Electronic Devices
Wearable robotics
Wearable robots
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Title Control of Soft Wearable Robots for Elbow Assistance and Rehabilitation: A Simplified Solution Using Disturbance Observer and Nonsmooth Feedback
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