Real-Time Identification of Periodic Signals using the Recursive Variable Projection Algorithm

Johannes Handler, Dimitar Ninevski, Mathias Rollett, Paul O'Leary

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a real-time parameter identification algorithm for periodic signals, based on the recursive variable projection (RVP) algorithm. The recursive implementation enables the tracking of time-varying parameters. The signal model is linear with respect to the amplitude parameters while being nonlinear with respect to the phase and frequency. This feature motivates the use of a variable projection based approach. Its performance is tested using Monte Carlo simulations and the results are compared with those obtained by a multiobjective Gauss-Newton (MGN) algorithm. Furthermore, the RVP algorithm is applied to measurement data acquired by a MEMS accelerometer and it is demonstrated that it can successfully track time-varying linear and nonlinear parameters.
Original languageEnglish
Title of host publicationIECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society
PublisherPubl by IEEE
Pages1-6
DOIs
Publication statusPublished - 9 Dec 2022
Event48th Annual Conference of the IEEE Industrial Electronics Society - IECON 2022 - Brüssel, Belgium
Duration: 17 Oct 202220 Oct 2022

Conference

Conference48th Annual Conference of the IEEE Industrial Electronics Society - IECON 2022
Abbreviated titleIECON 2022
Country/TerritoryBelgium
CityBrüssel
Period17/10/2220/10/22

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