Scholarlink

<p>Achieving precise motion control while ensuring safe physical human-robot interaction (pHRI) remains difficult in rehabilitation robotics, especially when facing unpredictable muscular spasms and modeling uncertainties. To address these challenges, this paper proposes an integrated stiffness-adaptive regulation control (iSARC) scheme. Distinguished from traditional decoupled strategies, iSARC establishes a unified framework by integrating an ultra-local model (ULM) with a safety-constrained regulation scheme to simultaneously handle position tracking and stiffness regulation. Specifically, to enhance robustness, a bandwidth-parameterized linear extended state observer (LESO) is integrated to estimate and compensate for lumped disturbances in real-time. The core theoretical contribution is the formal embedding of a Barrier Lyapunov Function (BLF) into the ULM-based law to guarantee interaction safety. Notably, while existing ADRC or impedance-based approaches often fail to guarantee the strict satisfaction of interaction torque constraints under impulsive-like disturbances, iSARC provably maintains the system states within a predefined safe set. Theoretical analysis confirms closed-loop stability and bounded tracking error. Comparative experiments validate the effectiveness of iSARC, demonstrating significantly improved tracking accuracy and smoother stiffness modulation even under spasticity-mimicking disturbances. The results confirm that the proposed scheme effectively enhances disturbance rejection and adaptive compliance for dynamic rehabilitation tasks.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

iSARC: unified position and interaction-aware stiffness control for physical human-robot interaction

  • 期刊论文

  • 发表日期：

    2026年4月23日

查看全文
  • Keping Liu,
  • Yi Zheng,
  • Chen Wang,
  • Changlin Yu,
  • Zhongbo Sun,
  • Liming Zhao

摘要

Achieving precise motion control while ensuring safe physical human-robot interaction (pHRI) remains difficult in rehabilitation robotics, especially when facing unpredictable muscular spasms and modeling uncertainties. To address these challenges, this paper proposes an integrated stiffness-adaptive regulation control (iSARC) scheme. Distinguished from traditional decoupled strategies, iSARC establishes a unified framework by integrating an ultra-local model (ULM) with a safety-constrained regulation scheme to simultaneously handle position tracking and stiffness regulation. Specifically, to enhance robustness, a bandwidth-parameterized linear extended state observer (LESO) is integrated to estimate and compensate for lumped disturbances in real-time. The core theoretical contribution is the formal embedding of a Barrier Lyapunov Function (BLF) into the ULM-based law to guarantee interaction safety. Notably, while existing ADRC or impedance-based approaches often fail to guarantee the strict satisfaction of interaction torque constraints under impulsive-like disturbances, iSARC provably maintains the system states within a predefined safe set. Theoretical analysis confirms closed-loop stability and bounded tracking error. Comparative experiments validate the effectiveness of iSARC, demonstrating significantly improved tracking accuracy and smoother stiffness modulation even under spasticity-mimicking disturbances. The results confirm that the proposed scheme effectively enhances disturbance rejection and adaptive compliance for dynamic rehabilitation tasks.