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Diagnosability verification using LTL model checking

Discrete Event Dynamic Systems (2022)Cite this article

Abstract

One of the challenges of fault diagnosis is to verify diagnosability of systems with huge state space efficiently. Model checking approaches have the potential to analyze such systems efficiently. In this work, we propose a model checking approach to deal with the problem of the diagnosability verification. We define the diagnosability property in the transition system framework. To check this property, we describe it by using an unique linear temporal logic (LTL) formula. Our approach can be carried out in model checker tools for formal verification of models, such as SPIN and NuSMV. To illustrate the efficiency of our approach we perform some experiments. First, we consider a railway level crossing benchmark, comparing the results of our approach in SPIN and NuSMV with the results found using DESLab and Supremica tools. Then, we perform an exploratory statistical analysis comparing the average size of verifiers computed with our approach in SPIN with the average size of verifiers (it number of states plus transitions) computed with DESLab, which is a tool for diagnosability verification of Discrete Event Systems (DES) that uses the same foundation idea.

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Notes

  1. In this paper we always consider that x0 ∈ Xcoac

  2. http://projects.laas.fr/tina/home.php

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Authors and Affiliations

  1. COPPE - Programa de Engenharia Elétrica, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil

    Thiago M. Tuxi, Lilian K. Carvalho & Eduardo V. L. Nunes

  2. Programa de Pós-Graduação em Engenharia de Defesa (PGED), Instituto Militar de Engenharia (IME), Rio de Janeiro, RJ, Brazil

    Antonio E. C. da Cunha

Authors
  1. Thiago M. Tuxi
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  2. Lilian K. Carvalho
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  3. Eduardo V. L. Nunes
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  4. Antonio E. C. da Cunha
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Correspondence to Thiago M. Tuxi.

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This article belongs to the Topical Collection: Topical Collection on Control 2022 Guest Editors: Joerg Raisch, Carla Seatzu and Shigemasa Takai

This work is financed in part by CNPq, CAPES Finance Code 001, FAPERJ and the Brazilian Army Force.

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Tuxi, T.M., Carvalho, L.K., Nunes, E.V.L. et al. Diagnosability verification using LTL model checking. Discrete Event Dyn Syst (2022). https://doi.org/10.1007/s10626-022-00360-w

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Keywords

  • Diagnosability
  • Model-checking
  • Linear temporal logic
  • Statistical analysis
  • Tools