Interpolatory Methods For Model Reduction
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Interpolatory Methods For Model Reduction
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Author : A. C. Antoulas
language : en
Publisher: SIAM
Release Date : 2020-01-13
Interpolatory Methods For Model Reduction written by A. C. Antoulas and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-13 with Mathematics categories.
Dynamical systems are a principal tool in the modeling, prediction, and control of a wide range of complex phenomena. As the need for improved accuracy leads to larger and more complex dynamical systems, direct simulation often becomes the only available strategy for accurate prediction or control, inevitably creating a considerable burden on computational resources. This is the main context where one considers model reduction, seeking to replace large systems of coupled differential and algebraic equations that constitute high fidelity system models with substantially fewer equations that are crafted to control the loss of fidelity that order reduction may induce in the system response. Interpolatory methods are among the most widely used model reduction techniques, and Interpolatory Methods for Model Reduction is the first comprehensive analysis of this approach available in a single, extensive resource. It introduces state-of-the-art methods reflecting significant developments over the past two decades, covering both classical projection frameworks for model reduction and data-driven, nonintrusive frameworks. This textbook is appropriate for a wide audience of engineers and other scientists working in the general areas of large-scale dynamical systems and data-driven modeling of dynamics.
Interpolatory Methods For Model Reduction Of Large Scale Dynamical Systems
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Author : Tobias Breiten
language : en
Publisher:
Release Date : 2013
Interpolatory Methods For Model Reduction Of Large Scale Dynamical Systems written by Tobias Breiten and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
Model Reduction And Approximation
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Author : Peter Benner
language : en
Publisher: SIAM
Release Date : 2017-07-06
Model Reduction And Approximation written by Peter Benner and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-06 with Science categories.
Many physical, chemical, biomedical, and technical processes can be described by partial differential equations or dynamical systems. In spite of increasing computational capacities, many problems are of such high complexity that they are solvable only with severe simplifications, and the design of efficient numerical schemes remains a central research challenge. This book presents a tutorial introduction to recent developments in mathematical methods for model reduction and approximation of complex systems. Model Reduction and Approximation: Theory and Algorithms contains three parts that cover (I) sampling-based methods, such as the reduced basis method and proper orthogonal decomposition, (II) approximation of high-dimensional problems by low-rank tensor techniques, and (III) system-theoretic methods, such as balanced truncation, interpolatory methods, and the Loewner framework. It is tutorial in nature, giving an accessible introduction to state-of-the-art model reduction and approximation methods. It also covers a wide range of methods drawn from typically distinct communities (sampling based, tensor based, system-theoretic).?? This book is intended for researchers interested in model reduction and approximation, particularly graduate students and young researchers.
Realization And Model Reduction Of Dynamical Systems
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Author : Christopher Beattie
language : en
Publisher: Springer Nature
Release Date : 2022-06-09
Realization And Model Reduction Of Dynamical Systems written by Christopher Beattie and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-09 with Science categories.
This book celebrates Professor Thanos Antoulas's 70th birthday, marking his fundamental contributions to systems and control theory, especially model reduction and, more recently, data-driven modeling and system identification. Model reduction is a prominent research topic with wide ranging scientific and engineering applications.
Model Reduction Of Complex Dynamical Systems
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Author : Peter Benner
language : en
Publisher: Springer Nature
Release Date : 2021-08-26
Model Reduction Of Complex Dynamical Systems written by Peter Benner and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-26 with Mathematics categories.
This contributed volume presents some of the latest research related to model order reduction of complex dynamical systems with a focus on time-dependent problems. Chapters are written by leading researchers and users of model order reduction techniques and are based on presentations given at the 2019 edition of the workshop series Model Reduction of Complex Dynamical Systems – MODRED, held at the University of Graz in Austria. The topics considered can be divided into five categories: system-theoretic methods, such as balanced truncation, Hankel norm approximation, and reduced-basis methods; data-driven methods, including Loewner matrix and pencil-based approaches, dynamic mode decomposition, and kernel-based methods; surrogate modeling for design and optimization, with special emphasis on control and data assimilation; model reduction methods in applications, such as control and network systems, computational electromagnetics, structural mechanics, and fluid dynamics; and model order reduction software packages and benchmarks. This volume will be an ideal resource for graduate students and researchers in all areas of model reduction, as well as those working in applied mathematics and theoretical informatics.
Computational Methods For Approximation Of Large Scale Dynamical Systems
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Author : Mohammad Monir Uddin
language : en
Publisher: CRC Press
Release Date : 2019-04-30
Computational Methods For Approximation Of Large Scale Dynamical Systems written by Mohammad Monir Uddin and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-30 with Mathematics categories.
These days, computer-based simulation is considered the quintessential approach to exploring new ideas in the different disciplines of science, engineering and technology (SET). To perform simulations, a physical system needs to be modeled using mathematics; these models are often represented by linear time-invariant (LTI) continuous-time (CT) systems. Oftentimes these systems are subject to additional algebraic constraints, leading to first- or second-order differential-algebraic equations (DAEs), otherwise known as descriptor systems. Such large-scale systems generally lead to massive memory requirements and enormous computational complexity, thus restricting frequent simulations, which are required by many applications. To resolve these complexities, the higher-dimensional system may be approximated by a substantially lower-dimensional one through model order reduction (MOR) techniques. Computational Methods for Approximation of Large-Scale Dynamical Systems discusses computational techniques for the MOR of large-scale sparse LTI CT systems. Although the book puts emphasis on the MOR of descriptor systems, it begins by showing and comparing the various MOR techniques for standard systems. The book also discusses the low-rank alternating direction implicit (LR-ADI) iteration and the issues related to solving the Lyapunov equation of large-scale sparse LTI systems to compute the low-rank Gramian factors, which are important components for implementing the Gramian-based MOR. Although this book is primarly aimed at post-graduate students and researchers of the various SET disciplines, the basic contents of this book can be supplemental to the advanced bachelor's-level students as well. It can also serve as an invaluable reference to researchers working in academics and industries alike. Features: Provides an up-to-date, step-by-step guide for its readers. Each chapter develops theories and provides necessary algorithms, worked examples, numerical experiments and related exercises. With the combination of this book and its supplementary materials, the reader gains a sound understanding of the topic. The MATLAB® codes for some selected algorithms are provided in the book. The solutions to the exercise problems, experiment data sets and a digital copy of the software are provided on the book's website; The numerical experiments use real-world data sets obtained from industries and research institutes.
Reduction Approximation Machine Learning Surrogates Emulators And Simulators
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Author : Gianluigi Rozza
language : en
Publisher: Springer Nature
Release Date : 2024-06-24
Reduction Approximation Machine Learning Surrogates Emulators And Simulators written by Gianluigi Rozza and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-24 with Mathematics categories.
This volume is focused on the review of recent algorithmic and mathematical advances and the development of new research directions for Mathematical Model Approximations via RAMSES (Reduced order models, Approximation theory, Machine learning, Surrogates, Emulators, Simulators) in the setting of parametrized partial differential equations also with sparse and noisy data in high-dimensional parameter spaces. The book is a valuable resource for researchers, as well as masters and Ph.D students.
Approximation Of Large Scale Dynamical Systems
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Author : Athanasios C. Antoulas
language : en
Publisher: SIAM
Release Date : 2009-06-25
Approximation Of Large Scale Dynamical Systems written by Athanasios C. Antoulas and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-25 with Mathematics categories.
Mathematical models are used to simulate, and sometimes control, the behavior of physical and artificial processes such as the weather and very large-scale integration (VLSI) circuits. The increasing need for accuracy has led to the development of highly complex models. However, in the presence of limited computational accuracy and storage capabilities model reduction (system approximation) is often necessary. Approximation of Large-Scale Dynamical Systems provides a comprehensive picture of model reduction, combining system theory with numerical linear algebra and computational considerations. It addresses the issue of model reduction and the resulting trade-offs between accuracy and complexity. Special attention is given to numerical aspects, simulation questions, and practical applications.
System And Data Driven Methods And Algorithms
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Author : Peter Benner
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2021-11-08
System And Data Driven Methods And Algorithms written by Peter Benner and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-08 with Mathematics categories.
An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This first volume focuses on real-time control theory, data assimilation, real-time visualization, high-dimensional state spaces and interaction of different reduction techniques.
Stability Preservation For Parametric Model Order Reduction By Matrix Interpolation
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Author : Andreas Michael Barthlen
language : en
Publisher: Cuvillier Verlag
Release Date : 2016-09-30
Stability Preservation For Parametric Model Order Reduction By Matrix Interpolation written by Andreas Michael Barthlen and has been published by Cuvillier Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-30 with Mathematics categories.
In dieser Arbeit wird das Problem der Stabilitätserhaltung für parametrische Modellreduktion mittels Matrixinterpolation untersucht. Hierfür werden die benötigten mathematischen Grundlagen aus der Systemtheorie eingeführt. Es werden darüber hinaus die beiden bekanntesten Modellreduktionsverfahren für lineare Systeme betrachtet und ein kurzer Überblick über verschiedene relevante Methoden zur parametrischen Modellreduktion gegeben. Die titelgebende Matrixinterpolation wird im Detail analysiert, und es werden die verschiedenen Schwierigkeiten des Verfahrens, als auch existierende Lösungen aus der Literatur, untersucht. Auf diesen aufbauend wird ein Verfahren zur Erweiterung von lokalen Unterräumen vorgeschlagen, während für die aus der Literatur bekannten Verfahren zur Stabilitätserhaltung mögliche Probleme aufgezeigt und neue theoretische Resultate gegeben werden. Es wird als Alternative ein neuartiges, flexibles Verfahren zur Stabilitätserhaltung vorgeschlagen, dessen potenzielle Vor- und Nachteile für zwei numerische Beispiele gezeigt werden. In this thesis the problem of stability preservation for parametric model order reduction by matrix interpolation is investigated. For this purpose the necessary mathematical fundamentals from system theory are given. Furthermore the two most popular model order reduction methods for linear systems are looked at and a brief introduction to various relevant methods for parametric model order reduction is given. The title giving matrix interpolation is analyzed in detail and its various problems, as well as solutions from literature, are studied. Based on these a procedure for the extension of local subspaces is given, whereas for the stability preservation methods known from literature possible problems are shown and new theoretical results are given. As an alternative a novel, flexible method for stability preservation is proposed and its potential pros and cons are shown for two numerical examples.