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Data-driven H-infinity-norm estimation via expert advice
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0003-0355-2663
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2017 (English)In: 2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1560-1565Conference paper, Published paper (Refereed)
Abstract [en]

H-infinity-norm estimation is usually an important aspect of robust control design. The aim of this paper is to develop a data-driven estimation method exploiting iterative input design, without requiring parametric modeling. More specifically, the estimation problem is formulated as a sequential game, whose solution is derived within the prediction with expert advice framework. The proposed method is shown to be competitive with the state-of-the-art techniques.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 1560-1565
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-223867DOI: 10.1109/CDC.2017.8263873ISI: 000424696901091Scopus ID: 2-s2.0-85046129816ISBN: 978-1-5090-2873-3 OAI: oai:DiVA.org:kth-223867DiVA, id: diva2:1187830
Conference
56th IEEE Annual Conference on Decision and Control, CDC 2017, Melbourne Convention and Exhibition Centre (MCEC)Melbourne, Australia, 12 December 2017 through 15 December 2017
Note

QC 20180306

Available from: 2018-03-06 Created: 2018-03-06 Last updated: 2018-11-14Bibliographically approved

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Rojas, Cristian R.

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CiteExportLink to record
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Citation style
  • apa
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
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