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Asymptotic Properties of Identification of Hammerstein Models with Input Saturation
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Department of Electrical and Computer Engineering University of Newcastle, Australia.
2000 (English)Report (Other academic)
Abstract [en]

This paper considers the estimation of Hammerstein models with input saturation. These models are characterised by a linear dynamical model acting on an input sequence which is affected by a hard saturation of unknown level. The main result of the paper lies in a specication of a set of sufficient conditions on the input sequence in order to ensure that a non-linear least-squares approach enjoys properties of consistency and asymptotic normality and furthermore, that an estimate of the parameter covariance matrix is also consistent. The set of assumptions is specied using the concept of near epoch dependence, which has been developed in the econometrics literature. Indeed, one purpose of this paper is to highlight the usefulness of this concept in the context of analysing estimation procedures for nonlinear dynamical systems.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2000. , 9 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2266
Keyword [en]
Nonlinear system identification, Hammerstein models, Asymptotic properties
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-55677ISRN: LiTH-ISY-R-2266OAI: oai:DiVA.org:liu-55677DiVA: diva2:316395
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-09-11Bibliographically approved

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Automatic ControlThe Institute of Technology
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CiteExportLink to record
Permanent link

Direct link
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf