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Diagnosis of Discrete Event Systems Using Decentralized Architectures

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An Erratum to this article was published on 05 April 2013

Abstract

Decentralized diagnosis of discrete event systems has received a lot of attention to deal with distributed systems or with systems that may be too large to be diagnosed by one centralized site. This paper casts the problem of decentralized diagnosis in a new hierarchical framework. A key feature is the exploitation of different local decisions together with appropriate rules for their fusion. This includes local diagnosis decisions that can be interpreted as “conditional decisions.” Under this new framework, a series of new decentralized architectures are defined and studied. The properties of their corresponding notions of decentralized diagnosability are characterized and their relationship with existing work described. Corresponding verification algorithms are also presented and on-line diagnosis strategies discussed.

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Authors and Affiliations

  1. Department of EECS, University of Michigan, Ann Arbor, MI, 48109-2122, USA

    Yin Wang & Stéphane Lafortune

  2. Idaho National Laboratory, Idaho Falls, ID, 83403-2528, USA

    Tae-Sic Yoo

Authors
  1. Yin Wang
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  2. Tae-Sic Yoo
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  3. Stéphane Lafortune
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Corresponding author

Correspondence to Yin Wang.

Additional information

This research is supported in part by NSF Grant CCR-0325571, by ONR grant N00014-03-1-0232, and by a grant from the Xerox University Affairs Committee.

An erratum to this article can be found online at http://dx.doi.org/10.1007/s10626-013-0161-7.

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Wang, Y., Yoo, TS. & Lafortune, S. Diagnosis of Discrete Event Systems Using Decentralized Architectures. Discrete Event Dyn Syst 17, 233–263 (2007). https://doi.org/10.1007/s10626-006-0006-8

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  • DOI: https://doi.org/10.1007/s10626-006-0006-8

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