State and sensor faults estimation via a proportional integral observer
Résumé
This paper deals with the problem of fault detection and identification in noisy systems. A proportional integral observer with unknown inputs is used in order to reconstruct state and sensors faults. A mathematical transformation is made to conceive an augmented system, in which the initial sensor fault appear as an unknown input. This reconstruction is made by the use of a proportionnel integral observer. The noise effect on the state and fault estimation errors is also minimized. The obtained results are then extended to nonlinear systems described by nonlinear Takagi-Sugeno models.
Domaines
Automatique / Robotique
Origine : Fichiers produits par l'(les) auteur(s)
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