HPPN-based Prognosis for Hybrid Systems
Résumé
This paper presents a model-based prognosis method for hybrid
systems i.e. that have both discrete and continuous behaviors.
The current state of the hybrid system is estimated
by a diagnosis process and the prognosis process uses this
state estimation to predict the future states and to determine
the end of life (EOL) or the remaining useful life (RUL) of
the system. The Hybrid Particle Petri Nets (HPPN) formalism
is used to model the hybrid system behavior and degradation.
A HPPN-based diagnoser has already been defined to
provide a current state estimation that takes uncertainty about
the system model and observations into account. We propose
to generate a prognoser from the HPPN model of the system.
This prognoser is initialized and updated with the result of the
HPPN-based diagnoser. It computes a distribution of beliefs
over the future mode trajectories of the system and predicts
the system RUL/EOL. The prognosis methodology is demonstrated
on a three tanks example.
Domaines
Automatique / RobotiqueOrigine | Fichiers produits par l'(les) auteur(s) |
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