Beyond Nyquist in Frequency Response Function Identification: Applied to Slow-Sampled Systems

Max Van Haren*, Leonid Mirkin, Lennart Blanken, Tom Oomen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review


Fast-sampled models are essential for control design, e.g., to address intersample behavior. The aim of this letter is to develop a non-parametric identification technique for fast-sampled models of systems that have relevant dynamics and actuation above the Nyquist frequency of the sensor, such as vision-in-the-loop systems. The developed method assumes smoothness of the frequency response function, which allows to disentangle aliased components through local models over multiple frequency bands. The method identifies fast-sampled models of slowly-sampled systems accurately in a single identification experiment. Finally, an experimental example demonstrates the effectiveness of the technique.

Original languageEnglish
Pages (from-to)2131-2136
JournalIEEE Control Systems Letters
Publication statusPublished - 2023

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Frequency response function
  • sampled-data systems
  • system identification


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