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On optimal input design for nonlinear FIR-type systems
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. (System Identification Group)
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. (System Identification Group)ORCID iD: 0000-0002-9368-3079
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. (System Identification Group)ORCID iD: 0000-0003-0355-2663
2010 (English)In: 49TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), New York: IEEE , 2010, 7220-7225 p.Conference paper, Published paper (Refereed)
Abstract [en]

We consider optimal input design for system identification of nonlinear FIR-type systems in the prediction error (PEM) framework. The input sequences are designed in terms of their statistical properties and not directly in time domain. The starting point is the asymptotic properties of PEM estimates. The fact that the inverse covariance matrix of the estimated parameters is linear in the input probability density function is exploited to formulate convex optimization problems. The main issues considered are the parameterization of the input pdf, reduction of the number of free variables in the optimization and to some extent signal generation. Two special model classes where tractable problems are obtainable are studied in detail. Convex formulations of the input design problem are presented for the static nonlinear and nonlinear FIR cases. Numerical examples of the discussed ideas are also presented.

Place, publisher, year, edition, pages
New York: IEEE , 2010. 7220-7225 p.
National Category
Control Engineering
Research subject
SRA - ICT
Identifiers
URN: urn:nbn:se:kth:diva-48363DOI: 10.1109/CDC.2010.5717250ISI: 000295049108030Scopus ID: 2-s2.0-79953142322ISBN: 978-1-4244-7746-3 (print)OAI: oai:DiVA.org:kth-48363DiVA: diva2:457428
Conference
49th IEEE Conference on Decision and Control (CDC) Location: Atlanta, GA Date: DEC 15-17, 2010
Funder
Swedish Research Council, 621-2007-6271
Note

QC 20111122

Available from: 2011-11-17 Created: 2011-11-17 Last updated: 2016-06-01Bibliographically approved

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Hjalmarsson, HåkanRojas, Cristian R.

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