{"title":"基于最小二乘技术和工具变量的非整数阶模型估计:Hn模型","authors":"A. Khadhraoui, K. Jelassi, J. Trigeassou","doi":"10.1109/STA.2015.7505104","DOIUrl":null,"url":null,"abstract":"This contribution has as its goal to identify of fractional order systems using least-squares (LS) and instrumental variable (IV) technique. System estimation can be considered as a necessary step in control theory. We introduce, in this paper, a new technique that permits us to estimate non-integer model. This method employs a linearization technique to find a linear equation, and then estimates unknown parameters using least squares approach. In noisy output context, this method offers a biased estimation; the proposed solution is to use a new approach of instrumental variable technique. Different simulations test are presented.","PeriodicalId":128530,"journal":{"name":"2015 16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimation of non-integer order model based on least-squares technique and instrumental variables: Hn model\",\"authors\":\"A. Khadhraoui, K. Jelassi, J. Trigeassou\",\"doi\":\"10.1109/STA.2015.7505104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This contribution has as its goal to identify of fractional order systems using least-squares (LS) and instrumental variable (IV) technique. System estimation can be considered as a necessary step in control theory. We introduce, in this paper, a new technique that permits us to estimate non-integer model. This method employs a linearization technique to find a linear equation, and then estimates unknown parameters using least squares approach. In noisy output context, this method offers a biased estimation; the proposed solution is to use a new approach of instrumental variable technique. Different simulations test are presented.\",\"PeriodicalId\":128530,\"journal\":{\"name\":\"2015 16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)\",\"volume\":\"111 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/STA.2015.7505104\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STA.2015.7505104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimation of non-integer order model based on least-squares technique and instrumental variables: Hn model
This contribution has as its goal to identify of fractional order systems using least-squares (LS) and instrumental variable (IV) technique. System estimation can be considered as a necessary step in control theory. We introduce, in this paper, a new technique that permits us to estimate non-integer model. This method employs a linearization technique to find a linear equation, and then estimates unknown parameters using least squares approach. In noisy output context, this method offers a biased estimation; the proposed solution is to use a new approach of instrumental variable technique. Different simulations test are presented.