• DocumentCode
    2461663
  • Title

    Direct torque control of induction motor by Active Learning Method

  • Author

    Ghorbani, Mohammad Jawad ; Akhbari, Mahdi ; Mokhtari, Hossein

  • Author_Institution
    Sharif University of Technology Tehran, Iran
  • fYear
    2010
  • fDate
    17-18 Feb. 2010
  • Firstpage
    267
  • Lastpage
    272
  • Abstract
    This paper presents a high performance direct torque control (DTC) theme for the induction motor (IM). To solve those problems associated with conventional DTC, such as flux and torque ripple, variable switching frequency, inaccuracy in motor model and other parts of system. The Active Learning Method (ALM) is implemented on the DTC. In the Active Learning Method for information modeling, a method known as Ink Drop Spread (IDS) is used. The simulation results of DTC system based on ALM and the comparison of motor performance under the proposed control system with respect to those obtained under conventional DTC confirms its effectiveness and accuracy.
  • Keywords
    Humans; Induction motors; Ink; Intrusion detection; Learning systems; Paper technology; Power electronics; Power engineering and energy; Stators; Torque control; active learning method; direct torque control; fuzzy modeling; induction motor; reinforcement learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Electronic & Drive Systems & Technologies Conference (PEDSTC), 2010 1st
  • Conference_Location
    Tehran, Iran
  • Print_ISBN
    978-1-4244-5944-5
  • Type

    conf

  • DOI
    10.1109/PEDSTC.2010.5471817
  • Filename
    5471817