Robustness against model uncertainties of norm optimal iterative learning control

M.C.F. Donkers, J.J.M. Wijdeven, van de, O.H. Bosgra

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

29 Citaten (Scopus)
3 Downloads (Pure)

Samenvatting

In this paper, we study MIMO Iterative Learning Control (ILC) and its robustness against model uncertainty. Although it is argued that, so-called, norm optimal ILC controllers have some inherent robustness, not many results are available that can make quantitative statements about the allowable model uncertainty. In this paper, we derive sufficient conditions for robust convergence of the ILC algorithm in presence of an uncertain system with an additive uncertainty bound. These conditions are applied to norm optimal ILC, resulting in guidelines for robust controller design. Theoretical results are illustrated by simulations.
Originele taal-2Engels
TitelProceedings of the 2008 American Control Conference (ACC2008), Seattle, Washington, USA, June 11-13, 2008
Plaats van productiePiscataway
UitgeverijInstitute of Electrical and Electronics Engineers
Pagina's4561-4566
ISBN van geprinte versie978-1-424-42078-0
DOI's
StatusGepubliceerd - 2008

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