Constant Parameter Identification: An ...
Type de document :
Communication dans un congrès avec actes
Titre :
Constant Parameter Identification: An Accelerated Heavy-Ball-based Approach
Auteur(s) :
Ríos, Héctor [Auteur]
Instituto Tecnologico de la Laguna [ITL]
Efimov, Denis [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Ushirobira, Rosane [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Instituto Tecnologico de la Laguna [ITL]
Efimov, Denis [Auteur]

Finite-time control and estimation for distributed systems [VALSE]
Ushirobira, Rosane [Auteur]

Finite-time control and estimation for distributed systems [VALSE]
Titre de la manifestation scientifique :
IEEE CDC 2024 - IEEE Conference on Decision and Control
Ville :
MIlan
Pays :
Italie
Date de début de la manifestation scientifique :
2024-12-09
Mot(s)-clé(s) en anglais :
Parameter Identification
Heavy-Ball Method
Finite-Time
Heavy-Ball Method
Finite-Time
Discipline(s) HAL :
Informatique [cs]/Automatique
Résumé en anglais : [en]
This paper contributes to designing a parameter identification algorithm for linear regression systems with constant unknown parameters. The proposed algorithm is based on an accelerated version of the heavy-ball method ...
Lire la suite >This paper contributes to designing a parameter identification algorithm for linear regression systems with constant unknown parameters. The proposed algorithm is based on an accelerated version of the heavy-ball method and uses a nonlinear version of Kreisselmeier's regressor extension. Moreover, it can identify constant parameters in a finite time under a persistent excitation condition. The local stability analysis is developed using a Lyapunov function approach. The applicability and effectiveness of the proposed parameter identification algorithm are illustrated through simulation results.Lire moins >
Lire la suite >This paper contributes to designing a parameter identification algorithm for linear regression systems with constant unknown parameters. The proposed algorithm is based on an accelerated version of the heavy-ball method and uses a nonlinear version of Kreisselmeier's regressor extension. Moreover, it can identify constant parameters in a finite time under a persistent excitation condition. The local stability analysis is developed using a Lyapunov function approach. The applicability and effectiveness of the proposed parameter identification algorithm are illustrated through simulation results.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
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