Communication Dans Un Congrès Année : 2017

LPV unknown input observer based fault sensor diagnosis for vehicle lateral dynamics

Résumé

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.

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Dates et versions

hal-01736848 , version 1 (18-03-2018)

Identifiants

  • HAL Id : hal-01736848 , version 1

Citer

Ibrahim Alaridh, Abdel Aitouche, Ali Zemouche, Boulaïd Boulkroune. LPV unknown input observer based fault sensor diagnosis for vehicle lateral dynamics. 14th International Workshop on Advanced Control and Diagnosis, ACD 2017, Nov 2017, Bucharest, Romania. ⟨hal-01736848⟩
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