Samenvatting
Cross-coupled iterative learning control (ILC) can achieve high performance for manufacturing applications in which tracking a contour is essential for the quality of a product. The aim of this paper is to develop a framework for norm-optimal cross-coupled ILC that enables the use of exact contour errors that are calculated offline, and iteration-and time-varying weights. Conditions for the monotonic convergence of this iteration-varying ILC algorithm are developed. In addition, a resource-efficient implementation is proposed in which the ILC update law is reframed as a linear quadratic tracking problem, reducing the computational load significantly. The approach is illustrated on a simulation example.
Originele taal-2 | Engels |
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Titel | 61th IEEE Conference on Decision and Control |
Uitgeverij | Institute of Electrical and Electronics Engineers |
Pagina's | 1485-1490 |
Aantal pagina's | 6 |
ISBN van elektronische versie | 978-1-6654-6761-2 |
DOI's | |
Status | Gepubliceerd - 10 jan. 2023 |
Evenement | 2022 IEEE 61st Conference on Decision and Control (CDC) - The Marriott Cancún Collection, Cancun, Mexico Duur: 6 dec. 2022 → 9 dec. 2022 Congresnummer: 61 https://cdc2022.ieeecss.org/ |
Congres
Congres | 2022 IEEE 61st Conference on Decision and Control (CDC) |
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Verkorte titel | CDC 2022 |
Land/Regio | Mexico |
Stad | Cancun |
Periode | 6/12/22 → 9/12/22 |
Internet adres |