{"title":"线性动态系统的模糊状态估计","authors":"H. Sira-Ramírez","doi":"10.1109/CDC.1980.271820","DOIUrl":null,"url":null,"abstract":"The problem of state estimation in linear dynamic systems with fuzzy initial states and poorly defined perturbation input signals (i.e fuzzy inputs) is considered. A new notion of vector summ of n-dimensional fuzzy sets provides the basis for state and input \"imprecision\" propagation trough the systems dynamics. Recursive state estimation formulae are developed to obtain a fuzzy set of possible states at each instant of time.","PeriodicalId":332964,"journal":{"name":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","volume":"2619 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1980-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Fuzzy state estimation in linear dynamic systems\",\"authors\":\"H. Sira-Ramírez\",\"doi\":\"10.1109/CDC.1980.271820\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of state estimation in linear dynamic systems with fuzzy initial states and poorly defined perturbation input signals (i.e fuzzy inputs) is considered. A new notion of vector summ of n-dimensional fuzzy sets provides the basis for state and input \\\"imprecision\\\" propagation trough the systems dynamics. Recursive state estimation formulae are developed to obtain a fuzzy set of possible states at each instant of time.\",\"PeriodicalId\":332964,\"journal\":{\"name\":\"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes\",\"volume\":\"2619 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1980-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CDC.1980.271820\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CDC.1980.271820","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The problem of state estimation in linear dynamic systems with fuzzy initial states and poorly defined perturbation input signals (i.e fuzzy inputs) is considered. A new notion of vector summ of n-dimensional fuzzy sets provides the basis for state and input "imprecision" propagation trough the systems dynamics. Recursive state estimation formulae are developed to obtain a fuzzy set of possible states at each instant of time.