29 citations · 55 across the 4 of their papers we have counts for
5 papers
Nonlinear Model Order Reduction of Dynamical Systems in Process Engineering: Review and Comparison
Jan C. Schulze, Alexander Mitsos
Computationally cheap yet accurate dynamical models are a key requirement for real-time capable nonlinear optimization and model-based control. When given a computationally expensi…
A practical scenario generation method for electricity prices on day-ahead and intraday spot markets
Chrysanthi Papadimitriou, Jan C. Schulze, Alexander Mitsos
The increasing interest in demand-side management (DSM) as part of the energy cost optimization calls for effective methods to determine representative electricity prices for energ…
Data-driven Nonlinear Model Reduction using Koopman Theory: Integrated Control Form and NMPC Case Study
Jan C. Schulze, Alexander Mitsos
We use Koopman theory for data-driven model reduction of nonlinear dynamical systems with controls. We propose generic model structures combining delay-coordinate encoding of measu…
Data-Driven Model Reduction and Nonlinear Model Predictive Control of an Air Separation Unit by Applied Koopman Theory
Jan C. Schulze, Danimir T. Doncevic, Nils Erwes +1
Achieving real-time capability is an essential prerequisite for the industrial implementation of nonlinear model predictive control (NMPC). Data-driven model reduction offers a way…
Identification of MIMO Wiener-type Koopman Models for Data-Driven Model Reduction using Deep Learning
Jan C. Schulze, Danimir T. Doncevic, Alexander Mitsos
We use Koopman theory to develop a data-driven nonlinear model reduction and identification strategy for multiple-input multiple-output (MIMO) input-affine dynamical systems. While…