• DocumentCode
    1989223
  • Title

    Remarks on Servo Controller Using Quantum Neural Network with Qubit Neurons

  • Author

    Takahashi, Kazuhiko

  • Author_Institution
    Dept. of Inf. Syst. Design, Doshisha Univ., Kyotanabe, Japan
  • fYear
    2012
  • fDate
    27-30 May 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper presents the servo controller design of using a quantum neural network and investigates its characteristics for control systems. A multi-layer quantum neural network that uses qubit neurons as an information processing unit is used to design three types of neural network-based servo controller: the direct controller, the parallel controller and the self-tuning controller. Computational experiments to control the nonlinear discrete-time plant are conducted in order to evaluate the learning performance and the capability of the quantum neural controller. The results of the computational experiments confirm both the feasibility and effectiveness of the quantum neural controllers.
  • Keywords
    control system synthesis; discrete time systems; learning systems; neurocontrollers; nonlinear control systems; quantum computing; self-adjusting systems; servomechanisms; control systems; direct controller; information processing unit; learning performance evaluation; multilayer quantum neural network; neural network-based servo controller design; nonlinear discrete-time plant control; parallel controller; quantum neural controller; qubit neurons; self-tuning controller; Biological neural networks; Logic gates; Neurons; Quantum computing; Servomotors; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering and Technology (S-CET), 2012 Spring Congress on
  • Conference_Location
    Xian
  • Print_ISBN
    978-1-4577-1965-3
  • Type

    conf

  • DOI
    10.1109/SCET.2012.6341959
  • Filename
    6341959