{"title":"自主非线性系统的维数估计","authors":"Alberto Padoan, A. Astolfi","doi":"10.1109/CDC.2015.7402093","DOIUrl":null,"url":null,"abstract":"The problem of estimating the dimension of the state-space of an autonomous nonlinear system is considered. Assuming that sampled measurements of the output and finitely many of its time derivatives are available, an exhaustive search algorithm able to retrieve the dimension of the minimal state-space realization is proposed. The performance of the algorithm are evaluated on specific nonlinear systems.","PeriodicalId":308101,"journal":{"name":"2015 54th IEEE Conference on Decision and Control (CDC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Dimension estimation for autonomous nonlinear systems\",\"authors\":\"Alberto Padoan, A. Astolfi\",\"doi\":\"10.1109/CDC.2015.7402093\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of estimating the dimension of the state-space of an autonomous nonlinear system is considered. Assuming that sampled measurements of the output and finitely many of its time derivatives are available, an exhaustive search algorithm able to retrieve the dimension of the minimal state-space realization is proposed. The performance of the algorithm are evaluated on specific nonlinear systems.\",\"PeriodicalId\":308101,\"journal\":{\"name\":\"2015 54th IEEE Conference on Decision and Control (CDC)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 54th IEEE Conference on Decision and Control (CDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.2015.7402093\",\"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 54th IEEE Conference on Decision and Control (CDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.2015.7402093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Dimension estimation for autonomous nonlinear systems
The problem of estimating the dimension of the state-space of an autonomous nonlinear system is considered. Assuming that sampled measurements of the output and finitely many of its time derivatives are available, an exhaustive search algorithm able to retrieve the dimension of the minimal state-space realization is proposed. The performance of the algorithm are evaluated on specific nonlinear systems.