LPV unknown input observer based fault ...
Type de document :
Autre communication scientifique (congrès sans actes - poster - séminaire...): Communication dans un congrès avec actes
Titre :
LPV unknown input observer based fault sensor diagnosis for vehicle lateral dynamics
Auteur(s) :
Alaridh, Ibrahim [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Aitouche, Abdel [Auteur]
Hautes Etudes d’Ingénieur [Lille] [HEI]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Zemouche, Ali [Auteur]
Centre de Recherche en Automatique de Nancy [CRAN]
Boulkroune, Boulaïd [Auteur]
Flanders Make [Lommel]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Aitouche, Abdel [Auteur]
Hautes Etudes d’Ingénieur [Lille] [HEI]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Zemouche, Ali [Auteur]
Centre de Recherche en Automatique de Nancy [CRAN]
Boulkroune, Boulaïd [Auteur]
Flanders Make [Lommel]
Titre de la manifestation scientifique :
14th International Workshop on Advanced Control and Diagnosis, ACD 2017
Ville :
Bucharest
Pays :
Roumanie
Date de début de la manifestation scientifique :
2017-11-16
Discipline(s) HAL :
Sciences de l'ingénieur [physics]/Automatique / Robotique
Résumé en anglais : [en]
This study deals with a fault sensor estimation and state variables estimation based on Unknown Input Observer for automated steering vehicle. The vehicle lateral dynamics is represented by a fourth degree of freedom model. ...
Lire la suite >This study deals with a fault sensor estimation and state variables estimation based on Unknown Input Observer for automated steering vehicle. 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 states variables in presence of sensor faults. Based on Lyapunov theory, the observer gains are computed using Linear Matrix Inequalities. Simulation results are given to show the effectiveness of the proposed approach to detect sensor faults and to discriminate the disturbance.Lire moins >
Lire la suite >This study deals with a fault sensor estimation and state variables estimation based on Unknown Input Observer for automated steering vehicle. 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 states variables in presence of sensor faults. Based on Lyapunov theory, the observer gains are computed using Linear Matrix Inequalities. Simulation results are given to show the effectiveness of the proposed approach to detect sensor faults and to discriminate the disturbance.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
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