基于积分障碍李雅普诺夫函数的下肢康复机器人柔顺控制
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浙江工业大学

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TP

基金项目:

国家自然科学基金项目(面上项目,重点项目,重大项目)


Compliant Control of Lower Limb Rehabilitation Robots Based on Integral Barrier Lyapunov Function
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Affiliation:

Zhejiang University of Technology

Fund Project:

The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    摘要:

    为保障下肢失能患者主动康复训练的效果和安全性, 针对下肢康复外骨骼机器人设计一种基于非对称积分障碍李雅普诺夫函数的无力矩传感器导纳控制方法. 首先, 基于广义动量法设计一种滑模观测器, 用以实时估计人机交互力矩, 从而降低下肢外骨骼对力矩传感器的依赖. 其次, 面向下肢外骨骼构建一种导纳控制框架, 利用饱和函数将外环导纳模型生成的参考轨迹约束在预定的安全区间内, 以保证外骨骼的柔顺性与安全性. 此外, 针对内环步态轨迹跟踪设计一种基于非对称积分李雅普诺夫函数的反演滑模控制算法, 保障系统的输出约束性能与步态轨迹跟踪精度. 最后, 基于李雅普诺夫稳定性判据证明控制系统的稳定性, 并在下肢康复机器人实验平台上验证所提出控制算法的有效性和优越性.

    Abstract:

    To ensure the effectiveness and safety of active rehabilitation training for patients with lower limb disabilities, this study designs a torque-less sensor admittance control method based on an asymmetric integral barrier Lyapunov function for lower limb rehabilitation exoskeleton robots. Firstly, a sliding mode observer is designed based on the generalized momentum method to estimate the human-robot interaction torque in real-time, thereby reducing the reliance on torque sensors by the lower limb exoskeleton. Secondly, an admittance control framework is constructed for the lower limb exoskeleton, utilizing a saturation function to constrain the reference trajectory generated by the outer loop admittance model within a predetermined safe range, ensuring the compliance and safety of the exoskeleton. Additionally, for the inner loop gait trajectory tracking, an inverse sliding mode control algorithm based on an asymmetric integral Lyapunov function is designed to guarantee the system"s output constraint performance and gait trajectory tracking accuracy. Finally, the stability of the control system is proven based on the Lyapunov stability criterion, and the effectiveness and superiority of the proposed control algorithm are verified on a lower limb rehabilitation robot experimental platform.

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  • 收稿日期:2024-10-08
  • 最后修改日期:2024-12-16
  • 录用日期:2024-12-17
  • 在线发布日期: 2024-12-31
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