On robust parameter estimation in finite-time ...
Type de document :
Compte-rendu et recension critique d'ouvrage
DOI :
Titre :
On robust parameter estimation in finite-time without persistence of excitation
Auteur(s) :
Wang, Jian [Auteur]
Hangzhou Dianzi University [HDU]
Efimov, Denis [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Bobtsov, Alexey [Auteur]
National Research University of Information Technologies, Mechanics and Optics [St. Petersburg] [ITMO]
Hangzhou Dianzi University [HDU]
Efimov, Denis [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Bobtsov, Alexey [Auteur]
National Research University of Information Technologies, Mechanics and Optics [St. Petersburg] [ITMO]
Titre de la revue :
IEEE Transactions on Automatic Control
Pagination :
1731-1738
Éditeur :
Institute of Electrical and Electronics Engineers
Date de publication :
2020-04-01
ISSN :
0018-9286
Discipline(s) HAL :
Sciences de l'ingénieur [physics]/Automatique / Robotique
Résumé en anglais : [en]
The problem of adaptive estimation of constant parameters in the linear regressor model is studied without the hypothesis that regressor is Persistently Excited (PE). First, the initial vector estimation problem is transformed ...
Lire la suite >The problem of adaptive estimation of constant parameters in the linear regressor model is studied without the hypothesis that regressor is Persistently Excited (PE). First, the initial vector estimation problem is transformed to a series of the scalar ones using the method of Dynamic Regressor Extension and Mixing (DREM). Second, several adaptive estimation algorithms are proposed for the scalar scenario. In such a case, if the regressor may be nullified asymptotically or in a finite time, then the problem of estimation is also posed on a finite interval of time. Robustness of the proposed algorithms with respect to measurement noise and exogenous disturbances is analyzed. The efficiency of the designed estimators is demonstrated in numeric experiments for academic examples.Lire moins >
Lire la suite >The problem of adaptive estimation of constant parameters in the linear regressor model is studied without the hypothesis that regressor is Persistently Excited (PE). First, the initial vector estimation problem is transformed to a series of the scalar ones using the method of Dynamic Regressor Extension and Mixing (DREM). Second, several adaptive estimation algorithms are proposed for the scalar scenario. In such a case, if the regressor may be nullified asymptotically or in a finite time, then the problem of estimation is also posed on a finite interval of time. Robustness of the proposed algorithms with respect to measurement noise and exogenous disturbances is analyzed. The efficiency of the designed estimators is demonstrated in numeric experiments for academic examples.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
Source :
Fichiers
- https://hal.inria.fr/hal-02196992/document
- Accès libre
- Accéder au document
- https://hal.inria.fr/hal-02196992/document
- Accès libre
- Accéder au document
- https://hal.inria.fr/hal-01998043/file/FT_Adaptive_J.pdf
- Accès libre
- Accéder au document
- https://hal.inria.fr/hal-02196992/document
- Accès libre
- Accéder au document
- https://hal.inria.fr/hal-01998043/file/FT_Adaptive_J.pdf
- Accès libre
- Accéder au document
- document
- Accès libre
- Accéder au document
- FT_Adaptive_J.pdf
- Accès libre
- Accéder au document
- FT_Adaptive_J.pdf
- Accès libre
- Accéder au document