• DocumentCode
    2108860
  • Title

    Chaos Optimizing BP-NNG Speed Recognition in DTC System

  • Author

    Cao, Chengzhi ; Li, Fengkun ; Zhang, Kun ; Zhang, Hongbing ; San, Hongli

  • Author_Institution
    Coll. of Inf. Sci. & Eng., Shenyang Univ. of Techonolgy, Shenyang
  • fYear
    2008
  • fDate
    21-22 Dec. 2008
  • Firstpage
    1077
  • Lastpage
    1080
  • Abstract
    According to the non-linear relationship of direct torque control (DTC) system, multiorbit chaos optimizing algorithm is put forward, which resolve the slower converging problem of single-orbit and single-non-linearity-function chaos algorithm. In addition, the conception of neural network group (NNG) is proposed to resolve the bigger periodical errors problem. As the sub-network of NNG is intended to deal with different data group, the accuracy has been improved greatly. The result of DTC system simulation in MATLAB/SIMULINK shows that NNG speed recognition optimized by the multiorbit chaos optimizing algorithm has better tracking capability and fitness, as well as favorable static and dynamic properties.
  • Keywords
    backpropagation; chaos; control nonlinearities; neurocontrollers; torque control; velocity control; DTC system; MATLAB/SIMULINK; chaos optimizing BP-NNG speed recognition; linear direct torque control; multiorbit chaos optimizing algorithm; neural network group; periodical errors problem; single-nonlinearity-function chaos algorithm; single-orbit chaos algorithm; Ant colony optimization; Chaos; Design optimization; Educational institutions; Information science; Information technology; MATLAB; Neural networks; Nonlinear dynamical systems; Torque control; DTC; Neural Network Group (NNG); chaos; multiorbit;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3505-0
  • Type

    conf

  • DOI
    10.1109/IITA.Workshops.2008.54
  • Filename
    4732124