EE Seminar: On conditions under which receding horizon control delivers approximately optimal solutions
(The talk will be given in English)
Speaker: Prof. Lars Gruene
Dept. of Applied Mathematics, University of Bayreuth, Germany
Monday, October 31st, 2016
15:00 - 16:00
Room 011, Kitot Bldg., Faculty of Engineering
On conditions under which receding horizon control delivers approximately optimal solutions
Abstract
Receding horizon control — also known as model predictive control — is a method which solves optimal control problems on infinite or indefinitely long time horizons by iteratively solving problems on relatively short finite time horizons. It can thus be seen as a model reduction technique in time. Clearly, this technique does not apply to every optimal control problem. In this talk we will discuss conditions under which receding horizon control can be shown to yield approximately optimal solutions. A particular emphasis is put on the so-called turnpike property, which we consider as one of the central properties for making receding horizon control work.
Bio: Lars Grüne has been Professor for Applied Mathematics at the University of Bayreuth, Germany, since 2002. He received his Diploma and Ph.D. in Mathematics in 1994 and 1996, respectively, from the University of Augsburg and his habilitation from the J.W. Goethe University in Frankfurt/M in 2001. He held visiting positions at the Universities of Rome ‘Sapienza’ (Italy), Padova (Italy), Melbourne (Australia), Paris IX — Dauphine (France) and Newcastle (Australia). Prof. Grüne is Editor-in-Chief of the journal Mathematics of Control, Signals and Systems (MCSS) and Associate Editor of the Journal of Optimization Theory and Applications (JOTA) and of the Journal of Applied Mathematics and Mechanics (ZAMM). His research interests lie in the area of mathematical systems and control theory with a focus on numerical and optimization-based methods for nonlinear systems.
