Jin Feng, Fei Yu, Na Yang, Pengyu Zhang, Wei Gao, Xin Zhang
{"title":"多不确定系统的Krein空间鲁棒滤波方法","authors":"Jin Feng, Fei Yu, Na Yang, Pengyu Zhang, Wei Gao, Xin Zhang","doi":"10.1109/ICAL.2011.6024732","DOIUrl":null,"url":null,"abstract":"In this paper, a new Krein space approach to robust filtering for linear systems with multiple uncertainties is developed. The multiple uncertainties satisfy the energy-type constraints, entering into both state and measurement equations. The proposed approach is used to tackle the sub-optimization problem arising from a sum quadratic constraint (SQC) of system uncertainties. To this end, a novel Krein space formal system is designed. Then recursive estimation is derived from the formal system. Also, the necessary and sufficient condition for the estimation to be optimal is proposed. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach.","PeriodicalId":351518,"journal":{"name":"2011 IEEE International Conference on Automation and Logistics (ICAL)","volume":"115 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Krein space approach to robust filtering for multiple uncertain systems\",\"authors\":\"Jin Feng, Fei Yu, Na Yang, Pengyu Zhang, Wei Gao, Xin Zhang\",\"doi\":\"10.1109/ICAL.2011.6024732\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new Krein space approach to robust filtering for linear systems with multiple uncertainties is developed. The multiple uncertainties satisfy the energy-type constraints, entering into both state and measurement equations. The proposed approach is used to tackle the sub-optimization problem arising from a sum quadratic constraint (SQC) of system uncertainties. To this end, a novel Krein space formal system is designed. Then recursive estimation is derived from the formal system. Also, the necessary and sufficient condition for the estimation to be optimal is proposed. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach.\",\"PeriodicalId\":351518,\"journal\":{\"name\":\"2011 IEEE International Conference on Automation and Logistics (ICAL)\",\"volume\":\"115 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Conference on Automation and Logistics (ICAL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAL.2011.6024732\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Automation and Logistics (ICAL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAL.2011.6024732","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Krein space approach to robust filtering for multiple uncertain systems
In this paper, a new Krein space approach to robust filtering for linear systems with multiple uncertainties is developed. The multiple uncertainties satisfy the energy-type constraints, entering into both state and measurement equations. The proposed approach is used to tackle the sub-optimization problem arising from a sum quadratic constraint (SQC) of system uncertainties. To this end, a novel Krein space formal system is designed. Then recursive estimation is derived from the formal system. Also, the necessary and sufficient condition for the estimation to be optimal is proposed. Finally, a numerical example is given to demonstrate the effectiveness of the proposed approach.