Application of Recursive Least Squares Algorithm With Variable Forgetting Factor for Frequency Component Estimation in a Generic Input Signal
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| Název: | Application of Recursive Least Squares Algorithm With Variable Forgetting Factor for Frequency Component Estimation in a Generic Input Signal |
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| Autoři: | Beza, Mebtu Bihonegn, 1981, Bongiorno, Massimo, 1976 |
| Zdroj: | IEEE Transactions on Industry Applications. 50(2):1168-1176 |
| Témata: | least squares methods, frequency estimation, variable forgetting factor, SYSTEMS, Adaptive estimation, phase, estimation, phase-locked loops (PLLs) |
| Popis: | Signal estimation is important for protection, system study, and control purposes. This paper deals with the application of a modified recursive least squares algorithm, based on a variable forgetting factor, for estimation of frequency components in a generic input signal. Application areas such as synchronization and control in three- and single-phase systems for various grid conditions as well as estimation of harmonic and subsynchronous components will be discussed. Advantages of the proposed method over the available techniques in terms of estimation speed, frequency selectivity, and noise rejection capability will be described. Finally, simulation and experimental results will be used to evaluate the dynamic performance of the proposed method. |
| Přístupová URL adresa: | https://research.chalmers.se/publication/199227 |
| Databáze: | SwePub |
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Nájsť tento článok vo Web of Science | Abstrakt: | Signal estimation is important for protection, system study, and control purposes. This paper deals with the application of a modified recursive least squares algorithm, based on a variable forgetting factor, for estimation of frequency components in a generic input signal. Application areas such as synchronization and control in three- and single-phase systems for various grid conditions as well as estimation of harmonic and subsynchronous components will be discussed. Advantages of the proposed method over the available techniques in terms of estimation speed, frequency selectivity, and noise rejection capability will be described. Finally, simulation and experimental results will be used to evaluate the dynamic performance of the proposed method. |
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| ISSN: | 00939994 19399367 |
| DOI: | 10.1109/tia.2013.2279195 |