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Robust fault detection for vehicle lateral dynamics

Authors: Sebastien Varrier; Damien Koenig; John Jairo Martinez 0001;

Robust fault detection for vehicle lateral dynamics

Abstract

This paper investigates the problem of fault detection and isolation (FDI) for vehicle lateral dynamics. The system under consideration is a Linear Parameter Varying (LPV) model, where the scheduling parameter is related to the vehicle speed. The heart of the proposed approach relies in synthesizing robust residuals for some specified working speed. The robustness guaranties the validity between each working points. Synthesis of robust residuals is inspired from the well-known parity-space method but extended for uncertain systems. The final fault detector is reconstructed by switching from the different residuals according to the speed. An applicative illustration is presented to detect a sensor fault on a vehicle lateral dynamic system. The measurements have been provided by the MIPS laboratory in collaboration within the French INOVE project.

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    influence
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Average
Top 10%
Top 10%
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