{"title":"A new approach in estimating the dynamics matrix of a system","authors":"A. El-Sinawi","doi":"10.1109/NAECON.1998.710093","DOIUrl":null,"url":null,"abstract":"This paper presents a new approach in estimating the parameters of a dynamic system from an initial and relatively inaccurate state-space model. The proposed approach is based on determining an optimal control law that minimizes a quadratic performance index for a free final state condition by means of solving a two-point boundary-value problem. The control input to both the model and the physical system is assumed to be the difference between their outputs. The proposed approach is applied to a second order system that has a modeling error of about 40%. The new approach succeeded in reducing the modeling error to about 5%.","PeriodicalId":202280,"journal":{"name":"Proceedings of the IEEE 1998 National Aerospace and Electronics Conference. NAECON 1998. Celebrating 50 Years (Cat. No.98CH36185)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE 1998 National Aerospace and Electronics Conference. NAECON 1998. Celebrating 50 Years (Cat. No.98CH36185)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAECON.1998.710093","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 presents a new approach in estimating the parameters of a dynamic system from an initial and relatively inaccurate state-space model. The proposed approach is based on determining an optimal control law that minimizes a quadratic performance index for a free final state condition by means of solving a two-point boundary-value problem. The control input to both the model and the physical system is assumed to be the difference between their outputs. The proposed approach is applied to a second order system that has a modeling error of about 40%. The new approach succeeded in reducing the modeling error to about 5%.