• DocumentCode
    1907143
  • Title

    Simulation of Semi-Active Air Suspension Based on Neural Network-Adaptive Control Algorithm

  • Author

    Li, Hua ; Tang, Chuanyin ; Yang, Dexu ; Tao, Xuezong

  • Author_Institution
    Eng. Coll., Shenyang Agric. Univ., Shenyang, China
  • Volume
    2
  • fYear
    2009
  • fDate
    10-11 Oct. 2009
  • Firstpage
    236
  • Lastpage
    239
  • Abstract
    Neural Network-adaptive Control Algorithm is pointed out according to the non-linear characteristic for the semi-active suspension of automobiles and at the same time the recognition device and controller have been designed.The results of the simulation research on the 1/4 variable rigidity air suspension show that neural network self- adaptive controlled semi-active air suspension has an apparent advantages to passive suspension in reducing vibration,correcting the stability and smooth of the automobiles.Thereby, the feasibility and validity which applied into semi-active air suspension is testified.The research also has an instructional function for the further research on the semi-active air suspension.
  • Keywords
    adaptive control; automotive components; control system synthesis; neurocontrollers; nonlinear control systems; stability; suspensions (mechanical components); vibration control; automobiles; controller design; neural network-adaptive control algorithm; recognition device design; self-adaptive controller; semiactive air suspension; stability correction; vibration reduction; Adaptive control; Adaptive systems; Algorithm design and analysis; Automatic testing; Automobiles; Character recognition; Neural networks; Programmable control; Stability; Vibration control; adaptive control; air suspension; neural network; semi-active suspension; 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.2009.294
  • Filename
    5288102