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.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01872858
Contributor : Abdel Aitouche <>
Submitted on : Wednesday, September 12, 2018 - 3:32:41 PM
Last modification on : Saturday, March 23, 2019 - 1:26:12 AM

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  • HAL Id : hal-01872858, version 1

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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. ⟨hal-01872858⟩

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