Monday, December 05, 2016, 11:00 - 17:30

Room 101-02-016, Georges-Koehler-Allee 101, Freiburg 79110, Germany

The bilateral workshop is part of the DFG "Forschergruppe Optimierungsbasierte Multiskalenregelung motorischer Niedertemperatur-Brennverfahren”, and will
focus on the sub-project "Numerical methods for optimization based control of cyclic processes”. Aim of the workshop is to exchange ideas between researchers from both research teams that work on (or have interest in) embedded optimization algorithms for iterative learning nonlinear model predictive control (IL-NMPC), NMPC in the milli and microsecond range, and on periodic processes.

Preliminary program

11:00 Talk Thiva Albin
12:30 Lunch in Solar Info Center
14:00 Team member presentations Freiburg and Aachen (3-5 slides each)
15:00 Presentation of Numerical Research planned in DFG Project (Moritz)
15:30 Break
16:00 Brainstorming on Team Member Synergies
17:00 Wrap-Up
17:30 End

Abstract

"Potential and Challenges of IL-NMPC for innovative combustion engines"
by Thiva Albin

The ecological and economic energy supply poses a central challenge for society. An important goal for mobile propulsion consists in the reduction of engine combustion-related emissions of the greenhouse gas CO2 as well as pollutants. For realization of high efficiency with simultaneously low pollutant emissions, low temperature combustion is a promising future technology. Even though many advantages exist, the complexity of the process control is one of the main reasons, preventing technical realization. The relevant time scales of the process are smaller than the combustion cycle, which is the reason why the process cannot be effectively controlled by state-of-the-art cycle-based control concepts.

The presentation will give an overview on the DFG research unit 2401 (FOR2401) which investigates the control of low temperature combustion engines. To enable an improved process control in terms of stability, pollutant emissions and efficiency, the goal of the research group is to establish innovative multiscale control concepts based on embedded optimization. The arising challenge are the system dynamics, characterized by a strongly nonlinear, multiple-input multiple output behavior as well as the necessary small time scales in the range of milli- and microseconds. Tailor-made control concepts shall be developed which use the periodic behavior of the process. Specifically the idea of iterative learning control shall be combined with nonlinear model predictive control (IL-NMPC).