• DocumentCode
    1895108
  • Title

    Research on Suspension System Based on Genetic Algorithm and Neural Network Control

  • Author

    Tang, Chuan Yin ; Zhao, Guang Yao ; Li, Hua ; Zhou, Shu Wen

  • Author_Institution
    Sch. of Mech. Eng. & Autom., North Eastern Univ., Shenyang, China
  • Volume
    1
  • fYear
    2009
  • fDate
    10-11 Oct. 2009
  • Firstpage
    468
  • Lastpage
    471
  • Abstract
    An active suspension system for vehicles using the genetic algorithms and neural network controls strategy is presented. A half car four degree of freedom suspension vibration model is described. Compared with the conventional passive suspension system, the analysis is done to the system control performance. The analysis of the system response is obtained through the change of the neural network training coefficients, genetic algorithms input functions and the change of velocity. The simulation results indicate that the vehicle vibration can be reduced and the ride comfort is improved by the proposed suspension systems.
  • Keywords
    automobiles; genetic algorithms; learning (artificial intelligence); neurocontrollers; suspensions (mechanical components); vibration control; active suspension system; automobile; genetic algorithm; neural network control; neural network training coefficient; ride comfort; vehicle vibration model; Automatic control; Automation; Control systems; Damping; Genetic algorithms; Mechanical engineering; Neural networks; Road vehicles; Shock absorbers; Tires; active suspension; genetic algorithm; neural networks; simulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
  • Conference_Location
    Changsha, Hunan
  • Print_ISBN
    978-0-7695-3804-4
  • Type

    conf

  • DOI
    10.1109/ICICTA.2009.120
  • Filename
    5287610