Beyond quantization in iterative learning control: exploiting time-varying time-stamps

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

1 Citaat (Scopus)
3 Downloads (Pure)

Samenvatting

Equidistant sampling in control system may lead to quantization errors for certain measurement equipment, e.g., encoders. The aim of this paper is to develop an Iterative Learning Control (ILC) framework that eliminates quantization by exploiting time stamping. The developed ILC framework employs the non-equidistant time stamps in a linear time-varying (LTV) approach. Since the data at the time-stamps does not suffer from quantization, unparalleled performance can be achieved, while the intersample behaviour is bounded by definition. A simulation example confirms superiority of the ILC framework which employs time stamping.

Originele taal-2Engels
Titel2019 American Control Conference, ACC 2019
Plaats van productiePIscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's2984-2989
Aantal pagina's6
ISBN van elektronische versie978-1-5386-7926-5
DOI's
StatusGepubliceerd - 1 jul 2019
Evenement2019 American Control Conference, ACC 2019 - Philadelphia, Verenigde Staten van Amerika
Duur: 10 jul 201912 jul 2019
http://acc2019.a2c2.org

Congres

Congres2019 American Control Conference, ACC 2019
Verkorte titelACC2019
LandVerenigde Staten van Amerika
StadPhiladelphia
Periode10/07/1912/07/19
Internet adres

Vingerafdruk Duik in de onderzoeksthema's van 'Beyond quantization in iterative learning control: exploiting time-varying time-stamps'. Samen vormen ze een unieke vingerafdruk.

Citeer dit