2022/10/28 by Tim Moser, Moser, Tim, Boris Lohmann +1
Engineering · Mathematics · Physics and Astronomy · #Dynamical Systems (math.DS) #FOS: Electrical engineering #FOS: Mathematics #Fuel Cells and Related Materials #Model Reduction and Neural Networks #Numerical Analysis (math.NA) #Numerical methods for differential equations #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2210.16071
openalex publication_date 2022/10/28 · openalex created_date 2022/11/05 · openalex updated_date 2026/07/28
We present a new structure-preserving model order reduction (MOR) framework for large-scale port-Hamiltonian descriptor systems (pH-DAEs). Our method exploits the structural properties of the Rosenbrock system matrix for this system class and utilizes condensed forms which often arise in applications and reveal the solution behaviour of a system. Provided that the original system has such a form, our method produces reduced-order models (ROMs) of minimal dimension, which tangentially interpolate the original model's transfer function and are guaranteed to be again in pH-DAE form. This allows the ROM to be safely coupled with other dynamical systems when modelling large system networks, which is useful, for instance, in electric circuit simulation.