{"title":"连续分数卡尔曼滤波","authors":"M. Aoun, S. Najar, M. Abdelhamid, M. Abdelkrim","doi":"10.1109/SSD.2012.6198068","DOIUrl":null,"url":null,"abstract":"This paper develops a new Kalman filter for linear systems described with continuous time fractional model. It extends the classical Kalman filter to deals with fractional differentiation. It is called continuous fractional Kalman Filter. The algorithm of the new filter is detailed and a suboptimal filter can be deduced. A numerical example illustrates the state estimation of a fractional model with the new filter.","PeriodicalId":425823,"journal":{"name":"International Multi-Conference on Systems, Sygnals & Devices","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Continuous fractional Kalman filter\",\"authors\":\"M. Aoun, S. Najar, M. Abdelhamid, M. Abdelkrim\",\"doi\":\"10.1109/SSD.2012.6198068\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper develops a new Kalman filter for linear systems described with continuous time fractional model. It extends the classical Kalman filter to deals with fractional differentiation. It is called continuous fractional Kalman Filter. The algorithm of the new filter is detailed and a suboptimal filter can be deduced. A numerical example illustrates the state estimation of a fractional model with the new filter.\",\"PeriodicalId\":425823,\"journal\":{\"name\":\"International Multi-Conference on Systems, Sygnals & Devices\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Multi-Conference on Systems, Sygnals & Devices\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SSD.2012.6198068\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Multi-Conference on Systems, Sygnals & Devices","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSD.2012.6198068","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper develops a new Kalman filter for linear systems described with continuous time fractional model. It extends the classical Kalman filter to deals with fractional differentiation. It is called continuous fractional Kalman Filter. The algorithm of the new filter is detailed and a suboptimal filter can be deduced. A numerical example illustrates the state estimation of a fractional model with the new filter.
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