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In modern automotive industry, the state-of-art technology of fuel injection controllers utilizes feed-forward control with a mass airflow sensor located upstream of the throttle, plus a proportional and integral (PI) type feedback control. The feed-forward control is simply implemented with look-up tables, which requires a laborious process of calibration and tuning. With the development of micro-controllers for engine control units (ECU), a variety of advanced control schemes has been introduced to automotive industry. This research work, firstly, investigated neural network based feed-forward control method to improve the performance of fuel injector. In addition, based on the air/fuel ratio model developed, a nonlinear model predictive control scheme is implemented successfully, and the control performance and robustness are evaluated by introducing system uncertainties.