Research on Human Upper Limb Tremor Suppression Method Based on Port-Controlled Hamiltonian System and Sliding Mode Control

In upper-limb rehabilitation training aided by robotic systems, patients often develop tremors due to insufficient muscle strength or neurological control disorders, adversely impacting the rehabilitation process. Based on the Port-Hamiltonian Systems (PHS) theoretical framework, this paper proposes a Sliding Mode Control (SMC) strategy to suppress tremors during upper-limb rehabilitation. The approach employs two Lyapunov functions: on one hand, the Hamiltonian (the system’s energy function) ensures overall Lyapunov stability; on the other, an additional Lyapunov function enforces finite-time convergence of the sliding variable, thereby rapidly mitigating tremors and maintaining tracking accuracy. Simulation results indicate that this method not only achieves outstanding stability but also guarantees finite-time convergence of the sliding variable, significantly reducing arm tremors. Consequently, it provides an efficient and viable advanced control solution for upper-limb rehabilitation robots.

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Publication Details

Published
2025-05-23
DOI
https://doi.org/10.1109/icaisisas64483.2025.11051604
Primary Topic
Neuroscience and Neural Engineering
Type
article
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Research on Human Upper Limb Tremor Suppression Method Based on Port-Controlled Hamiltonian System and Sliding Mode Control

Jian Li, Minshan Feng, Hongyu Yan, Jiawen Zhan et al.
Neuroscience and Neural Engineering
article

Research on Human Upper Limb Tremor Suppression Method Based on Port-Controlled Hamiltonian System and Sliding Mode Control

Jian Li, Minshan Feng, Hongyu Yan, Jiawen Zhan, Jingjing Li, Zhe Chen
article en

Abstract

In upper-limb rehabilitation training aided by robotic systems, patients often develop tremors due to insufficient muscle strength or neurological control disorders, adversely impacting the rehabilitation process. Based on the Port-Hamiltonian Systems (PHS) theoretical framework, this paper proposes a Sliding Mode Control (SMC) strategy to suppress tremors during upper-limb rehabilitation. The approach employs two Lyapunov functions: on one hand, the Hamiltonian (the system’s energy function) ensures overall Lyapunov stability; on the other, an additional Lyapunov function enforces finite-time convergence of the sliding variable, thereby rapidly mitigating tremors and maintaining tracking accuracy. Simulation results indicate that this method not only achieves outstanding stability but also guarantees finite-time convergence of the sliding variable, significantly reducing arm tremors. Consequently, it provides an efficient and viable advanced control solution for upper-limb rehabilitation robots.

Beijing Institute of Technology (CN), Wangjing Hospital of China Academy of Chinese Medical Sciences (CN)
Openalex Percentile: Top 83%
Neuroscience and Neural Engineering
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