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Avtomatika i Telemekhanika, 2023, Issue 1, Pages 23–62
DOI: https://doi.org/10.31857/S0005231023010026 (Mi at15862) 		 
This article is cited in 2 scientific papers (total in 2 papers)

Nonlinear Systems

Relaxation of conditions for convergence of dynamic regressor extension and mixing procedure

A. I. Glushchenko, K. A. Lastochkin

Trapeznikov Institute of Control Sciences, Russian Academy of Sciences, Moscow, Russia
Full-text PDF (1544 kB) First page Citations (2)
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DOI: https://doi.org/10.31857/S0005231023010026
Abstract: A generalization of the dynamic regressor extension and mixing procedure is proposed, which, unlike the original procedure, first, guarantees a reduction of the unknown parameter identification error if the requirement of regressor semi-finite excitation is met, and second, it ensures exponential convergence of the regression function (regressand) tracking error to zero when the regressor is semi-persistently exciting with a rank one or higher.
Keywords: identification, linear regression, semi-finite excitation, semi-persistent excitation, parameter error, convergence, boundedness, monotonicity, singular value decomposition.
Funding agency Grant number
Ministry of Science and Higher Education of the Russian Federation МД.1787.2022.4
This research was in part financially supported by Grants Council of the President of the Russian Federation (project MD-1787.2022.4).
Presented by the member of Editorial Board: A. A. Bobtsov

Received: 13.12.2021
Revised: 17.06.2022
Accepted: 29.09.2022
English version:
Automation and Remote Control, 2023, Volume 84, Issue 1, Pages 14–41
DOI: https://doi.org/10.1134/S0005117923010046
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: A. I. Glushchenko, K. A. Lastochkin, “Relaxation of conditions for convergence of dynamic regressor extension and mixing procedure”, Avtomat. i Telemekh., 2023, no. 1, 23–62; Autom. Remote Control, 84:1 (2023), 14–41
Citation in format AMSBIB
\Bibitem{GluLas23}
\by A.~I.~Glushchenko, K.~A.~Lastochkin
\paper Relaxation of conditions for convergence of dynamic regressor extension and mixing procedure
\jour Avtomat. i Telemekh.
\yr 2023
\issue 1
\pages 23--62
\mathnet{http://mi.mathnet.ru/at15862}
\crossref{https://doi.org/10.31857/S0005231023010026}
\edn{https://elibrary.ru/LUAPNM}
\transl
\jour Autom. Remote Control
\yr 2023
\vol 84
\issue 1
\pages 14--41
\crossref{https://doi.org/10.1134/S0005117923010046}
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    • This publication is cited in the following 2 articles:
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