• DocumentCode
    550057
  • Title

    Single neuron ADRC control based on RBF neural network on-line identification

  • Author

    Su Si-Xian ; Yang Hui-zhong

  • Author_Institution
    Key Lab. of Adv. Process Control for Light Ind., Jiangnan Univ., Wuxi, China
  • fYear
    2011
  • fDate
    22-24 July 2011
  • Firstpage
    3669
  • Lastpage
    3672
  • Abstract
    Arming at the problem of over many parameters to be turned in the active disturbance rejection controller (ADRC), a self-adaptive single neuron Active Disturbance Rejection Control (ADRC) is proposed based on RBF neural network on-line identification, which identifies the Jacobian matrix of controlled object by means of RBF neural network identifier and acquires on-line tuning information of ADRC parameters. The self-tuning of the controller parameters is implemented by the single neuron controller, and the intelligent control of the system is achieved. The simulation result indicates that the proposed control system greatly reduces the adjusted parameter and possesses the advantages of high precision, great adaptability and robustness.
  • Keywords
    Jacobian matrices; adaptive control; intelligent control; neurocontrollers; radial basis function networks; Jacobian matrix; RBF neural network online identification; active disturbance rejection controller; intelligent control; single neuron ADRC control; Biological neural networks; Electronic mail; Jacobian matrices; Neurons; Object recognition; Robustness; Sensitivity analysis; Active Disturbance Rejection Control (ADRC); Nonlinear state error feedback; RBF neural network; Single neuron;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2011 30th Chinese
  • Conference_Location
    Yantai
  • ISSN
    1934-1768
  • Print_ISBN
    978-1-4577-0677-6
  • Electronic_ISBN
    1934-1768
  • Type

    conf

  • Filename
    6000394