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On the convergence of the Prediction Error Method to its global minimum
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
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
2012 (English)In: 16th IFAC Symposium on System Identification, IFAC , 2012, 698-703 p.Conference paper, Published paper (Refereed)
Abstract [en]

The Prediction Error Method (PEM) is related to an optimization problem built on input/output data collected from the system to be identified. It is often hard to find the global solution of this optimization problem because the corresponding objective function presents local minima and/or the search space is constrained to a nonconvex set. The existence of local minima, and hence the difficulty in solving the optimization, depends mainly on the experimental conditions, more specifically on the spectrum of the input/output data collected from the system. It is therefore possible to avoid the existence of local minima by properly choosing the spectrum of the input; in this paper we show how to perform this choice. We present sufficient conditions for the convergence of PEM to the global minimum and from these conditions we derive two approaches to avoid the existence of nonglobal minima. We present the application of one of these two approaches to a case study where standard identification toolboxes tend to get trapped in nonglobal minima.

Place, publisher, year, edition, pages
IFAC , 2012. 698-703 p.
Series
IFAC Proceedings Volumes (IFAC-PapersOnline), ISSN 1474-6670 ; 16
Keyword [en]
Convergence, Gradient methods, Identification
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-72583DOI: 10.3182/20120711-3-BE-2027.00371Scopus ID: 2-s2.0-84867061419ISBN: 978-390282306-9 (print)OAI: oai:DiVA.org:kth-72583DiVA: diva2:488375
Conference
16th IFAC Symposium on System Identification (SYSID 2012), Universite Libre de Bruxelles; Bruxelles; 11 July 2012 through 13 July 2012
Funder
ICT - The Next Generation
Note

QC  20121122

Available from: 2012-02-01 Created: 2012-01-31 Last updated: 2013-04-15Bibliographically approved

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Rojas, Cristian R.Hjalmarsson, Håkan

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