EU Regional School - Grüne Seminar
Prof. Dr. Grüne - Nonlinear Model Predictive Control
Nonlinear Model Predictive Control (NMPC) is a control method in which a closed loop or feedback control is synthesized from the iterative solution of open loop optimal control problems. As such, the method is applicable to all classes of systems for which optimal control problems can be efficiently solved numerically, including most ODE and DAE models but also many control systems governed by PDEs. Traditionally, the optimal control problem in the NMPC formulation is of tracking type, i.e., it penalizes the distance of the solution to a desired reference. In this context, the important question we will answer in the first part of this short course is whether the closed loop solution generated by NMPC converges to the desired reference, or, more specifically, whether it is asymptotically stable. In the second part of the course we will investigate performance issues. Here we will also consider NMPC problems which are not of tracking type and which have recently attracted a lot of interest in the literature under the name economic NMPC.