• DocumentCode
    3392660
  • Title

    Investigation of the use of neural networks for anti-skid brake system design

  • Author

    Cheng Chew Lim

  • fYear
    1995
  • fDate
    27-29 Aug 1995
  • Firstpage
    505
  • Lastpage
    510
  • Abstract
    A neural network based model reference adaptive control approach to anti-skid brake system (ABS) design is investigated in this paper. The principal benefit of using neural networks in an ABS is their ability to adapt to changes in the environmental conditions without significant degradation in performance. In the proposed approach, the controller neural network is designed to produce a braking torque which regulates the wheel slip for the vehicle-brake system to a prespecified level. Simulation studies are performed to demonstrate the effectiveness of the proposed neural network based anti-skid brake system
  • Keywords
    adaptive control; automobiles; braking; dynamics; model reference adaptive control systems; neurocontrollers; anti-skid brake system; automobiles; braking torque; dynamics; model reference adaptive control; neural networks; neurocontrol; wheel slip; Australia; Design engineering; Differential equations; Friction; Neural networks; Optimal control; Road vehicles; Tires; Vehicle dynamics; Wheels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control, 1995., Proceedings of the 1995 IEEE International Symposium on
  • Conference_Location
    Monterey, CA
  • ISSN
    2158-9860
  • Print_ISBN
    0-7803-2722-5
  • Type

    conf

  • DOI
    10.1109/ISIC.1995.525106
  • Filename
    525106