Recursive least squares estimation with rank two updates

New recursive least squares algorithms with rank two updates (RLSR2) that include both exponential and instantaneous forgetting (implemented via a proper choice of the forgetting factor and the window size) are introduced and systematically associated in this report with well-known RLS algorithms with rank one updates. Moreover, new properties (which can be used for further performance improvement) of the recursive algorithms associated with the convergence of the inverse of information matrix and parameter vector are established in this report. The performance of new algorithms is examined in the problem of estimation of the grid events in the presence of significant harmonic emissions.

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Publication Details

Journal
Automatika
Published
2025-07-14
DOI
https://doi.org/10.1080/00051144.2025.2517431
Citations
3
Primary Topic
Control Systems and Identification
Type
article
Field-Weighted Citation Impact
3.64
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article

Recursive least squares estimation with rank two updates

Alexander Stotsky
3 citations
Automatika
Control Systems and Identification
3.64
article

Recursive least squares estimation with rank two updates

Alexander Stotsky
article en
3 citations

Abstract

New recursive least squares algorithms with rank two updates (RLSR2) that include both exponential and instantaneous forgetting (implemented via a proper choice of the forgetting factor and the window size) are introduced and systematically associated in this report with well-known RLS algorithms with rank one updates. Moreover, new properties (which can be used for further performance improvement) of the recursive algorithms associated with the convergence of the inverse of information matrix and parameter vector are established in this report. The performance of new algorithms is examined in the problem of estimation of the grid events in the presence of significant harmonic emissions.

AutomatikaVol. 66(4)
Chalmers University of Technology (SE)
Openalex Percentile: Top 7%
Control Systems and Identification
3.64
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