{"title":"随机参数离散双线性系统稳定性","authors":"X. Yang, R. R. Mohler, L. Chen","doi":"10.1109/CDC.1989.70323","DOIUrl":null,"url":null,"abstract":"Stability of discrete, time-varying, stochastic, bilinear systems is studied. Bilinear systems with output feedback are included. Mean-square stability conditions are derived for stochastic models without the assumption of stationarity for the random noise. The feedback function includes a larger class of functions than the class of linear functions or functions satisfying the Lipschitz condition. The sufficient stabilizing conditions depend only on the coefficient matrices of the bilinear system.<<ETX>>","PeriodicalId":156565,"journal":{"name":"Proceedings of the 28th IEEE Conference on Decision and Control,","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Random parameter discrete bilinear system stability\",\"authors\":\"X. Yang, R. R. Mohler, L. Chen\",\"doi\":\"10.1109/CDC.1989.70323\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Stability of discrete, time-varying, stochastic, bilinear systems is studied. Bilinear systems with output feedback are included. Mean-square stability conditions are derived for stochastic models without the assumption of stationarity for the random noise. The feedback function includes a larger class of functions than the class of linear functions or functions satisfying the Lipschitz condition. The sufficient stabilizing conditions depend only on the coefficient matrices of the bilinear system.<<ETX>>\",\"PeriodicalId\":156565,\"journal\":{\"name\":\"Proceedings of the 28th IEEE Conference on Decision and Control,\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1989-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 28th IEEE Conference on Decision and Control,\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.1989.70323\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 28th IEEE Conference on Decision and Control,","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1989.70323","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Random parameter discrete bilinear system stability
Stability of discrete, time-varying, stochastic, bilinear systems is studied. Bilinear systems with output feedback are included. Mean-square stability conditions are derived for stochastic models without the assumption of stationarity for the random noise. The feedback function includes a larger class of functions than the class of linear functions or functions satisfying the Lipschitz condition. The sufficient stabilizing conditions depend only on the coefficient matrices of the bilinear system.<>
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