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

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Abstract

Fast-sampled models are essential for control design, e.g., to address intersample behavior. The aim of this paper 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 fastsampled models of slowly-sampled systems accurately in a single identification experiment. Finally, an experimental example demonstrates the effectiveness of the technique.
Original languageEnglish
Title of host publication62nd IEEE Conference on Decision and Control
PublisherInstitute of Electrical and Electronics Engineers
Publication statusAccepted/In press - 2023
Event62nd IEEE Conference on Decision and Control, CDC 2023 - Singapore, Singapore, Singapore, Singapore
Duration: 13 Dec 202315 Dec 2023
Conference number: 62

Conference

Conference62nd IEEE Conference on Decision and Control, CDC 2023
Abbreviated titleCDC 2023
Country/TerritorySingapore
CitySingapore
Period13/12/2315/12/23

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