下肢软质康复外骨骼机器人的模糊神经网络阻抗控制

doi:10.13973/j.cnki.robot.190489

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张玉明, 吴青聪, 陈柏, 吴洪涛, 刘焕瑞. 下肢软质康复外骨骼机器人的模糊神经网络阻抗控制[J]. 机器人, 2020, 42(4): 477-484,493.DOI: 10.13973/j.cnki.robot.190489. ZHANG Yuming, WU Qingcong, CHEN Bai, WU Hongtao, LIU Huanrui. Fuzzy Neural Network Impedance Control of Soft Lower Limb RehabilitationExoskeleton Robot. ROBOT, 2020, 42(4): 477-484,493. DOI: 10.13973/j.cnki.robot.190489.

摘要针对脑卒中或交通意外等因素导致的运动功能障碍问题，设计了一种可用于康复训练的可穿戴式的软质膝关节外骨骼机器人．在重点介绍基于Hill肌肉模型的套索人工肌肉驱动系统设计和实时控制平台的基础上，分析了模糊神经网络阻抗控制算法的推导过程．最后，分别在定阻抗与变阻抗参数控制策略条件下，进行人机协同训练模式下的康复训练实验，并对比分析了康复外骨骼系统对受试者肌肉活性的影响．实验结果表明，定频率定幅值训练时的屈/伸扭矩分别增加了9.70%和9.06%，而变频率变幅值训练时的屈/伸扭矩提升了88.34%和57.68%．由此可知，选择符合人体生理肌肉刚度特性的阻抗模型可以改善下肢康复机器人系统的稳定性和安全性，提高人机交互的柔顺性和协调性．

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	张玉明
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关键词 ：下肢, 软质康复机器人, Hill肌肉模型, 模糊神经网络, 阻抗控制, 人机交互

Abstract：To solve the motor dysfunction due to the stroke or the traffic accidents, a wearable soft knee exoskeleton robot for rehabilitation training is designed. Based on the emphatic introduction of the Hill-muscle-model-based tendon-sheath artificial muscle drive system design and real-time control platform, the derivation process of the fuzzy neural network impedance control algorithm is analyzed. Finally, the rehabilitation training experiment is carried out in the human-machine cooperative training mode, in the conditions of the fixed and the variable impedance parameter control strategies. The influence of the rehabilitation exoskeleton system on the muscle activity of subjects is also compared and analyzed. The experimental results show that the flexor/extensor torques are increased by 9.70% and 9.06% during the constant frequency and amplitude training, and the flexor/extensor torques are increased by 88.34% and 57.68% during variable frequency and amplitude training. Therefore, the stability and the safety of the lower limb rehabilitation robot can be enhanced by selecting the suitable impedance model that conforms to the physiological muscle stiffness characteristics, as well as the human-robot interactive compliance and coordination can be improved.

Key words： lower limb soft rehabilitation robot Hill muscle model fuzzy neural network impedance control human-robot interaction

收稿日期: 2019-09-09 录用日期: 2020-02-19

TP24

基金资助:国家自然科学基金（51705240）；中国博士后科学基金（2018M640480）；江苏省自然科学基金（BK20170783）；机器人技术与系统国家重点实验室开放研究项目（SKLRS-2018-KF-10）

通讯作者: 吴青聪,wuqc@nuaa.edu.cn E-mail: wuqc@nuaa.edu.cn

作者简介: 张玉明(1995-),男,硕士.研究领域:机器人运动控制,康复机器人,智能机器人等.
吴青聪(1988-),男,博士,讲师.研究领域:机器人动力学及其控制,先进医疗器械,康复机器人等.

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https://robot.sia.cn/CN/10.13973/j.cnki.robot.190489 或 https://robot.sia.cn/CN/Y2020/V42/I4/477

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