{"title":"扩展双线性状态空间模型的辨识","authors":"A. Schrempf, L. Re","doi":"10.1109/CDC.2001.980572","DOIUrl":null,"url":null,"abstract":"An identification algorithm for a special model class which captures essential characteristics of many nonlinear systems is presented. Conditions are given under which this nonlinear model can be identified by use of efficient linear tools. Subspace identification is used to determine the linear part of the model and an initial estimate for the nonlinear one. The estimate of the nonlinear part is computed by a final numerical optimization step. A simulation study illustrates the applicability of the proposed method.","PeriodicalId":131411,"journal":{"name":"Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Identification of extended bilinear state space models\",\"authors\":\"A. Schrempf, L. Re\",\"doi\":\"10.1109/CDC.2001.980572\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An identification algorithm for a special model class which captures essential characteristics of many nonlinear systems is presented. Conditions are given under which this nonlinear model can be identified by use of efficient linear tools. Subspace identification is used to determine the linear part of the model and an initial estimate for the nonlinear one. The estimate of the nonlinear part is computed by a final numerical optimization step. A simulation study illustrates the applicability of the proposed method.\",\"PeriodicalId\":131411,\"journal\":{\"name\":\"Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-12-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.2001.980572\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.2001.980572","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identification of extended bilinear state space models
An identification algorithm for a special model class which captures essential characteristics of many nonlinear systems is presented. Conditions are given under which this nonlinear model can be identified by use of efficient linear tools. Subspace identification is used to determine the linear part of the model and an initial estimate for the nonlinear one. The estimate of the nonlinear part is computed by a final numerical optimization step. A simulation study illustrates the applicability of the proposed method.