Set-membership fault detection under noisy environment with application to the detection of abnormal aircraft control surface positions

Abstract : The paper develops a set membership detection methodology which is applied to the detection of abnormal positions of aircraft control surfaces. Robust and early detection of such abnormal positions is an important issue for early system reconfiguration and overall optimization of aircraft design. In order to improve fault sensitivity while ensuring a high level of robustness, the method combines a data-driven characterization of noise and a model-driven approach based on interval prediction. The efficiency of the proposed methodology is illustrated through simulation results obtained based on data recorded in several flight scenarios of a highly representative Aircraft benchmark.
Type de document :
Article dans une revue
International Journal of Control and Computers, 2015
Liste complète des métadonnées

https://hal.archives-ouvertes.fr/hal-01126600
Contributeur : Laboratoire Cedric <>
Soumis le : vendredi 6 mars 2015 - 12:03:19
Dernière modification le : samedi 9 février 2019 - 01:26:11

Identifiants

  • HAL Id : hal-01126600, version 1

Citation

Rihab El Houda Thabet, Christophe Combastel, Tarek Raïssi, Ali Zolghadri. Set-membership fault detection under noisy environment with application to the detection of abnormal aircraft control surface positions. International Journal of Control and Computers, 2015. 〈hal-01126600〉

Partager

Métriques

Consultations de la notice

108