{"title":"Least Squares Based Iterative Parameter Estimation Algorithm for State Space Model with Time-Delay","authors":"Gu Ya, Chou Yongxin, Ding Wei, L. Jicheng","doi":"10.23919/CHICC.2018.8483727","DOIUrl":null,"url":null,"abstract":"This paper researches parameter estimation problem for state space systems with time-delay. Combing the linear transformation and the property of the shift operator, the state space model with time-delay can be equivalent to the input-output representation and then can be transformed into the identification model. The least squares based iterative parameter estimation algorithm is raised to identify the system with time-delay and makes full use of all data at each iteration and thus can generate highly accurate parameter estimates. Finally, the example is provided to validate the proposed theorems.","PeriodicalId":158442,"journal":{"name":"2018 37th Chinese Control Conference (CCC)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 37th Chinese Control Conference (CCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/CHICC.2018.8483727","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 paper researches parameter estimation problem for state space systems with time-delay. Combing the linear transformation and the property of the shift operator, the state space model with time-delay can be equivalent to the input-output representation and then can be transformed into the identification model. The least squares based iterative parameter estimation algorithm is raised to identify the system with time-delay and makes full use of all data at each iteration and thus can generate highly accurate parameter estimates. Finally, the example is provided to validate the proposed theorems.