Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

State Observation and Diagnosis of Discrete-Event Systems Described by Stochastic Automata

  • Published:
Discrete Event Dynamic Systems Aims and scope Submit manuscript

Abstract

The problems ofstate observation and diagnosis are solved for discrete–eventsystems, which are described by stochastic automata. As manysystems are not observable in the sense that it is possible toreconstruct the state unambiguously, the observation problemis set up as the problem of determining the smallest possibleset of states that are compatible with the measured input andoutput sequences. The diagnostic problem is shown to be, in principle,an observation problem. Conditions for the observability anddiagnosability of stochastic automata are presented. The resultsare illustrated by examples.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Aghasaryan, A., Fabre, E., Benveniste, A., Boubour, R., and Jard, C. 1998. Fault detection and diagnosis in distributed systems: An approach by partially stochastic Petri-nets. Discrete Event Dynamic Systems: Theory and Applications 8: 203–231.

    Google Scholar 

  • Bukharaev, R. 1995. Theorie der Stochastischen Automaten. Stuttgart: B. G. Teubner.

    Google Scholar 

  • Carlyle, J. W. 1965. State-calculable stochastic sequential machines, equivalences and events. Switching circuit theory and logic. Design IEEE Conf. Rec. 16C13, New York.

  • Cao, C., Lin, F., and Lin, Z.-H. 1997. Why event observation: Observability revisited. Discrete Event Dynamic Systems: Theory and Applications 7: 127–149.

    Google Scholar 

  • Cassandras, C. G., and Lafortune, S. 1999. Introduction to Discrete Event Systems. Boston: Kluwer Academic Publ.

    Google Scholar 

  • Hamscher, W., Console, L., and deKleer, J. (Eds.) 1992. Readings in Model-based Diagnosis. San Mateo: Morgan Kaufmann Pub.

    Google Scholar 

  • Lichtenberg, G., and Zacharias, M. 1997. Qualitative Modelling Toolbox Users Guide. TU Hamburg-Harburg, AB Regelungstechnik, http://www.tu-harburg.de/rts.

    Google Scholar 

  • Lin, F. 1994. Diagnosability of discrete-event systems and its applications. Discrete Event Dynamic Systems 4: 197–212.

    Google Scholar 

  • Lin, F., and Wonham, W. M. 1988. On observability of discrete-event systems. Information Sciences 44: 173–198.

    Google Scholar 

  • Lunze, J. 1994. Qualitative modelling of linear dynamical systems with quantised state measurements. Automatica 30: 417–431.

    Google Scholar 

  • Lunze, J. 1995. Künstliche Intelligenz für Ingenieure, Band 2. München, Wien: Oldenbourg.

    Google Scholar 

  • Lunze, J. 1998. On the Markov property of quantised state measurement sequences. Automatica 34: 1439–1444.

    Google Scholar 

  • Lunze, J., and Schröder, J. 1999. Process diagnosis based on a discrete-event description. Automatisierungstechnik 47: 358–365.

    Google Scholar 

  • Lunze, J., Nixdorf, B., and Schröder, J. 1999. Deterministic discrete-event representations of linear continuousvariable systems. Automatica 35: 395–406.

    Google Scholar 

  • Özveren, C. M., and Willsky, A. S. 1990. Observability of discrete-event dynamic systems. IEEE Trans.Automatic Control 35: 797–806.

    Google Scholar 

  • Portinale, L. 1997. Behavioral Petri-nets: A model for diagnostic knowledge representation and reasoning. IEEE Trans. SMC-27: 184–195.

    Google Scholar 

  • Ramadge, P. J., and Wonham, W. M. 1989. The control of discrete-event systems. Proceedings of the IEEE 77: 81–98.

    Google Scholar 

  • Sampath, M., Sengupta, R., Lafurtune, S., Sinnamohideen, K., and Teneketzis, D. 1996. Failure diagnosis using discrete-event models. Proc. Conf. Decision Control, Lake BuenaVista, 1994, pp. 3110–3116; extended version in IEEE Trans. CST-4(2), 1996.

    Google Scholar 

  • Sampath, M., Sengupta, R., Lafurtune, S., Sinnamohideen, K., and Teneketzis, D. 1995. Diagnosability of discrete-event systems. IEEE Trans. AC-40: 1555–1575.

    Google Scholar 

  • Schiller, F., and Schröder, J. 1999. Combining qualitative model-based diagnosis and observation within faulttolerant systems. AI Communications 12: 79–98.

    Google Scholar 

  • Starke, P. H. 1969. Abstrakte Automaten. Berlin: VEB Deutscher Verlag.

    Google Scholar 

  • Srinivasan, V. S., and Jafari, M. A. 1993. Fault detection/monitoring using timed Petri-nets. IEEE Trans. SMC-23.

  • Willems, J. 1991. Paradigms and puzzels in the theory of dynamical systems. IEEE Transactions on Automatic Control 36: 259–294.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Technical University Hamburg–Harburg, Eissendorfer Str. 40, 21071, Hamburg, Germany

    J. Lunze & J. Schröder

Authors
  1. J. Lunze
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. Schröder
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lunze, J., Schröder, J. State Observation and Diagnosis of Discrete-Event Systems Described by Stochastic Automata. Discrete Event Dynamic Systems 11, 319–369 (2001). https://doi.org/10.1023/A:1011273108731

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1011273108731

Search

Navigation