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

Max Van Haren; Leonid Mirkin; Lennart Blanken; Tom Oomen

doi:10.1109/LCSYS.2023.3284344

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

Team Jan-Willem van Wingerden

Research output: Contribution to journal › Article › Scientific › peer-review

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Abstract

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 language	English
Pages (from-to)	2131-2136
Journal	IEEE Control Systems Letters
Volume	7
DOIs	https://doi.org/10.1109/LCSYS.2023.3284344
Publication status	Published - 2023

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
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.

Keywords

Frequency response function
sampled-data systems
system identification

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abstract = "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. ",

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year = "2023",

doi = "10.1109/LCSYS.2023.3284344",

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AU - Oomen, Tom

N1 - Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care 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.

PY - 2023

Y1 - 2023

N2 - 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.

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

Abstract

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Keywords

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