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dc.contributor.authorGoubej, Martin
dc.contributor.authorMeeusen, Sven
dc.contributor.authorMooren, Noud
dc.contributor.authorOomen, Tom
dc.date.accessioned2020-03-16T11:00:22Z-
dc.date.available2020-03-16T11:00:22Z-
dc.date.issued2019
dc.identifier.citationGOUBEJ, M., MEEUSEN, S., MOOREN, N., OOMEN, T. Iterative learning control in high-performance motion systems: From theory to implementation. In: Proceedings 2019 24th IEEE InternationalConference on Emerging Technologiesand Factory Automation (ETFA). Zaragoza: University of Zaragoza, 2019. s. 851-856. ISBN 978-1-72810-303-7 , ISSN 1946-0740.en
dc.identifier.isbn978-1-72810-303-7
dc.identifier.issn1946-0740
dc.identifier.uri2-s2.0-85074209777
dc.identifier.urihttp://hdl.handle.net/11025/36662
dc.format6 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.relation.ispartofseriesProceedings 2019 24th IEEE InternationalConference on Emerging Technologiesand Factory Automation (ETFA)en
dc.rightsPlný text je přístupný v rámci univerzity přihlášeným uživatelům.cs
dc.rights© University of Zaragozaen
dc.titleIterative learning control in high-performance motion systems: From theory to implementationen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessrestrictedAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedIterative learning control (ILC) enables a perfect compensation for systems that perform the same task over and over again. The aim of this paper is to demonstrate practical applicability of two various state-of-the-art ILC algorithms to point-to-point positioning systems. A simple Frequency domain ILC approach is exploited focusing on systems with exactly repeating motion tasks. Furthermore, flexible ILC is employed to enable learning also for non-repeating tasks. Particular steps providing a seamless transfer from theory and algorithms to practical implementation in a real-time environment by means of industrial-grade SW and HW are given. They may serve as a practical example of a workflow suitable for a wide range of motion control applications. Potential benefits of the learning-type control in comparison with conventional feedback and feedforward control are discussed as well.en
dc.subject.translatedadvanced feedforward controlen
dc.subject.translatedbasis-function ILCen
dc.subject.translatedfrequency-domain ILCen
dc.subject.translatediterative learning controlen
dc.subject.translatedmotion controlen
dc.subject.translatedreal-time systemsen
dc.identifier.doi10.1109/ETFA.2019.8868996
dc.type.statusPeer-revieweden
dc.identifier.obd43927324
dc.project.ID8A17005/I-MECH Intelligent Motion Control Platform for Smart Mechatronic Systemscs
dc.project.IDEF17_048/0007267/InteCom: VaV inteligentních komponent pokročilých technologií pro plzeňskou metropolitní oblastcs
Appears in Collections:Konferenční příspěvky / Conference Papers (KKY)
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