{"title":"基于分数阶信息过滤器的分数阶状态空间正则模型识别","authors":"B. Safarinejadian, M. Asad","doi":"10.1109/AISP.2015.7123479","DOIUrl":null,"url":null,"abstract":"In the present paper the identification and estimation problem of a fractional order state space system will be addressed. This paper presents a fractional order information filter and also a hierarchical identification algorithm to identify and estimate parameters and states of a fractional order system. Then, merging this algorithm with fractional order information filter, a novel identification method based on hierarchical identification theory is introduced to reduce the computational complexity. Finally, the applicability and performance of this platform on an exemplary system is examined.","PeriodicalId":405857,"journal":{"name":"2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP)","volume":"65 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Fractional order state space canonical model identification using fractional order information filter\",\"authors\":\"B. Safarinejadian, M. Asad\",\"doi\":\"10.1109/AISP.2015.7123479\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the present paper the identification and estimation problem of a fractional order state space system will be addressed. This paper presents a fractional order information filter and also a hierarchical identification algorithm to identify and estimate parameters and states of a fractional order system. Then, merging this algorithm with fractional order information filter, a novel identification method based on hierarchical identification theory is introduced to reduce the computational complexity. Finally, the applicability and performance of this platform on an exemplary system is examined.\",\"PeriodicalId\":405857,\"journal\":{\"name\":\"2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP)\",\"volume\":\"65 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 The International Symposium on Artificial Intelligence and Signal Processing (AISP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AISP.2015.7123479\",\"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 The International Symposium on Artificial Intelligence and Signal Processing (AISP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AISP.2015.7123479","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fractional order state space canonical model identification using fractional order information filter
In the present paper the identification and estimation problem of a fractional order state space system will be addressed. This paper presents a fractional order information filter and also a hierarchical identification algorithm to identify and estimate parameters and states of a fractional order system. Then, merging this algorithm with fractional order information filter, a novel identification method based on hierarchical identification theory is introduced to reduce the computational complexity. Finally, the applicability and performance of this platform on an exemplary system is examined.