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Blind Identification via Lifting
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering. University of Calif Berkeley, CA 94720 USA.
University of Calif Berkeley, CA 94720 USA.
University of Calif Berkeley, CA 94720 USA.
University of Calif Berkeley, CA 94720 USA.
2014 (English)In: IFAC PAPERSONLINE, ELSEVIER SCIENCE BV , 2014, Vol. 47, no 3, p. 10367-10372Conference paper, Published paper (Refereed)
Abstract [en]

Blind system identification is known to be an ill-posed problem and without further assumptions, no unique solution is at hand. In this contribution, we are concerned with the task of identifying an ARX model from only output measurements. We phrase this as a constrained rank minimization problem and present a relaxed convex formulation to approximate its solution. To make the problem well posed we assume that the sought input lies in some known linear subspace.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE BV , 2014. Vol. 47, no 3, p. 10367-10372
Series
IFAC-PapersOnLine, E-ISSN 1474-6670
Keywords [en]
System identification; Parameter estimation; Identification algorithms
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-137422OAI: oai:DiVA.org:liu-137422DiVA, id: diva2:1095564
Conference
19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014; Cape Town; South Africa; 24 August 2014 through 29 August 2014
Available from: 2017-05-15 Created: 2017-05-15 Last updated: 2019-11-29

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Citation style
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Output format
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