A design approach for noncausal robust iterative learning control using worst case disturbance optimisation

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)
88 Downloads (Pure)

Abstract

In this paper, we present a novel iterative learning control (ILC) strategy that is robust against model uncertainty, as given by a system model and an additive uncertainty bound. The design methodology hinges on Hinfin optimisation, however, the procedure is modified such that the ILC controller is noncausal and inherently acts on a finite time interval. The resulting controller has the structure of a norm optimal ILC controller, so that robustness can be easily assessed. Furthermore, in an example, we show that the presented robust ILC controller can outperform linear quadratic ILC controllers.
Original languageEnglish
Title of host publicationProceedings of the 2008 American Control Conference (ACC2008), Seattle, Washington, USA, June 11-13, 2008
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages4567-4572
ISBN (Print)978-1-4244-2078-0
DOIs
Publication statusPublished - 2008

Fingerprint Dive into the research topics of 'A design approach for noncausal robust iterative learning control using worst case disturbance optimisation'. Together they form a unique fingerprint.

Cite this