{"title":"非线性非最小相位系统输出跟踪的改进最陡下降迭代学习控制","authors":"J. Naiborhu, F. Firman, M. L. Sitanggang","doi":"10.1109/WCICA.2012.6358092","DOIUrl":null,"url":null,"abstract":"Iterative learning control (ILC) refers to a class of self-tuning controllers where the system performance of a specified task is gradually improved or perfected based on the previous performance of identical tasks. In this paper, based on the modified steepest descent control we proposed the iterative learning control algorithm for nonlinear nonminimum phase system. By applying the modified steepest descent control we have the extended system with relative degree greater one than original systems. By extending result of Gosh, cs [1], the convergence of algorithm is guaranteed.","PeriodicalId":114901,"journal":{"name":"Proceedings of the 10th World Congress on Intelligent Control and Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Iterative learning control based on modified steepest descent control for output tracking of nonlinear non-minimum phase systems\",\"authors\":\"J. Naiborhu, F. Firman, M. L. Sitanggang\",\"doi\":\"10.1109/WCICA.2012.6358092\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Iterative learning control (ILC) refers to a class of self-tuning controllers where the system performance of a specified task is gradually improved or perfected based on the previous performance of identical tasks. In this paper, based on the modified steepest descent control we proposed the iterative learning control algorithm for nonlinear nonminimum phase system. By applying the modified steepest descent control we have the extended system with relative degree greater one than original systems. By extending result of Gosh, cs [1], the convergence of algorithm is guaranteed.\",\"PeriodicalId\":114901,\"journal\":{\"name\":\"Proceedings of the 10th World Congress on Intelligent Control and Automation\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 10th World Congress on Intelligent Control and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCICA.2012.6358092\",\"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 10th World Congress on Intelligent Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCICA.2012.6358092","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Iterative learning control based on modified steepest descent control for output tracking of nonlinear non-minimum phase systems
Iterative learning control (ILC) refers to a class of self-tuning controllers where the system performance of a specified task is gradually improved or perfected based on the previous performance of identical tasks. In this paper, based on the modified steepest descent control we proposed the iterative learning control algorithm for nonlinear nonminimum phase system. By applying the modified steepest descent control we have the extended system with relative degree greater one than original systems. By extending result of Gosh, cs [1], the convergence of algorithm is guaranteed.
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