Coupling Continuous and Discrete Event System Techniques for Hybrid System Diagnosability Analysis

Mehdi Bayoudh (1) , Louise Travé-Massuyès (2) , Xavier Olive (3)

1 LAAS - Laboratoire d'analyse et d'architecture des systèmes
2 LAAS-DISCO - Équipe DIagnostic, Supervision et COnduite
3 TAS - Thales Alenia Space [Toulouse]

In this paper we propose a hybrid system modeling framework aimed at analyzing diagnosability. In this framework, the hybrid system is seen as the composition of an underlying discrete event and an underlying continuous systems. Diagnosability of these two underlying systems are fully analyzed and new results are provided for the underlying continuous system (called the multimode system). Based on these results, a hybrid language that contains 'natural' discrete events and discrete events capturing the continuous dynamics, is defined. On the basis of this language the diagnosability definition of hybrid systems is provided. With respect to this defini- tion, we prove that the diagnosability of the underlying continuous or the discrete event system is only a sufficient condition. Diagnosability of hybrid systems must be decided by coupling both discrete event and continuous informations. Finally, the necessary and sufficient condition of hybrid diagnosability is given.

Mots clés: Diagnosability; Hybrid systems

Domaines: Intelligence artificielle [cs.AI]

Mehdi Bayoudh, Louise Travé-Massuyès, Xavier Olive. Coupling Continuous and Discrete Event System Techniques for Hybrid System Diagnosability Analysis. 18th European Conference on Artificial Intelligence (ECAI 08), Jul 2008, Patras, Greece. p 219-223. ⟨hal-00530951⟩