{"title":"一类广义系统的故障估计——一种自适应鲁棒扩展卡尔曼滤波方法","authors":"Liang Kexin, Li Tiantian","doi":"10.1109/ICMCCE51767.2020.00279","DOIUrl":null,"url":null,"abstract":"This paper proposes an adaptive Robust Extended Klaman filter for a class of non-linear descriptor systems with unknown system noise. Firstly, a robust bound is given to decrease the influence of the linearization error on the estimation accuracy; an adaptive algorithm is introduced to implement an unbiased estimation of the noise, then; an numeral example is given to show the effectiveness of the method at last.","PeriodicalId":6712,"journal":{"name":"2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)","volume":"40 1","pages":"1274-1278"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fault Estimation for A Class of Descriptor Systems - An Adaptive Robust Extended Kalman Filter Approach\",\"authors\":\"Liang Kexin, Li Tiantian\",\"doi\":\"10.1109/ICMCCE51767.2020.00279\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an adaptive Robust Extended Klaman filter for a class of non-linear descriptor systems with unknown system noise. Firstly, a robust bound is given to decrease the influence of the linearization error on the estimation accuracy; an adaptive algorithm is introduced to implement an unbiased estimation of the noise, then; an numeral example is given to show the effectiveness of the method at last.\",\"PeriodicalId\":6712,\"journal\":{\"name\":\"2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)\",\"volume\":\"40 1\",\"pages\":\"1274-1278\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMCCE51767.2020.00279\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMCCE51767.2020.00279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fault Estimation for A Class of Descriptor Systems - An Adaptive Robust Extended Kalman Filter Approach
This paper proposes an adaptive Robust Extended Klaman filter for a class of non-linear descriptor systems with unknown system noise. Firstly, a robust bound is given to decrease the influence of the linearization error on the estimation accuracy; an adaptive algorithm is introduced to implement an unbiased estimation of the noise, then; an numeral example is given to show the effectiveness of the method at last.