An Application of C/GMRES Model Predictive Control to a Diesel Engine Air Path System

This paper considers an application of a C/GMRES-based model predictive control (MPC) method to a diesel engine air path system. The plant model is derived based on the physical first principle to explicitly take account of plant nonlinearities. Since the plant has unmeasurable states, we employ an extended Kalman filter to estimate them. Then we design a C/GMRES-MPC algorithm and apply it to a real engine. We demonstrate the effectiveness of the present method by showing experimental results.