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Design and Experimental Evaluation of Predictive Engine Air-ratio Control Based on Online Neural Network
FISITA2010/F2010C028

Authors

Wong, Hang Cheong* - University of Macau
Wong, Pak Kin - University of Macau

Abstract

Pollution reduction, fuel efficiency and driveability improvements relate mostly to air-ratio among all of the engine control variables. The best balance between power output and fuel consumption can be obtained by maintaining the air-ratio to be the stoichiometric value (1.0). This paper presents a nonlinear predictive control algorithm based on Online Neural Network (ONN) model. The control algorithm has been implemented on a real car for testing. The actual test results in experiments show that the proposed control algorithm can be regulate the engine air-ratio to the stoichiometric value (1.0) under external disturbance with less than 5% tolerance.

Keywords: Air-ratio, predictive control, online neural network, SIMULINK, National Instrument

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