• DocumentCode
    1578668
  • Title

    Direct adaptive regulation using dynamic neural networks: application to DC motors

  • Author

    Rovithakis, George A. ; Christodoulou, Manolis A.

  • Author_Institution
    Dept. of Electron. & Comput. Eng., Tech. Univ. of Crete, Chania, Greece
  • Volume
    1
  • fYear
    34881
  • Firstpage
    369
  • Abstract
    A direct nonlinear adaptive state regulator is derived, based on dynamic neural networks and it is successfully applied to control the speed of a nonlinearized DC motor. One interesting feature of the proposed control algorithm is that it covers the situation where the magnetic flux continuously varies, as it is the case in the loss minimization problem
  • Keywords
    DC motors; adaptive control; digital control; losses; machine control; magnetic flux; neural nets; power engineering computing; velocity control; DC motors; continuously varying magnetic flux; direct adaptive regulation; dynamic neural networks; loss minimization; nonlinear adaptive state regulator; nonlinearized DC motor; speed control; Adaptive control; Application software; Backpropagation; Control systems; DC motors; Linear feedback control systems; Neural networks; Programmable control; Regulators; Sliding mode control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics, 1995. ISIE '95., Proceedings of the IEEE International Symposium on
  • Conference_Location
    Athens
  • Print_ISBN
    0-7803-7369-3
  • Type

    conf

  • DOI
    10.1109/ISIE.1995.497024
  • Filename
    497024
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1578668