Accommodating trial-varying tasks in iterative learning control for LPV systems, applied to printer sheet positioning

Robin de Rozario, Remy Pelzer, Sjirk Koekcbakker, Tom Oomen

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

4 Citaten (Scopus)
3 Downloads (Pure)

Samenvatting

Many control applications are nonlinear and have to perform a range of different tasks. Iterative Learning Control (ILC) enables high performance for a single task, but is highly sensitive to task variations. The aim of this paper is to develop an ILC framework for Linear Parameter Varying (LPV) systems, which encompasses a large class of nonlinear systems, which allows for trial-varying reference signals. This is achieved by exploiting parameter varying basis functions, such that perfect tracking is enabled for LPV systems. The proposed approach is applied to a printer sheet positioning unit, thereby validating that the tracking performance is significantly enhanced with respect to existing approaches.

Originele taal-2Engels
Titel2018 Annual American Control Conference, ACC 2018
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's5213-5218
Aantal pagina's6
ISBN van geprinte versie9781538654286
DOI's
StatusGepubliceerd - 9 aug 2018
Evenement2018 American Control Conference (ACC 2018) - Hilton Milwaukee City Center Hotel, Milwaukee, Wisconsin, Verenigde Staten van Amerika
Duur: 27 jun 201829 jun 2018
http://acc2018.a2c2.org/

Congres

Congres2018 American Control Conference (ACC 2018)
Verkorte titelACC 2018
Land/RegioVerenigde Staten van Amerika
StadMilwaukee, Wisconsin
Periode27/06/1829/06/18
Internet adres

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