Robust fault detection using set-based approaches for LPV systems: Application to autonomous vehicles
Document typeConference report
Rights accessOpen Access
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 4.0 International
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.
CitationZhang, S.; Puig, V.; Ifqir, S. Robust fault detection using set-based approaches for LPV systems: Application to autonomous vehicles. A: IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes. "IFAC-PapersOnLine". 2022, p. 31-36. ISBN 2405-8963. DOI 10.1016/j.ifacol.2022.07.101.
|2638-Robust-Fau ... o-Autonomous-Vehicles-.pdf||1,011Mb||View/Open|