Optimal adaptive predictive control of a combustion engine

This paper deals with the optimal tracking control of a spark ignited combustion engine. The overall controller consists of an (a priori given) feed-forward part that steers the system close to the desired trajectory and an optimal adaptive predictive controller for the tracking error dynamics. The latter is based on estimating a linear model along the desired trajectory online, which is then used in a model predictive control (MPC) scheme that systematically incorporates the input and state constraints in the design process. The provided feed-forward control and its respective combination with an infinite linear-quadratic regulator (LQR) and the adaptive MPC are compared in simulation. The results demonstrate a decrease in fuel consumption at the price of a minor performance loss in terms of tracking the desired torque cycle, while avoiding disadvantageous operation of the engine at all times.