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Counterexample-Guided Abstraction-Refinement for Hybrid Systems Diagnosability Analysis

20 pagesPublished: January 6, 2018

Abstract

Verifying behavioral or safety properties of hybrid systems, either at design stage such as state reachability and diagnosability, or on-line such as fault detection and isolation is a challenging task. We are concerned here with abstractions oriented towards hybrid systems diagnosability checking. The verification can be done on the abstraction by classical methods developed for discrete event systems extended with time constraints, which provide a counterexample in case of non-diagnosability. The absence of such a counterexample proves the diagnosability of the original hybrid system. In the presence of a counterexample, the first step is to check if it is not a spurious effect of the abstraction and actually exists for the hybrid system, witnessing thus non-diagnosability. Otherwise, we show how to refine the abstraction, guided by the elimination of the counterexample, and continue the process of looking for another counterexample until either a final result is obtained or we reach an inconclusive verdict. We make use of qualitative modeling and reasoning to compute discrete abstractions. Abstractions as timed automata are particularly studied as they allow one to handle time constraints that can be captured at a qualitative level from the hybrid system.

Keyphrases: abstraction, Counter-example guided abstraction refinement, Diagnosability, hybrid systems, timed automata

In: Marina Zanella, Ingo Pill and Alessandro Cimatti (editors). 28th International Workshop on Principles of Diagnosis (DX'17), vol 4, pages 124--143

Links:
BibTeX entry
@inproceedings{DX'17:Counterexample_Guided_Abstraction_Refinement_for_Hybrid,
  author    = {Hadi Zaatiti and Lina Ye and Philippe Dague and Jean-Pierre Gallois},
  title     = {Counterexample-Guided Abstraction-Refinement for Hybrid Systems Diagnosability Analysis},
  booktitle = {28th International Workshop on Principles of Diagnosis (DX'17)},
  editor    = {Marina Zanella and Ingo Pill and Alessandro Cimatti},
  series    = {Kalpa Publications in Computing},
  volume    = {4},
  pages     = {124--143},
  year      = {2018},
  publisher = {EasyChair},
  bibsource = {EasyChair, http://www.easychair.org},
  issn      = {2515-1762},
  url       = {https://easychair.org/publications/paper/wthm},
  doi       = {10.29007/t8n3}}
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