تقرير
Structure-Preserving Model Order Reduction for Index Two Port-Hamiltonian Descriptor Systems
| العنوان: | Structure-Preserving Model Order Reduction for Index Two Port-Hamiltonian Descriptor Systems |
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| المؤلفون: | Moser, Tim, Schwerdtner, Paul, Mehrmann, Volker, Voigt, Matthias |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science Mathematics |
| مصطلحات موضوعية: | Electrical Engineering and Systems Science - Systems and Control, Mathematics - Dynamical Systems, Mathematics - Numerical Analysis |
| الوصف: | We present a new optimization-based structure-preserving model order reduction (MOR) method for port-Hamiltonian descriptor systems (pH-DAEs) with differentiation index two. Our method is based on a novel parameterization that allows us to represent any linear time-invariant pH-DAE with a minimal number of parameters, which makes it well-suited to model reduction. We propose two algorithms which directly optimize the parameters of a reduced model to approximate a given large-scale model with respect to either the H-infinity or the H-2 norm. This approach has several benefits. Our parameterization ensures that the reduced model is again a pH-DAE system and enables a compact representation of the algebraic part of the large-scale model, which in projection-based methods often requires a more involved treatment. The direct optimization is entirely based on transfer function evaluations of the large-scale model and is therefore independent of the system matrices' structure. Numerical experiments are conducted to illustrate the high accuracy and small reduced model orders in comparison to other structure-preserving MOR methods. Comment: 12 pages, 4 figures |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2206.03942 |
| رقم الأكسشن: | edsarx.2206.03942 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |