Fault sensor detection and estimation based ...
Type de document :
Autre communication scientifique (congrès sans actes - poster - séminaire...): Communication dans un congrès avec actes
Titre :
Fault sensor detection and estimation based on LPV observer for vehicle
Auteur(s) :
Alaridh, Ibrahim [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Aitouche, Abdel [Auteur]
Diagnostic, Commande et Observation pour des systèmes Tolérants aux fautes [DiCOT]
Hautes Etudes d’Ingénieur [Lille] [HEI]
Zemouche, Ali [Auteur]
Centre de Recherche en Automatique de Nancy [CRAN]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Aitouche, Abdel [Auteur]
Diagnostic, Commande et Observation pour des systèmes Tolérants aux fautes [DiCOT]
Hautes Etudes d’Ingénieur [Lille] [HEI]
Zemouche, Ali [Auteur]
Centre de Recherche en Automatique de Nancy [CRAN]
Titre de la manifestation scientifique :
7th International Conference on Systems and Control, ICSC 2018
Ville :
Valencia
Pays :
Espagne
Date de début de la manifestation scientifique :
2018-10-24
Date de publication :
2018-10-24
Discipline(s) HAL :
Sciences de l'ingénieur [physics]/Automatique / Robotique
Résumé en anglais : [en]
This paper deals with a fault sensor detection and estimation based on Unknown Input Observer (UIO) for vehicle lateral dynamics. The vehicle lateral dynamics is represented by a fourth degree of freedom model. This nonlinear ...
Lire la suite >This paper deals with a fault sensor detection and estimation based on Unknown Input Observer (UIO) for vehicle lateral dynamics. The vehicle lateral dynamics is represented by a fourth degree of freedom model. This nonlinear model is transformed into linear parameter varying model where the longitudinal velocity is considered as parameter varying. Then, an Unknown Input Observer is designed in order to reconstruct the state variables in presence of sensor faults. Based on Lyapunov theory, the observer gains are computed by Linear Matrix Inequalities. The approach can discriminate sensor faults from disturbances. Simulation results are given to show the effectiveness of the proposed approach to detect sensor faults subject to disturbances.Lire moins >
Lire la suite >This paper deals with a fault sensor detection and estimation based on Unknown Input Observer (UIO) for vehicle lateral dynamics. The vehicle lateral dynamics is represented by a fourth degree of freedom model. This nonlinear model is transformed into linear parameter varying model where the longitudinal velocity is considered as parameter varying. Then, an Unknown Input Observer is designed in order to reconstruct the state variables in presence of sensor faults. Based on Lyapunov theory, the observer gains are computed by Linear Matrix Inequalities. The approach can discriminate sensor faults from disturbances. Simulation results are given to show the effectiveness of the proposed approach to detect sensor faults subject to disturbances.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
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