Modeling Alternatives for Automotive Predictive Control

Recent years have witnessed an increased interest in model predictive control (MPC) for fast applications. MPC seems a suitable method to exploit the potentials of modern concepts and to fulfill the increasingly demanding automotive requirements since most of them can be stated in the form of a constrained optimal control problem and MPC provides an approximate solution to this class of problems. MPC performance, however, depends very strongly on the underlying model, which, accordingly, should be quite precise. However, model complexity strongly affect the complexity of the optimization problem to be solved and in particular its convexity. As automotive applications tend to be nonlinear, there is a need for modeling approaches which allow a sufficient precision while retaining a structural simplicity necessary to allow their on-line use.