• DocumentCode
    490402
  • Title

    CMAC Neural Network for Fuel-Injection Control

  • Author

    Shiraishi, Hitoshi ; Ipri, Susan L. ; Cho, Dan

  • Author_Institution
    Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, New Jersey 08544
  • fYear
    1993
  • fDate
    2-4 June 1993
  • Firstpage
    1773
  • Lastpage
    1778
  • Abstract
    A new automotive fuel-injection controller using the cerebellar model articulation controller (CMAC) neural network is developed and implemented to maintain the engine air-to-fuel ratio at its stoichiometric value. In contrast to conventional fuel-injection controllers, which rely heavily on laborious calibration and tuning processes the CMAC controller requires minimal knowledge of the dynamic system and possesses the ability so achieve a desired performance through rapid on-line learning. This real-time CMAC controller is experimentally evaluated on a research vehicle in a configuration fully compatible with production controllers. The results show the highly promising potential of the new controller.
  • Keywords
    Aerodynamics; Aerospace engineering; Automotive engineering; Calibration; Control systems; Engines; Manifolds; Neural networks; Vehicle dynamics; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 1993
  • Conference_Location
    San Francisco, CA, USA
  • Print_ISBN
    0-7803-0860-3
  • Type

    conf

  • Filename
    4793182