Efficient Modeling and Control of Large-Scale Systems

Efficient Modeling and Control of Large-Scale Systems

Author: Javad Mohammadpour

Publisher: Springer Science & Business Media

Published: 2010-06-23

Total Pages: 350

ISBN-13: 144195757X

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Complexity and dynamic order of controlled engineering systems is constantly increasing. Complex large scale systems (where "large" reflects the system’s order and not necessarily its physical size) appear in many engineering fields, such as micro-electromechanics, manufacturing, aerospace, civil engineering and power engineering. Modeling of these systems often result in very high-order models imposing great challenges to the analysis, design and control problems. "Efficient Modeling and Control of Large-Scale Systems" compiles state-of-the-art contributions on recent analytical and computational methods for addressing model reduction, performance analysis and feedback control design for such systems. Also addressed at length are new theoretical developments, novel computational approaches and illustrative applications to various fields, along with: - An interdisciplinary focus emphasizing methods and approaches that can be commonly applied in various engineering fields -Examinations of applications in various fields including micro-electromechanical systems (MEMS), manufacturing processes, power networks, traffic control "Efficient Modeling and Control of Large-Scale Systems" is an ideal volume for engineers and researchers working in the fields of control and dynamic systems.


Computational Methods for Approximation of Large-Scale Dynamical Systems

Computational Methods for Approximation of Large-Scale Dynamical Systems

Author: Mohammad Monir Uddin

Publisher: CRC Press

Published: 2019-04-30

Total Pages: 345

ISBN-13: 135102860X

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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.


Realization and Model Reduction of Dynamical Systems

Realization and Model Reduction of Dynamical Systems

Author: Christopher Beattie

Publisher: Springer Nature

Published: 2022-06-09

Total Pages: 462

ISBN-13: 303095157X

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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

Model Reduction of Complex Dynamical Systems

Author: Peter Benner

Publisher: Springer Nature

Published: 2021-08-26

Total Pages: 415

ISBN-13: 3030729834

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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.


Active Flow and Combustion Control 2014

Active Flow and Combustion Control 2014

Author: Rudibert King

Publisher: Springer

Published: 2014-09-13

Total Pages: 405

ISBN-13: 3319119672

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The book reports on the latest theoretical and experimental advances in the field of active flow and combustion control. It covers new developments in actuator technology and sensing, in robust and optimal open- and closed-loop control, as well as in model reduction for control. It collects contributions presented during the third edition of the Active Flow and Combustion Control conference, held in September 10-12, 2014 at the Technische Universität Berlin (Germany). This conference, as well as the research presented in the book, have been supported by the collaborative research center SFB 1029 -Substantial efficiency increase in gas turbines through direct use of coupled unsteady combustion and flow dynamics, funded by the DFG (German Research Foundation).


8th International Munich Chassis Symposium 2017

8th International Munich Chassis Symposium 2017

Author: Prof. Dr. Peter E. Pfeffer

Publisher: Springer

Published: 2017-09-20

Total Pages: 804

ISBN-13: 3658184590

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You can find in this book the development of highly and fully automatic driving and the increasing electrification of the powertrain now face chassis development with new challenges too. Innovative chassis systems have to provide solutions for automated driving. The efficient chassis of the future also has to keep an eye on CO2 targets, comfort and customer focus at all times. A modern chassis has to provide for this in the form of innovations while taking the physical and mechanical interdependencies into account. Confronting these new developments is a challenge for simulation and testing.


System Reduction for Nanoscale IC Design

System Reduction for Nanoscale IC Design

Author: Peter Benner

Publisher: Springer

Published: 2017-06-02

Total Pages: 205

ISBN-13: 3319072366

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This book describes the computational challenges posed by the progression toward nanoscale electronic devices and increasingly short design cycles in the microelectronics industry, and proposes methods of model reduction which facilitate circuit and device simulation for specific tasks in the design cycle. The goal is to develop and compare methods for system reduction in the design of high dimensional nanoelectronic ICs, and to test these methods in the practice of semiconductor development. Six chapters describe the challenges for numerical simulation of nanoelectronic circuits and suggest model reduction methods for constituting equations. These include linear and nonlinear differential equations tailored to circuit equations and drift diffusion equations for semiconductor devices. The performance of these methods is illustrated with numerical experiments using real-world data. Readers will benefit from an up-to-date overview of the latest model reduction methods in computational nanoelectronics.


Matrix Functions And Matrix Equations

Matrix Functions And Matrix Equations

Author: Zhaojun Bai

Publisher: World Scientific

Published: 2015-09-04

Total Pages: 146

ISBN-13: 9814675784

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Matrix functions and matrix equations are widely used in science, engineering and social sciences due to the succinct and insightful way in which they allow problems to be formulated and solutions to be expressed. This book covers materials relevant to advanced undergraduate and graduate courses in numerical linear algebra and scientific computing. It is also well-suited for self-study. The broad content makes it convenient as a general reference to the subjects.


Interpolatory Methods for Model Reduction

Interpolatory Methods for Model Reduction

Author: A. C. Antoulas

Publisher: SIAM

Published: 2020-01-13

Total Pages: 245

ISBN-13: 1611976081

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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.


Stability Preservation for Parametric Model Order Reduction by Matrix Interpolation

Stability Preservation for Parametric Model Order Reduction by Matrix Interpolation

Author: Andreas Michael Barthlen

Publisher: Cuvillier Verlag

Published: 2016-09-30

Total Pages: 134

ISBN-13: 3736983611

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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.