Recursive least squares estimation with rank two updates
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| Title: | Recursive least squares estimation with rank two updates |
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| Authors: | Stotsky, Alexander, 1960 |
| Source: | Automatika. 66(4):619-624 |
| Subject Terms: | Forgetting and windowing, rank two update versus rank one update, updating and downdating, wave form distortion monitoring for smart grids, estimation of the inverse of the information matrix and unknown parameters via RLS algorithms, RLSR2 (recursive least squares with rank two update) |
| Description: | This paper presents new recursive least squares (RLS) algorithms with enhanced performance, achieved via a combination of exponential forgetting and windowing techniques. The proposed algorithms with rank two updates are systematically aligned with established RLS algorithms with rank one updates to ensure unification and clarity. Newly identified properties of the recursive algorithms, associated with the convergence of both the inverse of the information matrix and the parameter estimates which are presented in this paper, offer great potential for further enhancement of the estimation performance. The proposed algorithms demonstrate significant improvements in the estimation of the grid events in the presence of substantial harmonic emissions. |
| File Description: | electronic |
| Access URL: | https://research.chalmers.se/publication/547561 https://research.chalmers.se/publication/547561/file/547561_Fulltext.pdf |
| Database: | SwePub |
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Nájsť tento článok vo Web of Science | Abstract: | This paper presents new recursive least squares (RLS) algorithms with enhanced performance, achieved via a combination of exponential forgetting and windowing techniques. The proposed algorithms with rank two updates are systematically aligned with established RLS algorithms with rank one updates to ensure unification and clarity. Newly identified properties of the recursive algorithms, associated with the convergence of both the inverse of the information matrix and the parameter estimates which are presented in this paper, offer great potential for further enhancement of the estimation performance. The proposed algorithms demonstrate significant improvements in the estimation of the grid events in the presence of substantial harmonic emissions. |
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| ISSN: | 00051144 |
| DOI: | 10.1080/00051144.2025.2517431 |