摘要
步态轨迹规划是动力下肢假肢运动控制的重要环节.为实现假肢-健肢运动的协同,现有步态轨迹规划一般采用数据驱动建模方法,将假肢穿戴者的健肢侧运动直接映射为假肢目标运动轨迹.考虑到现有建模方法复杂度高、抗扰能力差的不足,本文提出了时滞储备池驱动的步态轨迹规划新方法.该方法以Mackey-Glass振子为储备池非线性节点,以截肢端髋关节摆动角度为输入,最终输出假肢膝关节目标运动轨迹.特别地,该储备池的输出是其虚拟节点状态量的线性叠加,因此在模型训练和计算上具有全局收敛性高、收敛速度快的优势.进一步,本文在FPGA上实现了时滞储备池步态映射模型的硬件部署,并通过与STM32的串行通信完成了数据交互,开展了动力下肢假肢的穿戴测试.实验结果表明,采用本文提出的新模型,假肢穿戴者在正常行走情况下健肢与假肢之间的相关系数为0.8377,扰动情况下为0.7436,均表现出较强的相关性.关节电机角度的跃度也反映了模型对于扰动的鲁棒性,假肢侧的平均跃度为47979 deg/s 3,比健肢侧降低了约31%,表明时滞反馈储备池驱动的步态协同映射方法具有显著的抗扰动能力.本文提出的时滞反馈储备池提高了假肢控制的精度,增强了下肢假肢在不同行走场景下的适应性.
Gait trajectory planning is a critical component in the control of powered lower limb prostheses.In order to achieve coordination between the prosthesis and the intact limb,existing gait trajectory planning methods generally employ data-driven modeling,which directly maps the movement of intact limbs as the reference trajectory of prostheses.However,these methods often suffer from high modeling complexity and poor perturbation resilience.To address this issue,we proposed a novel gait trajectory planning method driven by the delayed feedback reservoir.In this approach,we utilized the Mackey-Glass oscillator as the nonlinear node of the reservoir,with the hip angle of the amputatied side serving as the input.The output is the mapped knee angle of the prosthesis.Notably,the output of the reservoir is the linear superposition of the virtual node states,offering significant advantages in terms of high global convergence and fast convergence speed during training and computing.Furthermore,we deployed the delayed feedback reservoir on the FPGA hardware and utilized serial communication to achieve data interaction with the STM32 microcontroller,allowing for real-time wearability experiments on a powered lower limb prosthesis.The experimental results show that our model achieves a correlation coefficient of 0.8377 between intact limb and prosthesis under normal walking and 0.7436 under perturbation,demonstrating a strong correlation.The jerk value also reflects the model’s robust resistance to perturbations,with an average jerk of 47979 deg/s 3,which is approximately 31%lower than that of the intact limb.This demonstrates that DFR possesses significant perturbation resistance and enhances the adaptability of lower limb prostheses in different walking scenarios.
作者
陆畅
吕阳
张稳
张晓旭
徐鉴
Lu Chang;Lv Yang;Zhang Wen;Zhang Xiaoxu;Xu Jian(Academy for Engineering&Technology,Fudan University,Shanghai 200433,China;MOE Frontiers Center for Brain Science,Fudan University,Shanghai 200433,China;Yiwu Research Institute,Fudan University,Yiwu 322000,China)
出处
《动力学与控制学报》
2025年第5期91-97,共7页
Journal of Dynamics and Control
基金
国家自然科学基金资助项目(12372065,12372022)。
关键词
时滞反馈储备池
数据驱动建模
动力下肢假肢
步态协同
步态控制
delayed feedback reservoir
data-driven modeling
powered lower limb prosthesis
gait coordination
gait control
