Fault sensor detection and estimation based on LPV observer for vehicle

Abstract : 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.
Type de document :
Communication dans un congrès
7th International Conference on Systems and Control, ICSC 2018, Oct 2018, Valencia, Spain. 2018
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https://hal.archives-ouvertes.fr/hal-01872858
Contributeur : Abdel Aitouche <>
Soumis le : mercredi 12 septembre 2018 - 15:32:41
Dernière modification le : vendredi 7 décembre 2018 - 17:53:33

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  • HAL Id : hal-01872858, version 1

Citation

Ibrahim Alaridh, Abdel Aitouche, Ali Zemouche. Fault sensor detection and estimation based on LPV observer for vehicle. 7th International Conference on Systems and Control, ICSC 2018, Oct 2018, Valencia, Spain. 2018. 〈hal-01872858〉

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