Over the past 15 years Economic Model Predictive Control (eMPC) has developed into a powerful approach to determine optimal operating regimes and optimal control strategies for dynamical systems simultaneously by using on-line optimization. For that, "classical" eMPC heavily relies on the availability of a suitable mathematical model of the system to be controlled. In this presentation we will give an introduction to data-driven economic MPC where the mathematical model is replaced by knowledge of persistently exciting input-output trajectories only. We will show how to properly formulate the online optimization problem so that the asymptotic average performance of the closed-loop system can be made arbitrarily close to that of the unknown optimal equilibrium.

Frank Allgöwer is professor in mechanical engineering and director of the Institute for Systems Theory and Automatic Control at the University of Stuttgart in Germany. His current research interests are to develop new methods for data-based control, optimization-based control and networked control. Frank has served the community in a number of roles, received several recognitions for his work, and has published over 500 scientific articles.

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