Gaussian Process Position-Dependent Feedforward: With Application to a Wire Bonder

Max van Haren, Maurice Poot, Dragan Kostic, Robin van Es, Jim Portegies, Tom Oomen

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

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Samenvatting

Mechatronic systems have increasingly stringent performance requirements for
motion control, leading to a situation where many factors, such as position-dependency, cannot be neglected in feedforward control. The aim of this paper is to compensate for position-dependent effects by modeling feedforward parameters as a function of position. A framework to model and identify feedforward parameters as a continuous function of position is developed by combining Gaussian processes and feedforward parameter learning techniques. The framework results in a fully data-driven approach, which can be readily implemented for industrial control applications. The framework is experimentally validated and shows a significant performance increase on a commercial wire
bonder.
Originele taal-2Engels
Titel2022 IEEE 17th International Conference on Advanced Motion Control (AMC)
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's268-273
Aantal pagina's6
ISBN van elektronische versie978-1-7281-7711-3
DOI's
StatusGepubliceerd - 11 mrt. 2022
Evenement17th IEEE International Conference on Advanced Motion Control, AMC 2022 - Padova, Italië
Duur: 18 feb. 202220 feb. 2022
Congresnummer: 17
http://static.gest.unipd.it/AMC2022/

Congres

Congres17th IEEE International Conference on Advanced Motion Control, AMC 2022
Verkorte titelAMC 2022
Land/RegioItalië
StadPadova
Periode18/02/2220/02/22
Internet adres

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