Adaptive Estimation for Uncertain Nonlinear ...
Type de document :
Compte-rendu et recension critique d'ouvrage
DOI :
Titre :
Adaptive Estimation for Uncertain Nonlinear Systems with Measurement Noise: A Sliding-Mode Observer Approach
Auteur(s) :
Franco, Roberto [Auteur]
Instituto Tecnologico de la Laguna [ITL]
Ríos, Héctor [Auteur]
Instituto Tecnologico de la Laguna [ITL]
Efimov, Denis [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Perruquetti, Wilfrid [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Instituto Tecnologico de la Laguna [ITL]
Ríos, Héctor [Auteur]
Instituto Tecnologico de la Laguna [ITL]
Efimov, Denis [Auteur]
Finite-time control and estimation for distributed systems [VALSE]
Perruquetti, Wilfrid [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Titre de la revue :
International Journal of Robust and Nonlinear Control
Éditeur :
Wiley
Date de publication :
2020-09-15
ISSN :
1049-8923
Mot(s)-clé(s) en anglais :
Adaptive Observer
Nonlinear Systems
Sliding-Modes
Nonlinear Systems
Sliding-Modes
Discipline(s) HAL :
Sciences de l'ingénieur [physics]/Automatique / Robotique
Résumé en anglais : [en]
This paper deals with the problem of adaptive estimation, i.e. the simultaneous estimation of the state and time-varying parameters, in the presence of measurement noise and state disturbances, for a class of uncertain ...
Lire la suite >This paper deals with the problem of adaptive estimation, i.e. the simultaneous estimation of the state and time-varying parameters, in the presence of measurement noise and state disturbances, for a class of uncertain nonlinear systems. An adap-tive observer is proposed based on a nonlinear time-varying parameter identification algorithm and a sliding-mode observer. The nonlinear time-varying parameter identification algorithm provides a fixed-time rate of convergence, to a neighborhood of the origin, while the sliding-mode observer ensures ultimate boundedness for the state estimation error attenuating the effects of the external disturbances. Linear matrix inequalities are provided for the synthesis of the adaptive observer while the convergence proofs are given based on the Lyapunov and Input-to-State Stability theory. Finally, some simulation results show the feasibility of the proposed approach.Lire moins >
Lire la suite >This paper deals with the problem of adaptive estimation, i.e. the simultaneous estimation of the state and time-varying parameters, in the presence of measurement noise and state disturbances, for a class of uncertain nonlinear systems. An adap-tive observer is proposed based on a nonlinear time-varying parameter identification algorithm and a sliding-mode observer. The nonlinear time-varying parameter identification algorithm provides a fixed-time rate of convergence, to a neighborhood of the origin, while the sliding-mode observer ensures ultimate boundedness for the state estimation error attenuating the effects of the external disturbances. Linear matrix inequalities are provided for the synthesis of the adaptive observer while the convergence proofs are given based on the Lyapunov and Input-to-State Stability theory. Finally, some simulation results show the feasibility of the proposed approach.Lire moins >
Langue :
Anglais
Vulgarisation :
Non
Collections :
Source :
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