{"title":"单连杆机械臂的自适应指数渐近跟踪控制","authors":"Yanjun Liang, Yuanxin Li","doi":"10.1109/DDCLS52934.2021.9455678","DOIUrl":null,"url":null,"abstract":"This article addresses the asymptotic tracking issues of a one-link manipulator system. To realize the exponentially asymptotic tracking performance, the exponential term has been introduced into the Lyapunov function and the bounds estimation method and the smooth modification function are used to guarantee the zero-error tracking. In addition, the neural networks (NNs) is devised to cope with the uncertain disturbance and unknown nonlinearlities. At last, a simulation example has been shown to verify the raised scheme.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive exponentially asymptotic tracking control for a one-link manipulator\",\"authors\":\"Yanjun Liang, Yuanxin Li\",\"doi\":\"10.1109/DDCLS52934.2021.9455678\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article addresses the asymptotic tracking issues of a one-link manipulator system. To realize the exponentially asymptotic tracking performance, the exponential term has been introduced into the Lyapunov function and the bounds estimation method and the smooth modification function are used to guarantee the zero-error tracking. In addition, the neural networks (NNs) is devised to cope with the uncertain disturbance and unknown nonlinearlities. At last, a simulation example has been shown to verify the raised scheme.\",\"PeriodicalId\":325897,\"journal\":{\"name\":\"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DDCLS52934.2021.9455678\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DDCLS52934.2021.9455678","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive exponentially asymptotic tracking control for a one-link manipulator
This article addresses the asymptotic tracking issues of a one-link manipulator system. To realize the exponentially asymptotic tracking performance, the exponential term has been introduced into the Lyapunov function and the bounds estimation method and the smooth modification function are used to guarantee the zero-error tracking. In addition, the neural networks (NNs) is devised to cope with the uncertain disturbance and unknown nonlinearlities. At last, a simulation example has been shown to verify the raised scheme.