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Predictive Control of Radio Telescope Using Multi-layer Perceptron Neural Network

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86086877" target="_blank" >RIV/61989100:27240/13:86086877 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27740/13:86086877

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Predictive Control of Radio Telescope Using Multi-layer Perceptron Neural Network

  • Original language description

    Radio telescope (RT) installations are highly valuable assets and during the period of their service life they need regular repair and maintenance to be carried out for delivering satisfactory performance and minimizing downtime. With the growing automation technologies, predictive control can prove to be a better approach than the traditionally applied visual inspection policy and linear models. In this paper, Irbene Radio telescope RT-16 disk rotation control motors are analysed. Retrieved data from the small DC motor is used for the predictive control approach. A Multilayer Perceptron (MLP) network approach is used for prediction of the indicator voltage output which affects the monitoring of the disk rotating angle

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>

  • Continuities

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

Others

  • Publication year

    2013

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Advances in Intelligent Systems and Computing. Volume 239

  • ISSN

    2194-5357

  • e-ISSN

  • Volume of the periodical

    210

  • Issue of the periodical within the volume

    2013

  • Country of publishing house

    DE - GERMANY

  • Number of pages

    12

  • Pages from-to

    233-244

  • UT code for WoS article

  • EID of the result in the Scopus database