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Decentralized and Distributed Active Fault Diagnosis for Stochastic Systems with Indirect Observations

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43956351" target="_blank" >RIV/49777513:23520/19:43956351 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/9011433" target="_blank" >https://ieeexplore.ieee.org/document/9011433</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Decentralized and Distributed Active Fault Diagnosis for Stochastic Systems with Indirect Observations

  • Original language description

    The active fault diagnosis (AFD) framework for stochastic large scale systems is treated. The systems are assumed to be decomposed into weakly coupled input-decentralized subsystems. Each subsystem is represented by a set of models describing fault-free and faulty behavior of the subsystems. The paper focuses on the problem formulation where the state of each subsystem is observed only indirectly using noisy measurements. The decentralized and distributed architectures of the AFD are considered, the corresponding estimation and optimization problems are set up and approximate solutions to these problems are proposed. The performance of the active fault detector in both architectures is illustrated using a numerical example.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 2019 22th International Conference on Information Fusion (FUSION)

  • ISBN

    978-0-9964527-8-6

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    1-8

  • Publisher name

    IEEE

  • Place of publication

    Ottawa

  • Event location

    Ottawa, Kanada

  • Event date

    Jul 2, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000567728800272