Zihao Xu, Weiqun Wang, Z. Hou, Xiaoming Lin, Xu Liang
{"title":"Dynamic model based fuzzy-impedance interaction control for rehabilitation robots","authors":"Zihao Xu, Weiqun Wang, Z. Hou, Xiaoming Lin, Xu Liang","doi":"10.1109/ROBIO.2017.8324643","DOIUrl":null,"url":null,"abstract":"During the robot assisted active rehabilitation training, it is very important to adaptively adjust the interaction force between the robot and limbs, online. Aiming at this problem, a fuzzy-impedance control strategy is proposed. First, the difference between the estimated and the measured forces is used to represent the human-robot interaction force. The estimated force is based on rehabilitation robot dynamic model. Then, an adaptive algorithm based on fuzzy logic is presented for adjusting the impedance parameters, including stiffness and damping. Specifically, the interaction force and position errors are used to adjust stiffness, and the interaction force and velocity errors to damping. Finally, the feasibility of the proposed algorithm is verified by the simulation experiment.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBIO.2017.8324643","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
During the robot assisted active rehabilitation training, it is very important to adaptively adjust the interaction force between the robot and limbs, online. Aiming at this problem, a fuzzy-impedance control strategy is proposed. First, the difference between the estimated and the measured forces is used to represent the human-robot interaction force. The estimated force is based on rehabilitation robot dynamic model. Then, an adaptive algorithm based on fuzzy logic is presented for adjusting the impedance parameters, including stiffness and damping. Specifically, the interaction force and position errors are used to adjust stiffness, and the interaction force and velocity errors to damping. Finally, the feasibility of the proposed algorithm is verified by the simulation experiment.