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In this paper, a practicable simulation-free model order reduction method by nonlinear moment matching is developed. Based on the steady-state interpretation of linear moment matching, we comprehensively explain the extension of this…

Systems and Control · Electrical Eng. & Systems 2024-12-20 Maria Cruz Varona , Raphael Gebhart , Julian Suk , Boris Lohmann

In this paper we discuss a projection model order reduction (MOR) method for a class of parametric linear evolution PDEs, which is based on the application of the Laplace transform. The main advantage of this approach consists in the fact…

Numerical Analysis · Mathematics 2022-09-02 Nicola Guglielmi , Mattia Manucci

Systems of differential-algebraic equations (DAEs) represent a widespread formalism in the modeling of constrained mechanical systems and electrical networks. Due to the automatic, object-oriented generation of the equations of motion and…

Numerical Analysis · Mathematics 2015-08-31 Alessandro Castagnotto , Heiko K. F. Panzer , Klaus-Dieter Reinsch , Boris Lohmann

In this paper, we address the model reduction problem for linear hybrid systems via the interconnection-based technique called moment matching. We consider two classical interconnections, namely the direct and swapped interconnections, in…

Systems and Control · Electrical Eng. & Systems 2026-01-23 Zirui Niu , Giordano Scarciotti , Alessandro Astolfi

The increasing size and complexity of modern power systems have led to a high-dimensional mathematical model for transient stability studies, rendering full-scale simulations computationally burdensome. While dimensionality reduction is…

Dynamical Systems · Mathematics 2025-12-08 Farhana Farooq , Danish Rafiq

Here, we focus on Model Order Reduction (MOR) of non-parametric second-order dynamical systems. In these MOR algorithms, sequences of large and sparse linear systems arise during the model reduction process. Solving such linear systems is…

Numerical Analysis · Mathematics 2025-11-06 Kapil Ahuja , Navneet Pratap Singh

We propose a projection based multi-moment matching method for model order reduction of quadratic-bilinear systems. The goal is to construct a reduced system that ensures higher-order moment matching for the multivariate transfer functions…

Systems and Control · Electrical Eng. & Systems 2023-03-01 Mian Muhammad Arsalan Asif , Mian Ilyas Ahmad , Peter Benner , Lihong Feng , Tatjana Stykel

We provide an introduction to POD-MOR with focus on (nonlinear) parametric PDEs and (nonlinear) time-dependent PDEs, and PDE constrained optimization with POD surrogate models as application. We cover the relation of POD and SVD, POD from…

Numerical Analysis · Mathematics 2020-08-04 Carmen Gräßle , Michael Hinze , Stefan Volkwein

In post--layout circuit simulation, efficient model order reduction (MOR) for many--port resistor--capacitor (RC) circuits remains a crucial issue. The current mainstream MOR methods for such circuits include high--order moment matching…

Systems and Control · Electrical Eng. & Systems 2025-10-21 Siyuan Yin , Yuncheng Xu , Lin Liu , Fan Yang , Xuan Zeng , Chengtao An , Yangfeng Su

In this paper, the moment matching techniques are adopted to obtain reduced-order closed-loop systems with reduced-order controllers that maintain the closed-loop stability and guarantee desired asymptotic performance, after revealing the…

Optimization and Control · Mathematics 2024-05-06 Tudor C. Ionescu

We investigate model order reduction (MOR) for linear dynamical systems, where a quadratic output is defined as a quantity of interest. The system can be transformed into a linear dynamical system with many linear outputs. MOR is feasible…

Numerical Analysis · Mathematics 2019-08-15 Roland Pulch , Akil Narayan

This work aims at tackling the problem of learning surrogate models from noisy time-domain data by means of matrix pencil-based techniques, namely the Hankel and Loewner frameworks. A data-driven approach to obtain reduced-order state-space…

Systems and Control · Electrical Eng. & Systems 2022-09-13 Pauline Kergus , Ion Victor Gosea

Model order reduction (MOR) techniques are often used to reduce the order of spatially-discretized (stochastic) partial differential equations and hence reduce computational complexity. A particular class of MOR techniques is balancing…

Optimization and Control · Mathematics 2019-03-29 Martin Redmann

Density-based topology optimization has become a powerful method for automatically generating optimized designs in a wide variety of applications. However, it comes with a large computational cost when solving the physical model requires…

Numerical Analysis · Mathematics 2026-04-22 Luis Fernando Cusicanqui Lopez , Ramadan Krasniqi , Florian Feppon , Karl Meerbergen

We propose a new model-order reduction framework to poorly reducible problems arising from parametric partial differential equations with geometric variability. In such problems, the solution manifold exhibits a slowly decaying Kolmogorov…

Numerical Analysis · Mathematics 2025-10-30 Abbas Kabalan , Fabien Casenave , Felipe Bordeu , Virginie Ehrlacher , Alexandre Ern

We present a novel model-order reduction (MOR) method for linear time-invariant systems that preserves passivity and is thus suited for structure-preserving MOR for port-Hamiltonian (pH) systems. Our algorithm exploits the well-known…

Dynamical Systems · Mathematics 2021-08-30 Tobias Breiten , Benjamin Unger

In this paper, we investigate the use of multilinear algebra for reducing the order of multidimensional linear time-invariant (MLTI) systems. Our main tools are tensor rational Krylov subspace methods, which enable us to approximate the…

Numerical Analysis · Mathematics 2024-11-28 Houda Barkouki , Khalide Jbilou

This paper transfers the concept of moment matching to nonlinear structural systems and further provides a simulation-free reduction scheme for such nonlinear second-order models. After first presenting the steady-state interpretation of…

Computational Engineering, Finance, and Science · Computer Science 2019-04-01 Maria Cruz Varona , Nico Schneucker , Boris Lohmann

We develop optimization-based structure-preserving model order reduction (MOR) methods for port-Hamiltonian (pH) descriptor systems of differentiation index one. Descriptor systems in pH form permit energy-based modeling and intuitive…

Optimization and Control · Mathematics 2022-06-06 Paul Schwerdtner , Tim Moser , Volker Mehrmann , Matthias Voigt

This work proposes a novel structure-preserving model order reduction (MOR) method for linear, time-invariant port-Hamiltonian (pH) systems. Our goal is to construct a reduced order pH system, which can still be interpreted in the physical…

Optimization and Control · Mathematics 2025-10-16 Silke Glas , Mir Mamunuzzaman , Hongliang Mu , Hans Zwart