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
Link To Document