Title :
CMAC neural network controller for fuel-injection systems
Author :
Shiraishi, Hitoshi ; Ipri, Susan L. ; Cho, Dong-il D.
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Princeton Univ., NJ, USA
fDate :
3/1/1995 12:00:00 AM
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. The CMAC controller requires minimal a priori knowledge of the engine dynamics because it can learn the dynamics and adapt to changing conditions in real time. The CMAC controller is experimentally evaluated on a research vehicle in a configuration fully compatible with production hardware. Initial training followed by continual adaptation allows the CMAC controller to maintain desired performance under previously inexperienced driving conditions
Keywords :
cerebellar model arithmetic computers; internal combustion engines; neurocontrollers; road vehicles; transport control; CMAC neural network controller; automotive fuel-injection controller; engine air-to-fuel ratio; research vehicle; stoichiometric value; Aerospace engineering; Automotive engineering; Combustion; Control system synthesis; Control systems; Degradation; Engines; Fuels; Neural networks; Vehicle dynamics;
Journal_Title :
Control Systems Technology, IEEE Transactions on