Constant Parameter Identification: An ...
Document type :
Communication dans un congrès avec actes
Title :
Constant Parameter Identification: An Accelerated Heavy-Ball-based Approach
Author(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]
Conference title :
IEEE CDC 2024 - IEEE Conference on Decision and Control
City :
MIlan
Country :
Italie
Start date of the conference :
2024-12-09
English keyword(s) :
Parameter Identification
Heavy-Ball Method
Finite-Time
Heavy-Ball Method
Finite-Time
HAL domain(s) :
Informatique [cs]/Automatique
English abstract : [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 ...
Show more >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.Show less >
Show more >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.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :
Files
- document
- Open access
- Access the document
- CDC24_0242_FI.pdf
- Open access
- Access the document