Abstract
In partially observed Petri nets, diagnosis is the task of detecting whether the given sequence of observed labels indicates that some unobservable fault has occurred. Diagnosability is an associated property of the Petri net, stating that in any possible execution, an occurrence of a fault can eventually be diagnosed.
In this article, we consider diagnosability under the weak fairness (WF) assumption, which intuitively states that no transition from a given set can stay enabled forever—it must eventually either fire or be disabled. We show that a previous approach to WF-diagnosability in the literature has a major flaw and present a corrected notion. Moreover, we present an efficient method for verifying WF-diagnosability based on a reduction to LTL-X model checking. An important advantage of this method is that the LTL-X formula is fixed—in particular, the WF assumption does not have to be expressed as a part of it (which would make the formula length proportional to the size of the specification), but rather the ability of existing model checkers to handle weak fairness directly is exploited.
- A. Agarwal, A. Madalinski, and S. Haar. 2012. Effective verification of weak diagnosability. In Proc. SAFEPROCESS’12. IFAC. DOI:http://dx.doi.org/10.3182/20120829-3-MX-2028.00083Google Scholar
- S. Biswas. 2013a. Equivalence of fair diagnosability and stochastic diagnosability of discrete event systems. In Proc. IEEE SMC. 378--383. Google Scholar
Digital Library
- S. Biswas. 2013b. Fair diagnosability in PN-based DES models. In Proc. ICCA. 378--383.Google Scholar
- S. Biswas, D. Sarkar, S. Mudhopadhyay, and A. Patra. 2010. Fairness of transitions in diagnosability analysis of discrete event systems. Discrete Event Dyn. Syst. Theory Appl. 20, 3 (September 2010), 349--376. Google Scholar
Digital Library
- M. P. Cabasino, A. Giua, S. Lafortune, and C. Seatzu. 2012. A new approach for diagnosability analysis of Petri nets using verifier nets. IEEE Trans. Autom. Control 57, 12 (December 2012), 3104--3117.Google Scholar
Cross Ref
- V. Germanos, S. Haar, V. Khomenko, and S. Schwoon. 2014. Diagnosability under weak fairness. In Proc. ACSD’14, A. Mokhov and L. Bernardinello (Eds.). IEEE Computing Society Press, 132--141. Google Scholar
Digital Library
- S. Haar, C. Rodríguez, and S. Schwoon. 2013. Reveal your faults: It’s only fair! In Proc. ACSD’13. IEEE Computer Society Press, 120--129. DOI:http://dx.doi.org/10.1109/ACSD.2013.15 Google Scholar
Digital Library
- S. Jiang, Z. Huang, V. Chandra, and R. Kumar. 2001. A polynomial algorithm for testing diagnosability of discrete event systems. IEEE Trans. Autom. Control 46, 8, 1318--1321.Google Scholar
Cross Ref
- L. Lamport. 1983. What good is temporal logic? In Proc. IFIP Congr.’83. Elsevier, 657--668.Google Scholar
- A. Madalinski and V. Khomenko. 2010. Diagnosability verification with parallel LTL-X model checking based on Petri net unfoldings. In Proc. SysTol’10. IEEE Computer Society Press, 398--403.Google Scholar
- A. Madalinski, F. Nouioua, and P. Dague. 2010. Diagnosability verification with Petri net unfoldings. KES J. 14, 2 (2010), 49--55. DOI:http://dx.doi.org/10.3233/KES-2010-0191 Google Scholar
Digital Library
- M. Mäkelä. 2005. Maria: The Modular Reachability Analyzer. Retrieved from http://www.tcs.hut.fi/Software/maria/index.en.html.Google Scholar
- A. Pnueli. 1977. The temporal logic of programs. In Proc. FOCS’77. 46--57. Google Scholar
Digital Library
- M. Sampath, R. Sengupta, S. Lafortune, K. Sinnamohideen, and D. Teneketzis. 1995. Diagnosability of discrete events systems. IEEE Trans. Autom. Control 40, 9 (1995), 1555--1575.Google Scholar
Cross Ref
- A. Schumann and Y. Pencolé. 2007. Scalable diagnosability checking of event-driven systems. In Proc. IJCAI’07. 575--580. Google Scholar
Digital Library
- D. Thorsley and D. Teneketzis. 2005. Diagnosability of Stochastic discrete event systems. IEEE Trans. Autom. Control 50, 4 (2005), 476--492.Google Scholar
Cross Ref
- W. Vogler. 1995. Fairness and partial order semantics. Inf. Process. Lett. 55, 1 (1995), 33--39. Google Scholar
Digital Library
- T.-S. Yoo and S. Lafortune. 2002. Polynomial-time verification of diagnosability of partially observed discrete-event systems. IEEE Trans. Autom. Control 47, 9 (2002), 1491--1495.Google Scholar
Cross Ref
Index Terms
Diagnosability under Weak Fairness
Recommendations
Diagnosability under Weak Fairness
ACSD '14: Proceedings of the 2014 14th International Conference on Application of Concurrency to System DesignIn partially observed Petri nets, diagnosis is the task of detecting whether or not the given sequence of observed labels indicates that some unobservable fault has occurred. Diagnosability is an associated property of the Petri net, stating that in any ...
The Complexity of Diagnosability and Opacity Verification for Petri Nets
Application and Theory of Petri Nets and Other Models of Concurrency: Special Issue of Selected Papers from Petri Nets 2017Diagnosability and opacity are two well-studied problems in discrete-event systems. We revisit these two problems with respect to expressiveness and complexity issues.
We first relate different notions of diagnosability and opacity. We consider in ...
Formal verification of ASMs using MDGs
We present a framework for the formal verification of abstract state machine (ASM) designs using the multiway decision graphs (MDG) tool. ASM is a state based language for describing transition systems. MDG provides symbolic representation of transition ...






Comments