{"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}
引用次数: 0
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.