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

Martin Goubej; Sven Meeusen; Noud Mooren; Tom Oomen

doi:10.1109/ETFA.2019.8868996

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

Martin Goubej, Sven Meeusen, Noud Mooren, Tom Oomen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

6 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Proceedings - 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Pages	851-856
Number of pages	6
ISBN (Electronic)	978-1-7281-0303-7
DOIs	https://doi.org/10.1109/ETFA.2019.8868996
Publication status	Published - 1 Sept 2019
Event	24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019 - Zaragoza, Spain Duration: 10 Sept 2019 → 13 Sept 2019

Conference

Conference	24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019
Country/Territory	Spain
City	Zaragoza
Period	10/09/19 → 13/09/19

Keywords

advanced feedforward control
basis-function ILC
frequency-domain ILC
iterative learning control
motion control
real-time systems

Access to Document

10.1109/ETFA.2019.8868996

Cite this

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 (pp. 851-856). [8868996] Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ETFA.2019.8868996

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abstract = "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.",

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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., 8868996, Institute of Electrical and Electronics Engineers, Piscataway, pp. 851-856, 24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019, Zaragoza, Spain, 10/09/19. https://doi.org/10.1109/ETFA.2019.8868996

Iterative learning control in high-performance motion systems : from theory to implementation. / Goubej, Martin; Meeusen, Sven; Mooren, Noud et al.

Proceedings - 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019. Piscataway : Institute of Electrical and Electronics Engineers, 2019. p. 851-856 8868996.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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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 International Conference on Emerging Technologies and Factory Automation, ETFA 2019. Piscataway: Institute of Electrical and Electronics Engineers. 2019. p. 851-856. 8868996 doi: 10.1109/ETFA.2019.8868996

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

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