Iterative learning control in high-performance motion systems: from theory to implementation

Martin Goubej, Sven Meeusen, Noud Mooren, Tom Oomen

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

1 Citaat (Scopus)

Samenvatting

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.

Originele taal-2Engels
TitelProceedings - 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's851-856
Aantal pagina's6
ISBN van elektronische versie978-1-7281-0303-7
DOI's
StatusGepubliceerd - 1 sep 2019
Evenement24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019 - Zaragoza, Spanje
Duur: 10 sep 201913 sep 2019

Congres

Congres24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019
LandSpanje
StadZaragoza
Periode10/09/1913/09/19

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  • Citeer dit

    Goubej, M., Meeusen, S., Mooren, N., & Oomen, T. (2019). Iterative learning control in high-performance motion systems: from theory to implementation. In Proceedings - 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019 (blz. 851-856). [8868996] Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ETFA.2019.8868996