On the detection of nonlinearities in sampled data

Jesica Escobar, Martin Enqvist

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Here we deal with the choice of the sampling rate in nonlinear system identification applications. In particular, we focus on the effect of the sampling rate when the prediction-error method is used. On one hand, a high sampling rate is advantageous since it enables the measurement of high-frequent nonlinear components in the output signal of the system without aliasing. However, a high sampling rate might also make it harder to realize that the system is nonlinear, since the nonlinearities cannot be detected in the residuals from a linear model in some cases. Here, this phenomenon is illustrated in a couple of numerical examples and a way to avoid it is proposed.

Original languageEnglish
Title of host publicationSYSID 2012 - 16th IFAC Symposium on System Identification, Final Program
PublisherIFAC Secretariat
Pages1587-1592
Number of pages6
EditionPART 1
ISBN (Print)9783902823069
DOIs
StatePublished - 2012
Externally publishedYes
EventUniversite Libre de Bruxelles - Bruxelles, Belgium
Duration: 11 Jul 201213 Jul 2012

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
NumberPART 1
Volume16
ISSN (Print)1474-6670

Conference

ConferenceUniversite Libre de Bruxelles
Country/TerritoryBelgium
CityBruxelles
Period11/07/1213/07/12

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