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In this paper, we extend the structure-preserving interpolatory model reduction framework, originally developed for linear systems, to structured bilinear control systems. Specifically, we give explicit construction formulae for the model…

Numerical Analysis · Mathematics 2021-05-17 Peter Benner , Serkan Gugercin , Steffen W. R. Werner

In this paper, we present an interpolation framework for structure-preserving model order reduction of parametric bilinear dynamical systems. We introduce a general setting, covering a broad variety of different structures for parametric…

Numerical Analysis · Mathematics 2021-07-13 Peter Benner , Serkan Gugercin , Steffen W. R. Werner

We develop a unifying framework for interpolatory $\mathcal{L}_2$-optimal reduced-order modeling for a wide classes of problems ranging from stationary models to parametric dynamical systems. We first show that the framework naturally…

Numerical Analysis · Mathematics 2023-09-26 Petar Mlinarić , Serkan Gugercin

In this paper, we focus on model reduction of large-scale bilinear systems. The main contributions are threefold. First, we introduce a new framework for interpolatory model reduction of bilinear systems. In contrast to the existing methods…

Numerical Analysis · Mathematics 2016-10-05 Garret Flagg , Serkan Gugercin

High-dimensional/high-fidelity nonlinear dynamical systems appear naturally when the goal is to accurately model real-world phenomena. Many physical properties are thereby encoded in the internal differential structure of these resulting…

Numerical Analysis · Mathematics 2024-03-14 Peter Benner , Serkan Gugercin , Steffen W. R. Werner

In this contribution, a new framework for H2-optimal reduction of multiple-input, multiple- output linear dynamical systems by tangential interpolation is presented. The framework is motivated by the local nature of both tangential…

Numerical Analysis · Mathematics 2017-09-22 Alessandro Castagnotto , Boris Lohmann

Port-Hamiltonian systems result from port-based network modeling of physical systems and are an important example of passive state-space systems. In this paper, we develop the framework for model reduction of large-scale…

Numerical Analysis · Mathematics 2015-03-17 Serkan Gugercin , Rostyslav V. Polyuga , Christopher Beattie , Arjan van der Schaft

This paper presents a model reduction method for the class of linear quantum stochastic systems often encountered in quantum optics and their related fields. The approach is proposed on the basis of an interpolatory projection ensuring that…

Quantum Physics · Physics 2015-09-21 O. Techakesari , H. I. Nurdin

We study the tangential interpolation problem for a passive transfer function in standard state-space form. We derive new interpolation conditions based on the computation of a deflating subspace associated with a selection of spectral…

Numerical Analysis · Mathematics 2023-08-08 Peter Benner , Pawan Goyal , Paul Van Dooren

Interpolatory necessary optimality conditions for $\mathcal{H}_2$-optimal reduced-order modeling of unstructured linear time-invariant (LTI) systems are well-known. Based on previous work on $\mathcal{L}_2$-optimal reduced-order modeling of…

Numerical Analysis · Mathematics 2024-09-23 Petar Mlinarić , Peter Benner , Serkan Gugercin

We examine interpolatory model reduction methods that are well-suited for treating large scale port-Hamiltonian differential-algebraic systems in a way that is able to preserve and indeed, take advantage of the underlying structural…

Numerical Analysis · Mathematics 2021-11-03 Chris A. Beattie , Serkan Gugercin , Volker Mehrmann

Interpolatory projection methods for model reduction of nonparametric linear dynamical systems have been successfully extended to nonparametric bilinear dynamical systems. However, this is not the case for parametric bilinear systems. In…

Numerical Analysis · Mathematics 2017-12-21 Andrea Carracedo Rodriguez , Serkan Gugercin , Jeff Borggaard

Optimal control of bilinear systems has been a well-studied subject in the area of mathematical control. However, techniques for solving emerging optimal control problems involving an ensemble of structurally identical bilinear systems are…

Optimization and Control · Mathematics 2016-01-14 Shuo Wang , Jr-Shin Li

In this paper, we discuss a novel model reduction framework for generalized linear systems. The transfer functions of these systems are assumed to have a special structure, e.g., coming from second-order linear systems and time-delay…

Numerical Analysis · Mathematics 2019-10-31 Peter Benner , Pawan Goyal , Igor Pontes Duff

In this work, we investigate a model order reduction scheme for polynomial parametric systems. We begin with defining the generalized multivariate transfer functions for the system. Based on this, we aim at constructing a reduced-order…

Numerical Analysis · Mathematics 2019-04-29 Peter Benner , Pawan Goyal

This paper introduces an interpolation framework for the weighted-H2 model reduction problem. We obtain a new representation of the weighted-H2 norm of SISO systems that provides new interpolatory first order necessary conditions for an…

Numerical Analysis · Mathematics 2013-09-03 Branimir Anic , Christopher A. Beattie , Serkan Gugercin , Athanasios C. Antoulas

We establish a separation principle for the output feedback stabilisation of state-affine systems that are observable at the stabilization target. Relying on control templates (recently introduced in [4]), that allow to approximate a…

Optimization and Control · Mathematics 2024-11-15 Ludovic Sacchelli , Lucas Brivadis , Ulysse Serres , Itaï Ben Yaacov

We consider model reduction of large-scale multi-input, multi-output (MIMO) systems using tangential interpolation in the frequency domain. Our scheme is related to the recently-developed Adaptive Antoulas--Anderson (AAA) algorithm, which…

Systems and Control · Electrical Eng. & Systems 2026-03-05 Jared Jonas , Bassam Bamieh

In this work, we will investigate the question of optimal control for bilinear systems with constrained endpoint. The optimal control will be characterized through a set of unconstrained minimization problems that approximate the former.…

Optimization and Control · Mathematics 2021-07-28 Soufiane Yahyaoui , Lahoussine Lafhim , Mohamed Ouzahra

Tensor interpolation is an essential step for tensor data analysis in various fields of application and scientific disciplines. In the present work, novel interpolation schemes for general, i.e., symmetric or non-symmetric, invertible…

Computational Engineering, Finance, and Science · Computer Science 2022-12-01 Abhiroop Satheesh , Christoph P. Schmidt , Wolfgang A. Wall , Christoph Meier
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