{"title":"具有任意初始状态的奇异系统的迭代学习控制","authors":"Mengji Chen, Yinjun Zhang, Jianhuan Su","doi":"10.1109/DDCLS.2018.8515976","DOIUrl":null,"url":null,"abstract":"In this paper, a class of a class linear singular system with an arbitrary initial state was proposed based on singular value decomposition. A novel generalized theoretical result is presented by using the D-type learning law. We established the convergence conditions of algorithm. By the matrix theory, we give rigorous convergence proof. The effectiveness of the theoretical result is illustrated in two application examples.","PeriodicalId":6565,"journal":{"name":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"58 1","pages":"141-144"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Iterative Learning Control for Singular System with An Arbitrary Initial State\",\"authors\":\"Mengji Chen, Yinjun Zhang, Jianhuan Su\",\"doi\":\"10.1109/DDCLS.2018.8515976\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a class of a class linear singular system with an arbitrary initial state was proposed based on singular value decomposition. A novel generalized theoretical result is presented by using the D-type learning law. We established the convergence conditions of algorithm. By the matrix theory, we give rigorous convergence proof. The effectiveness of the theoretical result is illustrated in two application examples.\",\"PeriodicalId\":6565,\"journal\":{\"name\":\"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)\",\"volume\":\"58 1\",\"pages\":\"141-144\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DDCLS.2018.8515976\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 7th Data Driven Control and Learning Systems Conference (DDCLS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DDCLS.2018.8515976","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Iterative Learning Control for Singular System with An Arbitrary Initial State
In this paper, a class of a class linear singular system with an arbitrary initial state was proposed based on singular value decomposition. A novel generalized theoretical result is presented by using the D-type learning law. We established the convergence conditions of algorithm. By the matrix theory, we give rigorous convergence proof. The effectiveness of the theoretical result is illustrated in two application examples.
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