Dynamic Modeling and Identification of Wearable Lower Limb Rehabilitation Exoskeleton Robots

Yang Liu, Jiajun Zhang, W. Liao
{"title":"Dynamic Modeling and Identification of Wearable Lower Limb Rehabilitation Exoskeleton Robots","authors":"Yang Liu, Jiajun Zhang, W. Liao","doi":"10.1109/ICCR55715.2022.10053854","DOIUrl":null,"url":null,"abstract":"Wearable lower limb rehabilitation exoskeleton robots play a positive role in lower limb rehabilitation training and assistance walking for patients with lower limb disorders. Firstly, the 3 degrees of freedom link-based dynamic model with friction is established by the Lagrange method. Secondly, a parameter identification experiment is designed based on a lower limb exoskeleton prototype. It contains three parts: static experiment of discrete controlled by specified position, dynamic experiment of uniform speed motion controlled by linear excitations, and dynamic experiment of continuous motion controlled by sinusoidal excitations. During the process of experiment, several terms in joint output torque expression are set to zero for simplicity of calculation, and leave the parameters to be identified. Furthermore, based on the acquired actuator torque data, nine parameters are identified by plotting and curves fitting with the least square method, including inertial parameters, static friction and Coulomb viscous friction. Finally, the parameter identification results are verified through comparing the torque measured by experiment and estimated by model.","PeriodicalId":441511,"journal":{"name":"2022 4th International Conference on Control and Robotics (ICCR)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 4th International Conference on Control and Robotics (ICCR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCR55715.2022.10053854","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Wearable lower limb rehabilitation exoskeleton robots play a positive role in lower limb rehabilitation training and assistance walking for patients with lower limb disorders. Firstly, the 3 degrees of freedom link-based dynamic model with friction is established by the Lagrange method. Secondly, a parameter identification experiment is designed based on a lower limb exoskeleton prototype. It contains three parts: static experiment of discrete controlled by specified position, dynamic experiment of uniform speed motion controlled by linear excitations, and dynamic experiment of continuous motion controlled by sinusoidal excitations. During the process of experiment, several terms in joint output torque expression are set to zero for simplicity of calculation, and leave the parameters to be identified. Furthermore, based on the acquired actuator torque data, nine parameters are identified by plotting and curves fitting with the least square method, including inertial parameters, static friction and Coulomb viscous friction. Finally, the parameter identification results are verified through comparing the torque measured by experiment and estimated by model.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
可穿戴下肢康复外骨骼机器人动力学建模与辨识
可穿戴式下肢康复外骨骼机器人在下肢障碍患者的下肢康复训练和辅助行走中发挥了积极的作用。首先,采用拉格朗日方法建立了考虑摩擦的3自由度连杆动力学模型;其次,设计了基于下肢外骨骼原型的参数辨识实验。它包括三个部分:指定位置控制的离散运动静态实验、线性激励控制的匀速运动动态实验和正弦激励控制的连续运动动态实验。在实验过程中,为方便计算,将关节输出转矩表达式中的若干项设为零,将参数留待识别。基于获取的作动器转矩数据,利用最小二乘法进行绘图和拟合,确定了惯性参数、静摩擦和库仑粘性摩擦等9个参数。最后,通过对比实验测得的转矩与模型估计的转矩,验证了参数辨识结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Mobile Humanoid Robot Control through Object Movement Imagery Optimization of Two-end Access Platform Automated Warehouse Storage Allocation Long-Tailed Object Mining Based on CLIP Model for Autonomous Driving Node Deployment and Energy Saving Optimization Method for Wireless Sensor Networks Based on Q-learning Off-policy Q-learning-based Tracking Control for Stochastic Linear Discrete-Time Systems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1