Iterative Learning Control — Algorithms, Applications and Future Research Directions

Eric Rogers; Bing Chu; Kevin  Moore; Tom A.E. Oomen; Ying Tan

doi:10.1109/CDC56724.2024.10886288

Iterative Learning Control — Algorithms, Applications and Future Research Directions

Eric Rogers, Bing Chu, Kevin Moore, Tom A.E. Oomen, Ying Tan

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

2 Citaten (Scopus)

9737 Downloads (Pure)

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This paper gives a tutorial on iterative learning control nearly five decades after what is widely regarded as the first substantive paper in the literature. The focus is on algo- rithm development under a number of general headings (linear, optimization, frequency domain, and nonlinear), together with supporting experimental validation/industrial applications and also applications in healthcare.

Originele taal-2	Engels
Titel	2024 IEEE 63rd Conference on Decision and Control, CDC 2024
Uitgeverij	Institute of Electrical and Electronics Engineers
Pagina's	2252-2268
Aantal pagina's	17
ISBN van elektronische versie	979-8-3503-1633-9
DOI's	https://doi.org/10.1109/CDC56724.2024.10886288
Status	Gepubliceerd - 26 feb. 2025
Evenement	63rd IEEE Annual Conference on Decision and Control, CDC 2024 - Milan, Italië Duur: 16 dec. 2024 → 19 dec. 2024

Congres

Congres	63rd IEEE Annual Conference on Decision and Control, CDC 2024
Land/Regio	Italië
Stad	Milan
Periode	16/12/24 → 19/12/24

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10.1109/CDC56724.2024.10886288

pdfDefinitieve gepubliceerde versie, 1,02 MBLicentie: TAVERNE
RogersChuMooOomTan2024Licentie: Anders

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title = "Iterative Learning Control — Algorithms, Applications and Future Research Directions",

abstract = "This paper gives a tutorial on iterative learning control nearly five decades after what is widely regarded as the first substantive paper in the literature. The focus is on algo- rithm development under a number of general headings (linear, optimization, frequency domain, and nonlinear), together with supporting experimental validation/industrial applications and also applications in healthcare.",

author = "Eric Rogers and Bing Chu and Kevin Moore and Oomen, \{Tom A.E.\} and Ying Tan",

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day = "26",

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booktitle = "2024 IEEE 63rd Conference on Decision and Control, CDC 2024",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "63rd IEEE Annual Conference on Decision and Control, CDC 2024 ; Conference date: 16-12-2024 Through 19-12-2024",

}

Rogers, E, Chu, B, Moore, K, Oomen, TAE & Tan, Y 2025, Iterative Learning Control — Algorithms, Applications and Future Research Directions. in 2024 IEEE 63rd Conference on Decision and Control, CDC 2024., 10886288, Institute of Electrical and Electronics Engineers, blz. 2252-2268, 63rd IEEE Annual Conference on Decision and Control, CDC 2024, Milan, Italië, 16/12/24. https://doi.org/10.1109/CDC56724.2024.10886288

Iterative Learning Control — Algorithms, Applications and Future Research Directions. / Rogers, Eric; Chu, Bing; Moore, Kevin et al.
2024 IEEE 63rd Conference on Decision and Control, CDC 2024. Institute of Electrical and Electronics Engineers, 2025. blz. 2252-2268 10886288.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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AB - This paper gives a tutorial on iterative learning control nearly five decades after what is widely regarded as the first substantive paper in the literature. The focus is on algo- rithm development under a number of general headings (linear, optimization, frequency domain, and nonlinear), together with supporting experimental validation/industrial applications and also applications in healthcare.

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Iterative Learning Control — Algorithms, Applications and Future Research Directions

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Congres

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