• DocumentCode
    2657418
  • Title

    DSP-based real-time implementation of a neural network observer and hybrid H Adaptive Controller for servo-motor drives

  • Author

    Yongjun, Chen ; Shenghua, Huang ; Shanming, Wan ; Fang, Wu

  • Author_Institution
    Coll. of Electron. & Inf., Yangtze Univ., Jingzhou
  • fYear
    2008
  • fDate
    16-18 July 2008
  • Firstpage
    130
  • Lastpage
    134
  • Abstract
    This paper presents a method for sensorless speed control of a non-salient permanent magnetic synchronous motor (PMSM). Special attention is put on the neural-based strategies and applied to the sensorless PMSM. An embedded hybrid Hinfin adaptive controller is implemented for trajectory tracking control of a PMSM servo drive system. The proposed control structure employs neural observer (DRNN) and Hinfin tracking controller algorithm to run on the hardware processor of the DSP. The result is a powerful tested for the rapid design and implementation of the controller for a low speed operation conditions. Experimental results are provided to verify the effectiveness of the proposed observer and controller.
  • Keywords
    Hinfin control; adaptive control; digital signal processing chips; machine control; neurocontrollers; observers; permanent magnet motors; position control; servomotors; synchronous motor drives; tracking; velocity control; DSP; embedded hybrid Hinfin adaptive controller; hardware processor; neural network observer; nonsalient permanent magnetic synchronous motor; sensorless speed control; servo drive system; servo-motor drives; trajectory tracking control; Adaptive control; Control systems; Hardware; Neural networks; Programmable control; Sensorless control; Servomechanisms; Synchronous motors; Trajectory; Velocity control; DSP; H adaptive controller; Neural network estimation; PMSM motion control; Sensorless;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference, 2008. CCC 2008. 27th Chinese
  • Conference_Location
    Kunming
  • Print_ISBN
    978-7-900719-70-6
  • Electronic_ISBN
    978-7-900719-70-6
  • Type

    conf

  • DOI
    10.1109/CHICC.2008.4605000
  • Filename
    4605000