Hiba Fawzia Bouchama's thesis defense

Summary

This thesis work contributes to the collaborative project "Train de Fret Autonome"' led by the SNCF and aims to automate freight train driving in order to guarantee reliable and safe autonomous driving in all environmental conditions. In this context, our contributions concern the development of estimators for accurately reconstructing the train's position and longitudinal speed under variable wheel-rail adhesion conditions.

The major difficulty stems from the fact that on-board odometric sensors provide a measurement of wheel rotation at axle level, but do not directly detect the phenomenon of wheel slip, resulting in a high degree of inaccuracy in estimating the longitudinal speed of the train. To overcome this problem, it is necessary to make a precise recalibration using the position of the train measured by radio beacons installed on the rail. However, this measurement is discrete, with a variable sampling period.

One of the challenges is to consider train measurements that combine both considered continuous and aperiodically sampled measurements. Thus, the main theoretical contribution of this thesis is the design of a continuous-discrete observer for a class of multi-input/multi-output systems with continuous outputs marred by measurement noise and aperiodically sampled outputs. This observer is designed to meet the specifications of the "Autonomous Freight Train" project, in order to estimate train speed under variable adhesion conditions. The performance of this observer is shown in simulation and compared with other approaches to train speed estimation, then validated experimentally via a test campaign carried out at the Centre d'Essai Ferroviaire de Tronville-en-Barrois.

Key words

Autonomous train, observer synthesis, grip force, continuous and aperiodically sampled measurements, continuous-discrete observer (CDO), time-varying exponential gain.

Jury composition

Mrs Lydie NOUVELIERE, Maitresse des conférences HDR, Université d'Evry Val d'Essonne (Rapporteur)
Mondher FARZA, Professeur des universités HDR, Université de Caen Normandie (Rapporteur)
Kevin GUELTON, Professeur des universités HDR, Université de Reims Champagne-Ardenne (Examiner)
Jimmy LAUBER, Professeur des universités HDR, Institut Nationale des Sciences Appliquées (Thesis Director)
Michael DEFOORT, Professeur des universités HDR, Institut Nationale des Sciences Appliquées (Thesis co-director)
Denis BERDJAG, Maitre des conférences, Université Polytechnique Hauts-de-France (Co-supervisor)
Smail ZIANI, IRT Railenium (Guest)