Limit sets and switching strategies in parameter-optimal iterative learning control
Owens, D. H., Tomas-Rodriguez, M. and Daley, S. (2008) Limit sets and switching strategies in parameter-optimal iterative learning control. International Journal of Control, 81, (4), 626-640. (doi:10.1080/00207170701579403).
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This paper characterizes the existence and form of the possible limit error signals in typical parameter-optimal iterative learning control. The set of limit errors has attracting and repelling components and the behaviour of the algorithm in the vicinity of these sets can be associated with the undesirable properties of apparent (but in fact temporary) convergence or permanent slow convergence properties in practice. The avoidance of these behaviours in practice is investigated using novel switching strategies. Deterministic strategies are analysed to prove the feasibility of the concept by proving that each of a number of such strategies is guaranteed to produce global convergence of errors to zero independent of the details of plant dynamics. For practical applications a random switching strategy is proposed to replace these approaches and shown, by example, to produce substantial potential improvements when compared with the non-switching case. The work described in this paper is covered by pending patent applications in the UK and elsewhere.
|Subjects:||T Technology > T Technology (General)|
|Divisions:||Faculty of Engineering and the Environment > Institute of Sound and Vibration Research > Signal Processing & Control Research Group
|Date Deposited:||07 Mar 2012 16:32|
|Last Modified:||18 Jan 2015 17:03|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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