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  • The paper deals with a replacement of adaptation algorithm in MRAS by the help of artificial neural network (ANN) with radial basis function. The main objective was to find and design some alternative neural network within the electric drive control. Digital signal processors TMS320F2812 are used for these electric drives control applications. The estimation of the rotor time constant for the adaptive model of MRAS is created with the support of a PI-controller which is then replaced with the Radial Basis Function network. The paper presents simulations results, which have been performed in the Matlab-Simulink software.
  • The paper deals with a replacement of adaptation algorithm in MRAS by the help of artificial neural network (ANN) with radial basis function. The main objective was to find and design some alternative neural network within the electric drive control. Digital signal processors TMS320F2812 are used for these electric drives control applications. The estimation of the rotor time constant for the adaptive model of MRAS is created with the support of a PI-controller which is then replaced with the Radial Basis Function network. The paper presents simulations results, which have been performed in the Matlab-Simulink software. (en)
  • Příspěvek se zabývá náhradou adaptačního algoritmu v MRAS pomocí umělé neuronové sítě s radiální bází. Hlavním cílem byl návrh neuronové sítě rp řízení elektrického pohonu. Pro řízení elektrického pohonu byl použit signálový procesor TMS320F2812. Estimace rotorové časové konstanty je provedena pomocí PI-regulátoru, který je pak nahrazen neuronovou sítí s radiální bází. V příspěvku jsou prezentovány simulační výsledky, které byly získány pomocí softwarového produktu Matlab-Simulink. (cs)
Title
  • Rotor Time Constant Adaptation Using Radial Basis Function Network
  • Rotor Time Constant Adaptation Using Radial Basis Function Network (en)
  • Adaptace rotorové časové konstanty s využitím neuronové sítě s radiální bází (cs)
skos:prefLabel
  • Rotor Time Constant Adaptation Using Radial Basis Function Network
  • Rotor Time Constant Adaptation Using Radial Basis Function Network (en)
  • Adaptace rotorové časové konstanty s využitím neuronové sítě s radiální bází (cs)
skos:notation
  • RIV/61989100:27240/08:00018780!RIV09-GA0-27240___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA102/08/0775)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 393334
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27240/08:00018780
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Digital Signal Processor; Induction Motor; Electric Drive; Vector Control; Neural Network; Radial Basis Function. (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [D0315BF90876]
http://linked.open...v/mistoKonaniAkce
  • Poznan, Poland
http://linked.open...i/riv/mistoVydani
  • Poznan, Poland
http://linked.open...i/riv/nazevZdroje
  • 13th International Power Electronics and Motion Control Conference
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Brandštetter, Pavel
  • Škuta, Ondřej
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Poznan, Poland
https://schema.org/isbn
  • 978-1-4244-1741-4
http://localhost/t...ganizacniJednotka
  • 27240
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