An Adaptive Sliding-Mode Observer for a ...
Type de document :
Compte-rendu et recension critique d'ouvrage
DOI :
Titre :
An Adaptive Sliding-Mode Observer for a Class of Uncertain Nonlinear Systems
Auteur(s) :
Ríos, Héctor [Auteur]
Instituto Tecnologico de la Laguna [ITL]
Efimov, Denis [Auteur]
Non-Asymptotic estimation for online systems [NON-A-POST]
Perruquetti, Wilfrid [Auteur]
Centrale Lille
Non-Asymptotic estimation for online systems [NON-A]
Instituto Tecnologico de la Laguna [ITL]
Efimov, Denis [Auteur]
Non-Asymptotic estimation for online systems [NON-A-POST]
Perruquetti, Wilfrid [Auteur]
Centrale Lille
Non-Asymptotic estimation for online systems [NON-A]
Titre de la revue :
International Journal of Adaptive Control and Signal Processing
Pagination :
511 - 527
Éditeur :
Wiley
Date de publication :
2018-03
ISSN :
0890-6327
Mot(s)-clé(s) en anglais :
Adaptive observer
Sliding-modes
Nonlinear systems
Sliding-modes
Nonlinear systems
Discipline(s) HAL :
Sciences de l'ingénieur [physics]/Automatique / Robotique
Résumé en anglais : [en]
In this paper the problem of simultaneous state and parameter estimation is studied for a class of uncertain nonlinear systems. A nonlinear adaptive sliding-mode observer is proposed based on a nonlinear parameter estimation ...
Lire la suite >In this paper the problem of simultaneous state and parameter estimation is studied for a class of uncertain nonlinear systems. A nonlinear adaptive sliding-mode observer is proposed based on a nonlinear parameter estimation algorithm. It is shown that such a nonlinear algorithm provides a rate of convergence faster than exponential, i.e. faster than the classic linear algorithm. Then, the proposed parameter estimation algorithm is included in the structure of a sliding-mode state observer providing an ultimate bound for the full estimation error attenuating the effects of the external disturbances. Moreover, the synthesis of the observer is given in terms of linear matrix inequalities. The corresponding proofs of convergence are developed based on Lyapunov function approach and input-to-state stability theory. Some simulation results illustrate the efficiency of the proposed adaptive sliding-mode observer.Lire moins >
Lire la suite >In this paper the problem of simultaneous state and parameter estimation is studied for a class of uncertain nonlinear systems. A nonlinear adaptive sliding-mode observer is proposed based on a nonlinear parameter estimation algorithm. It is shown that such a nonlinear algorithm provides a rate of convergence faster than exponential, i.e. faster than the classic linear algorithm. Then, the proposed parameter estimation algorithm is included in the structure of a sliding-mode state observer providing an ultimate bound for the full estimation error attenuating the effects of the external disturbances. Moreover, the synthesis of the observer is given in terms of linear matrix inequalities. The corresponding proofs of convergence are developed based on Lyapunov function approach and input-to-state stability theory. Some simulation results illustrate the efficiency of the proposed adaptive sliding-mode observer.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
Source :
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