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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), IEEE , 2017Conference 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
IEEE , 2017.
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-223867ISI: 000424696901091ISBN: 978-1-5090-2873-3 OAI: oai:DiVA.org:kth-223867DiVA, id: diva2:1187830
Conference
IEEE 56th Annual Conference on Decision and Control (CDC), DEC 12-15, 2017, Melbourne, AUSTRALIA
Note

QC 20180306

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

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Rojas, Cristian R.

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