Full metadata record
| DC pole | Hodnota | Jazyk |
|---|---|---|
| dc.contributor.author | Goubej, Martin | |
| dc.contributor.author | Meeusen, Sven | |
| dc.contributor.author | Mooren, Noud | |
| dc.contributor.author | Oomen, Tom | |
| dc.date.accessioned | 2020-03-16T11:00:22Z | - |
| dc.date.available | 2020-03-16T11:00:22Z | - |
| dc.date.issued | 2019 | |
| dc.identifier.citation | GOUBEJ, 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.isbn | 978-1-72810-303-7 | |
| dc.identifier.issn | 1946-0740 | |
| dc.identifier.uri | 2-s2.0-85074209777 | |
| dc.identifier.uri | http://hdl.handle.net/11025/36662 | |
| dc.format | 6 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | en |
| dc.relation.ispartofseries | Proceedings 2019 24th IEEE InternationalConference on Emerging Technologiesand Factory Automation (ETFA) | en |
| dc.rights | Plný text je přístupný v rámci univerzity přihlášeným uživatelům. | cs |
| dc.rights | © University of Zaragoza | en |
| dc.title | Iterative learning control in high-performance motion systems: From theory to implementation | en |
| dc.type | konferenční příspěvek | cs |
| dc.type | conferenceObject | en |
| dc.rights.access | restrictedAccess | en |
| dc.type.version | publishedVersion | en |
| dc.description.abstract-translated | Iterative 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.translated | advanced feedforward control | en |
| dc.subject.translated | basis-function ILC | en |
| dc.subject.translated | frequency-domain ILC | en |
| dc.subject.translated | iterative learning control | en |
| dc.subject.translated | motion control | en |
| dc.subject.translated | real-time systems | en |
| dc.identifier.doi | 10.1109/ETFA.2019.8868996 | |
| dc.type.status | Peer-reviewed | en |
| dc.identifier.obd | 43927324 | |
| dc.project.ID | 8A17005/I-MECH Intelligent Motion Control Platform for Smart Mechatronic Systems | cs |
| dc.project.ID | EF17_048/0007267/InteCom: VaV inteligentních komponent pokročilých technologií pro plzeňskou metropolitní oblast | cs |
| Vyskytuje se v kolekcích: | Konferenční příspěvky / Conference Papers (KKY) OBD | |
Soubory připojené k záznamu:
| Soubor | Velikost | Formát | |
|---|---|---|---|
| Goubej_2019_IterativeLearningControl.pdf | 781,92 kB | Adobe PDF | Zobrazit/otevřít Vyžádat kopii |
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