Robust fault detection for vehicle lateral dynamics: Azonotope-based set-membership approach
Document typeConference lecture
Rights accessOpen Access
In this work, a model-based fault detection layoutfor vehicle lateral dynamics system is presented. The majorfocus in this study is on the handling of model uncertainties andunknown inputs. In fact, the vehicle lateral model is affectedby several parameter variations such as longitudinal velocity,cornering stiffnesses coefficients and unknown inputs like windgust disturbances. Cornering stiffness parameters variation isconsidered to be unknown but bounded with known compactset. Their effect is addressed by generating intervals for theresiduals based on the zonotope representation of all possiblevalues. The developed fault detection procedure has been testedusing real driving data acquired from a prototype vehicle.Index Terms— Robust fault detection, interval models,zonotopes, set-membership, switched uncertain systems, LMIs,input-to-state stability, arbitrary switching.
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CitationPuig, V. Robust fault detection for vehicle lateral dynamics: Azonotope-based set-membership approach. A: International IEEE Conference on Intelligent Transportation Systems. "21st IEEE International Conference on Intelligent Transportation Systems". 2018, p. 1364-1369.