DocumentCode
184124
Title
On inferential Iterative Learning Control: With example to a printing system
Author
Bolder, Joost ; Oomen, Tom ; Steinbuch, Maarten
Author_Institution
Dept. of Mech. Eng., Eindhoven Univ. of Technol., Eindhoven, Netherlands
fYear
2014
fDate
4-6 June 2014
Firstpage
1827
Lastpage
1832
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.
Keywords
adaptive control; iterative methods; learning systems; sensors; batch-wise sensors; inferential ILC; inferential iterative learning control; performance improvement; performance variable measurement; performance variables; printing system; Adaptive control; Feedback control; Feedforward neural networks; Observers; Performance analysis; Position measurement; Real-time systems; Iterative learning control; Mechatronics; Optimal control;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2014
Conference_Location
Portland, OR
ISSN
0743-1619
Print_ISBN
978-1-4799-3272-6
Type
conf
DOI
10.1109/ACC.2014.6858946
Filename
6858946
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