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A framework for analysis of observer‐based ILC
Author(s) -
Wallén Johanna,
Norrlöf Mikael,
Gunnarsson Svante
Publication year - 2011
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.261
Subject(s) - iterative learning control , control theory (sociology) , observer (physics) , variable (mathematics) , bounded function , robot , mathematics , computer science , control (management) , artificial intelligence , physics , mathematical analysis , quantum mechanics
A framework for iterative learning control (ILC) is proposed for the situation when an ILC algorithm uses an estimate of the controlled variable obtained from an observer‐based estimation procedure. Assuming that the ILC input converges to a bounded signal, a general expression for the asymptotic error of the controlled variable is given. The asymptotic error is exemplified by an ILC algorithm applied to a flexible two‐mass model of a robot joint. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society