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Benchmark problems for continuous-time model identification: Design aspects, results and perspectives
ONERA French Aerosp Lab, France; Univ Lorraine, France.
Univ Lorraine, France; CNRS, France.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
ONERA French Aerosp Lab, France.
2019 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 107, p. 511-517Article in journal (Refereed) Published
Abstract [en]

The problem of estimating continuous-time model parameters of linear dynamical systems using sampled time-domain input and output data has received considerable attention over the past decades and has been approached by various methods. The research topic also bears practical importance due to both its close relation to first principles modelling and equally to linear model-based control design techniques, most of them carried in continuous time. Nonetheless, as the performance of the existing algorithms for continuous-time model identification has seldom been assessed and, as thus far, it has not been considered in a comprehensive study, this practical potential of existing methods remains highly questionable. The goal of this brief paper is to bring forward a first study on this issue and to factually highlight the main aspects of interest. As such, an analysis is performed on a benchmark designed to be consistent both from a system identification viewpoint and from a control-theoretic one. It is concluded that robust initialization aspects require further research focus towards reliable algorithm development. (C) 2019 Elsevier Ltd. All rights reserved.

Place, publisher, year, edition, pages
PERGAMON-ELSEVIER SCIENCE LTD , 2019. Vol. 107, p. 511-517
Keywords [en]
Identification algorithms; Output error identification; Parameter identification; Linear multivariable systems; Benchmark examples; Monte Carlo simulation
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-160161DOI: 10.1016/j.automatica.2019.06.011ISI: 000481723300056OAI: oai:DiVA.org:liu-160161DiVA, id: diva2:1349586
Note

Funding Agencies|ONERA - The French Aerospace Laboratory; Universite de Lorraine

Available from: 2019-09-09 Created: 2019-09-09 Last updated: 2019-09-09

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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  • Other style
More styles
Language
  • de-DE
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  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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