Air/fuel ratio control in SI1 engines using a combined neural network and estimator

In this paper by using a controller based on a neural network and an estimator, an efficient method in A/F ratio for SI engines is presented. This combined method improves plant performance effectively and provides robustness against disturbances due to work point changing. It is shown that by combining two separate methods, a useful control strategy may be generated. Simulation results reveal the superiority of this method.