Embedded Optimization for Nonlinear Model Predictive Control (IS Colloquium)
- Prof. Moritz Diehl
- University of Freiburg, Chair of Systems Theory, Control and Optimization
- More information
This talk shows how embedded optimization - i.e. autonomous optimization algorithms receiving data, solving problems, and sending answers continuously - are able to address challenging control problems. When nonlinear differential equation models are used to predict and optimize future system behaviour, one speaks of Nonlinear Model Predictive Control (NMPC).The talk presents experimental applications of NMPC to time and energy optimal control of mechatronic systems and discusses some of the algorithmic tricks that make NMPC optimization rates up to 1 MHz possible. Finally, we present on particular challenging application, tethered flight for airborne wind energy systems.
Biography: Moritz Diehl studied Mathematics and Physics in Heidelberg and Cambridge University and did his PhD in 2001 at Heidelberg University's Interdisciplinary Center for Scientific Computing (IWR). From 2006-2013 he has been a professor at the Electrical Engineering Department (ESAT- STADIUS) of KU Leuven University (Belgium) and served as the principal investigator of the Optimization in Engineering Center OPTEC. Since 2013 he holds the Chair of Systems Theory, Control and Optimizationat the Faculty of Engineering of the University of Freiburg, and keeps a joint appointment with KU Leuven. His research focuses on optimization and control, spanning from numerical methods and algorithm development to applications. One of his application areas is airborne wind energy, which he investigates within an ERC grant running from 2011 to 2016 in simulations and experiments.
