Health monitoring of hybrid systems using Hybrid Particle Petri Nets

Abstract

This paper presents an approach of model-based diagnosis for the health monitoring of hybrid systems. These systems have both continuous and discrete dynamics. Modified Particle Petri Nets, initially defined in the context of hybrid systems mission monitoring, are extended to estimate the health state of hybrid systems. This formalism takes into account both uncertainties about the system knowledge and about diagnosis results. The generation of a diagnoser is proposed to track online the system health state under uncertainties by using particle filter. To include more complex characteristics of the system, as its degradations for prognosis purpose, an enriched formalism called Hybrid Particle Petri Nets is defined.