Model predictive control of a fuel injection system with a radial basis function network observer

This paper proposes using a model predictive control (MPC) incorporating a radial basis function (RBF) network observer for the fuel injection problem. Two new contributions are presented. First, an RBF Network is used as an observer for the volumetric efficiency of the air system. This allows for gradual adaptation of the observer, ensuring the control scheme is capable of maintaining good performance under changing engine conditions brought about by engine wear, variations between individual engines and other similar factors. The other is the rise of model predictive control algorithms to compensate for the fuel pooling effect on the intake manifold walls. Two MPC algorithms are presented which enforce input, and input and state constraints. A comparison between the two constrained MPC algorithms is qualitatively presented, and some conclusions drawn about the necessity of constraints for the fuel injection problem. Simulation and actual engine results are presented that demonstrate the effectiveness of the control scheme.