Study of the minimum experiment length to identify linear dynamic systems: a variance based approach

J.F.M. Schoukens, S. Kolumban

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

Abstract

In this paper the effect of short data lengths in system identification is studied. It addresses the question of the minimum required data length that is needed in order to apply the asymptotic results on the uncertainty analysis. this paper is focused on the IIR-case by analyzing initially a first order system. The conclusions are extended to higher order systems by normalizing all results on the time constant of this system, and by adding a model complexity factor.

Original languageEnglish
Title of host publication2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 11-15 May 2015, Pisa, Italy
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages963-968
Number of pages6
ISBN (Electronic)978-1-4799-6114-6
DOIs
Publication statusPublished - 6 Jul 2015
Externally publishedYes
Event2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC 2015) - Palazzo dei Congressi, Pisa, Italy
Duration: 11 May 201514 May 2015

Conference

Conference2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC 2015)
Abbreviated titleI2MTC 2015
CountryItaly
CityPisa
Period11/05/1514/05/15

Keywords

  • IIR-models
  • Small data sets
  • System identification
  • Variance analysis

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    Schoukens, J. F. M., & Kolumban, S. (2015). Study of the minimum experiment length to identify linear dynamic systems: a variance based approach. In 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 11-15 May 2015, Pisa, Italy (pp. 963-968). [7151400] Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/I2MTC.2015.7151400