• DocumentCode
    2250836
  • Title

    Vehicle stability control based on adaptive PID control with single neuron network

  • Author

    Jinzhu, Zhang ; Hongtian, Zhang

  • Author_Institution
    Coll. of Power & Energy Eng., Harbin Eng. Univ., Harbin, China
  • Volume
    1
  • fYear
    2010
  • fDate
    6-7 March 2010
  • Firstpage
    434
  • Lastpage
    437
  • Abstract
    According to the nonlinear and parameter time-varying characteristics of vehicle stability control, a novel algorithm of vehicle stability adaptive PID control with single neuron network was proposed. Based on self-learning and adaptive ability of single neural network, the parameters of vehicle stability PID controller were self-tuning on-line and the problem of large computation time brought by traditional adaptive PID control was avoided, in which the parameters of reference model of the controlled system must be identified with large calculation burden. The results of the simulation show this algorithm can effectively make vehicle keep and track the desired direction, and has good robustness and adaptability for vehicle lateral stability control system.
  • Keywords
    adaptive control; learning systems; neurocontrollers; nonlinear control systems; stability; three-term control; time-varying systems; vehicle dynamics; computation time; nonlinear time-varying characteristics; parameter time-varying characteristics; reference model; single neuron network; vehicle lateral stability control system; vehicle stability adaptive PID controller; vehicle stability control; Adaptive control; Computational modeling; Computer networks; Control system synthesis; Neural networks; Neurons; Programmable control; Robust stability; Three-term control; Vehicles; PID; nonlinear; single neuron network; vehicle stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
  • Conference_Location
    Wuhan
  • ISSN
    1948-3414
  • Print_ISBN
    978-1-4244-5192-0
  • Electronic_ISBN
    1948-3414
  • Type

    conf

  • DOI
    10.1109/CAR.2010.5456803
  • Filename
    5456803