IRI - Robust fault detection using set-based approaches for LPV systems: Application to autonomous vehicles

Publication

Robust fault detection using set-based approaches for LPV systems: Application to autonomous vehicles

Conference Article

Conference

IFAC Symposium on Fault Detection Supervision and Safety for Technical Processes (SAFEPROCESS)

Edition

11th

Pages

31-36

Doc link

https://doi.org/10.1016/j.ifacol.2022.07.101

File

Download the digital copy of the doc pdf document

Authors

Abstract

This paper addresses the problem of robust fault detection for Linear Parameter Varying (LPV) systems using set-based approaches. Two approaches are proposed, based respectively on set-based state and parameter estimation methods, for implementing direct and inverse test for robust fault detection (FD). The uncertainties are assumed to be unknown but bounded and their effect is propagated using zonotopic sets. These robust FD test methods aim at checking the consistency between the measured and estimated behaviour obtained from estimator in the parameter or output space considering the effect of the uncertainty. When an inconsistency is detected, a fault can be indicated. A case study based on an autonomous vehicle is employed to compare the performance of proposed FD tests.

Author keywords

LPV, LMI, fault detection, zonotope, SMA

Scientific reference

S. Zhang, V. Puig and S. Ifqir. Robust fault detection using set-based approaches for LPV systems: Application to autonomous vehicles, 11th IFAC Symposium on Fault Detection Supervision and Safety for Technical Processes, 2022, Pafos, Cyprus, Vol 55 of IFAC Papers Online, pp. 31-36.