On inferential iterative learning control : with example on a printing system

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8 Citations (Scopus)

Abstract

Since performance variables cannot be measured directly, Iterative Learning Control (ILC) is usually applied to measured variables. In this paper, it is shown that this can deteriorate performance. New batch-wise sensors that measure the performance variables directly are well-suited for use in ILC and can potentially improve performance. In this paper, recent developments in inferential control are utilized to arrive at control structures suited for inferential ILC. The proposed frameworks extend earlier results and encompass various controller structures. The results are supported with a simulation example.
Original languageEnglish
Title of host publicationProceedings of the 2014 American Control Conference, 4-6 June 2014, Portland, Oregon
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages1827-1832
ISBN (Print)978-1-4799-3272-6
DOIs
Publication statusPublished - 2014
Event2014 American Control Conference (ACC 2014), June 4-6, 2014, Portland, OR, USA - Hilton Portland & Executive Tower , Portland, OR, United States
Duration: 4 Jun 20146 Jun 2014
http://acc2014.a2c2.org/

Conference

Conference2014 American Control Conference (ACC 2014), June 4-6, 2014, Portland, OR, USA
Abbreviated titleACC 2014
CountryUnited States
CityPortland, OR
Period4/06/146/06/14
Internet address

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