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  • Asynchronous electric motor control task can be successfully solved using reinforcement learning based method called Q-learning. The main problem to solve is the convergence speed. Two-phase Q-learning can be used to speed up the learning process. Efficient prelearning phase uses mathematical model and next phase using for tutorage real system. This method can increase learning speed significantly. When the table is used as Q-function approximation, the learning speed and precision of found controllers depend highly on the Q-function table grid properties. The paper is focused on finding the optimal division of grid.
  • Asynchronous electric motor control task can be successfully solved using reinforcement learning based method called Q-learning. The main problem to solve is the convergence speed. Two-phase Q-learning can be used to speed up the learning process. Efficient prelearning phase uses mathematical model and next phase using for tutorage real system. This method can increase learning speed significantly. When the table is used as Q-function approximation, the learning speed and precision of found controllers depend highly on the Q-function table grid properties. The paper is focused on finding the optimal division of grid. (en)
  • Asynchronous electric motor control task can be successfully solved using reinforcement learning based method called Q-learning. The main problem to solve is the convergence speed. Two-phase Q-learning can be used to speed up the learning process. Efficient prelearning phase uses mathematical model and next phase using for tutorage real system. This method can increase learning speed significantly. When the table is used as Q-function approximation, the learning speed and precision of found controllers depend highly on the Q-function table grid properties. The paper is focused on finding the optimal division of grid. (cs)
Title
  • Stanovení optimálního rastru Q-funkce pro řízení asynchronního elektromotoru
  • Stanovení optimálního rastru Q-funkce pro řízení asynchronního elektromotoru (cs)
  • Determination of Q-function Optimum Grid for Control Task of Asynchronous Electric Motor (en)
skos:prefLabel
  • Stanovení optimálního rastru Q-funkce pro řízení asynchronního elektromotoru
  • Stanovení optimálního rastru Q-funkce pro řízení asynchronního elektromotoru (cs)
  • Determination of Q-function Optimum Grid for Control Task of Asynchronous Electric Motor (en)
skos:notation
  • RIV/00216305:26210/04:PU45570!RIV11-MSM-26210___
http://linked.open...avai/riv/aktivita
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  • V
http://linked.open...vai/riv/dodaniDat
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  • 587838
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26210/04:PU45570
http://linked.open...riv/jazykVysledku
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  • Asynchronous electromotor, Q-learning, Control, PID (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [621BE0D5D70E]
http://linked.open...v/mistoKonaniAkce
  • Bratislava
http://linked.open...i/riv/mistoVydani
  • Bratislav, SK
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 7th International Symposium %22Topical Questions of Teaching Mechatronics%22
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http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Březina, Tomáš
  • Singule, Vladislav
  • Marada, Tomáš
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Slovenská technická univerzita v Bratislave. Strojnícka fakulta CA Mechatronika
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  • 80-227-2064-X
http://localhost/t...ganizacniJednotka
  • 26210
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