Applying model predictive control in automotive

Model predictive control (MPC), also called moving horizon control or receding horizon control, is one of the most successful and the most popular advanced control methods. The basis of MPC is the online solution of a constrained optimization problem updated by the actual state. The obtained control is injected into the system until the next sampling time, while the procedure is repeated whenever new measurements are available. Due to its ability to handle nonlinearity, to include various types of models predicting the future dynamics, to take time-domain constraints into account explicitly and to coordinate multiple performance requirements in the sense of optimization, MPC has become an attractive feedback strategy to design control systems in industrial applications over the last two decades.