{"title":"测量不确定条件下双线性系统镇定的序贯预测","authors":"I. Bhogaraju, M. Farasat, Michael A. Malisoff","doi":"10.1109/CDC45484.2021.9682965","DOIUrl":null,"url":null,"abstract":"We build delay-compensating feedback controls for a class of nonlinear systems that include bilinear systems with arbitrarily long known constant input delays. Unlike prior sequential predictor work, we cover bilinear systems whose state measurements have uncertainty, and we prove input-to-state stability with respect to the uncertainty. We do not require constructing or estimating distributed terms in the controls. We illustrate our result in a power systems example.","PeriodicalId":229089,"journal":{"name":"2021 60th IEEE Conference on Decision and Control (CDC)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sequential Predictors for Stabilization of Bilinear Systems under Measurement Uncertainty\",\"authors\":\"I. Bhogaraju, M. Farasat, Michael A. Malisoff\",\"doi\":\"10.1109/CDC45484.2021.9682965\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We build delay-compensating feedback controls for a class of nonlinear systems that include bilinear systems with arbitrarily long known constant input delays. Unlike prior sequential predictor work, we cover bilinear systems whose state measurements have uncertainty, and we prove input-to-state stability with respect to the uncertainty. We do not require constructing or estimating distributed terms in the controls. We illustrate our result in a power systems example.\",\"PeriodicalId\":229089,\"journal\":{\"name\":\"2021 60th IEEE Conference on Decision and Control (CDC)\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 60th IEEE Conference on Decision and Control (CDC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC45484.2021.9682965\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 60th IEEE Conference on Decision and Control (CDC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC45484.2021.9682965","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sequential Predictors for Stabilization of Bilinear Systems under Measurement Uncertainty
We build delay-compensating feedback controls for a class of nonlinear systems that include bilinear systems with arbitrarily long known constant input delays. Unlike prior sequential predictor work, we cover bilinear systems whose state measurements have uncertainty, and we prove input-to-state stability with respect to the uncertainty. We do not require constructing or estimating distributed terms in the controls. We illustrate our result in a power systems example.