Fault detection using Enhanced Adaptive degrees of freedom χ2-statistics method for Linear systems with mixed uncertainties - LAAS - Laboratoire d'Analyse et d'Architecture des Systèmes
Communication Dans Un Congrès Année : 2023

Fault detection using Enhanced Adaptive degrees of freedom χ2-statistics method for Linear systems with mixed uncertainties

Résumé

This article is concerned with a fault detection enhancement method using adaptive amplifier coefficients (a.a.c.) concept. It is developed for linear systems with mixed uncertainties (stochastic and bounded uncertainties framework). The study provides, also, analysis and discussions about the applicability and the efficiency of the enhanced method to several sensors fault error types. Simulations on a vehicle bicycle model (validated by experimental tests on the Renault Megane) are presented to emphasize on the performances of the developed method.
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Dates et versions

hal-04069624 , version 1 (08-06-2023)

Identifiants

  • HAL Id : hal-04069624 , version 1

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Quoc Hung Lu, Soheib Fergani, Carine Jauberthie. Fault detection using Enhanced Adaptive degrees of freedom χ2-statistics method for Linear systems with mixed uncertainties. The 22nd World Congress of the International Federation of Automatic Control, Jul 2023, Yokohama, Japan. ⟨hal-04069624⟩
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