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Decentralized and Distributed Active Fault Diagnosis: Multiple Model Estimation Algorithms

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43958925" target="_blank" >RIV/49777513:23520/20:43958925 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.34768/amcs-2020-0019" target="_blank" >http://dx.doi.org/10.34768/amcs-2020-0019</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.34768/amcs-2020-0019" target="_blank" >10.34768/amcs-2020-0019</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Decentralized and Distributed Active Fault Diagnosis: Multiple Model Estimation Algorithms

  • Original language description

    The paper focuses on the active fault diagnosis (AFD) of large scale systems. The multiple model framework is considered and two architectures are treated: the decentralized and the distributed one. An essential part of the AFD algorithm is the state estimation, which must be supplemented with a mechanism to achieve feasible implementation in the multiple model framework. In the paper, the generalized pseudo Bayes and the interacting multiple model estimation algorithms are considered. They are reformulated for the considered model of the large scale system. Performance of both AFD architectures is analyzed for different combinations of the multiple model estimation algorithms using a numerical example.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • 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

    2020

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    International Journal of Applied Mathematics and Computer Science

  • ISSN

    1641-876X

  • e-ISSN

  • Volume of the periodical

    30

  • Issue of the periodical within the volume

    2

  • Country of publishing house

    PL - POLAND

  • Number of pages

    11

  • Pages from-to

    239-249

  • UT code for WoS article

    000547371600004

  • EID of the result in the Scopus database

    2-s2.0-85090274889