Searching Optimal Values of Identification and Controller Design Horizon Lengths, and Regularization Parameters in NARMA Based Online Learning Controller Design

dc.contributor.author	Toprak, T.
dc.contributor.author	Sahin, S.
dc.contributor.author	Soydemir, M.U.
dc.contributor.author	Bulucu, P.
dc.contributor.author	Kocaoglu, A.
dc.date.accessioned	2021-01-25T19:32:52Z
dc.date.available	2021-01-25T19:32:52Z
dc.date.issued	2019
dc.identifier.issn	Guzelis, C.
dc.identifier.uri	https://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/7452
dc.description.abstract	This paper presents an analysis on searching the optimal values of the system identification and tracking window lengths, and regularization parameter for the online learning NARMA controller algorithm. Both window lengths and regularization parameter are
dc.description.sponsorship	Scientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [116E170]
dc.language.iso	English
dc.publisher	IEEE
dc.title	Searching Optimal Values of Identification and Controller Design Horizon Lengths, and Regularization Parameters in NARMA Based Online Learning Controller Design
dc.type	Proceedings Paper
dc.relation.firstpage	800
dc.relation.lastpage	804
dc.description.woscategory	Engineering, Electrical & Electronic
dc.description.wosresearcharea	Engineering
dc.identifier.wosid	WOS:000552654100161
dc.identifier.ctitle	11th International Conference on Electrical and Electronics Engineering (ELECO)
dc.identifier.cdate	NOV 28-30, 2019

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