Intermittent sampling in iterative learning control: a monotonically-convergent gradient-descent approach with application to time stamping

Nard Strijbosch, Tom A.E. Oomen

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

2 Citaten (Scopus)
4 Downloads (Pure)

Samenvatting

The standard assumption that a measurement signal is available at each sample in iterative learning control (ILC) is not always justified, e.g., in systems with data dropouts or when exploiting time-stamped data from incremental encoders. The aim of this paper is to develop a computationally tractable ILC framework for systems with arbitrary time- varying measurement points. New conditions for monotonic convergence of the input signal are established. These lead to a new single centralized design approach independent of the sampling times reminiscent of gradient-descent ILC. The approach is demonstrated in a simulation example of a massspring-damper system from which exact time-varying time- stamped data from the incremental encoder is available.

Originele taal-2Engels
Titel2019 IEEE 58th Conference on Decision and Control (CDC)
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's6542-6547
Aantal pagina's6
ISBN van elektronische versie978-1-7281-1397-5
DOI's
StatusGepubliceerd - 2019
Evenement2019 IEEE 58th Conference on Decision and Control (CDC) - Nice, France, Nice, Frankrijk
Duur: 11 dec. 201913 dec. 2019
Congresnummer: 58
https://cdc2019.ieeecss.org/

Congres

Congres2019 IEEE 58th Conference on Decision and Control (CDC)
Verkorte titelCDC 2019
Land/RegioFrankrijk
StadNice
Periode11/12/1913/12/19
Internet adres

Vingerafdruk

Duik in de onderzoeksthema's van 'Intermittent sampling in iterative learning control: a monotonically-convergent gradient-descent approach with application to time stamping'. Samen vormen ze een unieke vingerafdruk.

Citeer dit