{"title":"自适应非线性跟踪方法在运动跟踪中的应用","authors":"V. Gromov, Aleksei V. Meshkov, A. Pyrkin","doi":"10.1109/NIR50484.2020.9290163","DOIUrl":null,"url":null,"abstract":"The problem of output regulation for systems affected by nonlinear reference signal, which is caused by exosystem with parametric uncertainties, is addressed. The control law for a nonlinear trajectory is proposed with the design of an adaptive internal model. The efficiency of the proposed algorithm was proved by experiments using the setup that includes an articulated robot. The experimental results are presented.","PeriodicalId":274976,"journal":{"name":"2020 International Conference Nonlinearity, Information and Robotics (NIR)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive Nonlinear Tracking Approach for Motion Tracking Applications\",\"authors\":\"V. Gromov, Aleksei V. Meshkov, A. Pyrkin\",\"doi\":\"10.1109/NIR50484.2020.9290163\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of output regulation for systems affected by nonlinear reference signal, which is caused by exosystem with parametric uncertainties, is addressed. The control law for a nonlinear trajectory is proposed with the design of an adaptive internal model. The efficiency of the proposed algorithm was proved by experiments using the setup that includes an articulated robot. The experimental results are presented.\",\"PeriodicalId\":274976,\"journal\":{\"name\":\"2020 International Conference Nonlinearity, Information and Robotics (NIR)\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference Nonlinearity, Information and Robotics (NIR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NIR50484.2020.9290163\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference Nonlinearity, Information and Robotics (NIR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NIR50484.2020.9290163","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive Nonlinear Tracking Approach for Motion Tracking Applications
The problem of output regulation for systems affected by nonlinear reference signal, which is caused by exosystem with parametric uncertainties, is addressed. The control law for a nonlinear trajectory is proposed with the design of an adaptive internal model. The efficiency of the proposed algorithm was proved by experiments using the setup that includes an articulated robot. The experimental results are presented.