Subspace Identification For Linear Systems

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Subspace Identification for Linear Systems

Author : Peter van Overschee
Publisher : Springer Science & Business Media
ISBN 13 : 1461304652
Total Pages : 263 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Subspace Identification for Linear Systems by : Peter van Overschee

Download or read book Subspace Identification for Linear Systems written by Peter van Overschee and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Subspace Identification for Linear Systems focuses on the theory, implementation and applications of subspace identification algorithms for linear time-invariant finite- dimensional dynamical systems. These algorithms allow for a fast, straightforward and accurate determination of linear multivariable models from measured input-output data. The theory of subspace identification algorithms is presented in detail. Several chapters are devoted to deterministic, stochastic and combined deterministic-stochastic subspace identification algorithms. For each case, the geometric properties are stated in a main 'subspace' Theorem. Relations to existing algorithms and literature are explored, as are the interconnections between different subspace algorithms. The subspace identification theory is linked to the theory of frequency weighted model reduction, which leads to new interpretations and insights. The implementation of subspace identification algorithms is discussed in terms of the robust and computationally efficient RQ and singular value decompositions, which are well-established algorithms from numerical linear algebra. The algorithms are implemented in combination with a whole set of classical identification algorithms, processing and validation tools in Xmath's ISID, a commercially available graphical user interface toolbox. The basic subspace algorithms in the book are also implemented in a set of Matlab files accompanying the book. An application of ISID to an industrial glass tube manufacturing process is presented in detail, illustrating the power and user-friendliness of the subspace identification algorithms and of their implementation in ISID. The identified model allows for an optimal control of the process, leading to a significant enhancement of the production quality. The applicability of subspace identification algorithms in industry is further illustrated with the application of the Matlab files to ten practical problems. Since all necessary data and Matlab files are included, the reader can easily step through these applications, and thus get more insight in the algorithms. Subspace Identification for Linear Systems is an important reference for all researchers in system theory, control theory, signal processing, automization, mechatronics, chemical, electrical, mechanical and aeronautical engineering.

Subspace Methods for System Identification

Author : Tohru Katayama
Publisher : Springer Science & Business Media
ISBN 13 : 184628158X
Total Pages : 400 pages
Book Rating : 4.8/5 (462 download)

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Book Synopsis Subspace Methods for System Identification by : Tohru Katayama

Download or read book Subspace Methods for System Identification written by Tohru Katayama and published by Springer Science & Business Media. This book was released on 2005-10-11 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: An in-depth introduction to subspace methods for system identification in discrete-time linear systems thoroughly augmented with advanced and novel results, this text is structured into three parts. Part I deals with the mathematical preliminaries: numerical linear algebra; system theory; stochastic processes; and Kalman filtering. Part II explains realization theory as applied to subspace identification. Stochastic realization results based on spectral factorization and Riccati equations, and on canonical correlation analysis for stationary processes are included. Part III demonstrates the closed-loop application of subspace identification methods. Subspace Methods for System Identification is an excellent reference for researchers and a useful text for tutors and graduate students involved in control and signal processing courses. It can be used for self-study and will be of interest to applied scientists or engineers wishing to use advanced methods in modeling and identification of complex systems.

Applied and Computational Control, Signals, and Circuits

Author : Biswa N. Datta
Publisher : Springer Science & Business Media
ISBN 13 : 1461205719
Total Pages : 557 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Applied and Computational Control, Signals, and Circuits by : Biswa N. Datta

Download or read book Applied and Computational Control, Signals, and Circuits written by Biswa N. Datta and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this annual series, Applied and Computational Control, Signals, and Circuits, is to keep abreast of the fast-paced developments in computational mathematics and scientific computing and their increasing use by researchers and engineers in control, signals, and circuits. The series is dedicated to fostering effective communication between mathematicians, computer scientists, computational scientists, software engineers, theorists, and practicing engineers. This interdisciplinary scope is meant to blend areas of mathematics (such as linear algebra, operator theory, and certain branches of analysis) and computational mathematics (numerical linear algebra, numerical differential equations, large scale and parallel matrix computations, numerical optimization) with control and systems theory, signal and image processing, and circuit analysis and design. The disciplines mentioned above have long enjoyed a natural synergy. There are distinguished journals in the fields of control and systems the ory, as well as signal processing and circuit theory, which publish high quality papers on mathematical and engineering aspects of these areas; however, articles on their computational and applications aspects appear only sporadically. At the same time, there has been tremendous recent growth and development of computational mathematics, scientific comput ing, and mathematical software, and the resulting sophisticated techniques are being gradually adapted by engineers, software designers, and other scientists to the needs of those applied disciplines.

Filtering and System Identification

Author : Michel Verhaegen
Publisher : Cambridge University Press
ISBN 13 : 9781107405028
Total Pages : 0 pages
Book Rating : 4.4/5 (5 download)

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Book Synopsis Filtering and System Identification by : Michel Verhaegen

Download or read book Filtering and System Identification written by Michel Verhaegen and published by Cambridge University Press. This book was released on 2012-07-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Filtering and system identification are powerful techniques for building models of complex systems. This 2007 book discusses the design of reliable numerical methods to retrieve missing information in models derived using these techniques. Emphasis is on the least squares approach as applied to the linear state-space model, and problems of increasing complexity are analyzed and solved within this framework, starting with the Kalman filter and concluding with the estimation of a full model, noise statistics and state estimator directly from the data. Key background topics, including linear matrix algebra and linear system theory, are covered, followed by different estimation and identification methods in the state-space model. With end-of-chapter exercises, MATLAB simulations and numerous illustrations, this book will appeal to graduate students and researchers in electrical, mechanical and aerospace engineering. It is also useful for practitioners. Additional resources for this title, including solutions for instructors, are available online at www.cambridge.org/9780521875127.

System Identification

Author : Lennart Ljung
Publisher : Pearson Education
ISBN 13 : 0132440539
Total Pages : 873 pages
Book Rating : 4.1/5 (324 download)

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Book Synopsis System Identification by : Lennart Ljung

Download or read book System Identification written by Lennart Ljung and published by Pearson Education. This book was released on 1998-12-29 with total page 873 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field's leading text, now completely updated. Modeling dynamical systems — theory, methodology, and applications. Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and general non-linear black box methods, including neural networks and neuro-fuzzy modeling. The book contains many new computer-based examples designed for Ljung's market-leading software, System Identification Toolbox for MATLAB. Ljung combines careful mathematics, a practical understanding of real-world applications, and extensive exercises. He introduces both black-box and tailor-made models of linear as well as non-linear systems, and he describes principles, properties, and algorithms for a variety of identification techniques: Nonparametric time-domain and frequency-domain methods. Parameter estimation methods in a general prediction error setting. Frequency domain data and frequency domain interpretations. Asymptotic analysis of parameter estimates. Linear regressions, iterative search methods, and other ways to compute estimates. Recursive (adaptive) estimation techniques. Ljung also presents detailed coverage of the key issues that can make or break system identification projects, such as defining objectives, designing experiments, controlling the bias distribution of transfer-function estimates, and carefully validating the resulting models. The first edition of System Identification has been the field's most widely cited reference for over a decade. This new edition will be the new text of choice for anyone concerned with system identification theory and practice.

Linear Parameter-varying System Identification

Author : Paulo Lopes dos Santos
Publisher : World Scientific
ISBN 13 : 9814355445
Total Pages : 402 pages
Book Rating : 4.8/5 (143 download)

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Book Synopsis Linear Parameter-varying System Identification by : Paulo Lopes dos Santos

Download or read book Linear Parameter-varying System Identification written by Paulo Lopes dos Santos and published by World Scientific. This book was released on 2012 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This review volume reports the state-of-the-art in Linear Parameter Varying (LPV) system identification. It focuses on the most recent LPV identification methods for both discrete-time and continuous-time models--

Subspace Methods for System Identification

Author : Tohru Katayama
Publisher : Springer Science & Business Media
ISBN 13 : 9781852339814
Total Pages : 418 pages
Book Rating : 4.3/5 (398 download)

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Book Synopsis Subspace Methods for System Identification by : Tohru Katayama

Download or read book Subspace Methods for System Identification written by Tohru Katayama and published by Springer Science & Business Media. This book was released on 2005-06-15 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: An in-depth introduction to subspace methods for system identification in discrete-time linear systems thoroughly augmented with advanced and novel results, this text is structured into three parts. Part I deals with the mathematical preliminaries: numerical linear algebra; system theory; stochastic processes; and Kalman filtering. Part II explains realization theory as applied to subspace identification. Stochastic realization results based on spectral factorization and Riccati equations, and on canonical correlation analysis for stationary processes are included. Part III demonstrates the closed-loop application of subspace identification methods. Subspace Methods for System Identification is an excellent reference for researchers and a useful text for tutors and graduate students involved in control and signal processing courses. It can be used for self-study and will be of interest to applied scientists or engineers wishing to use advanced methods in modeling and identification of complex systems.

Linear Stochastic Systems

Author : Anders Lindquist
Publisher : Springer
ISBN 13 : 3662457504
Total Pages : 781 pages
Book Rating : 4.6/5 (624 download)

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Book Synopsis Linear Stochastic Systems by : Anders Lindquist

Download or read book Linear Stochastic Systems written by Anders Lindquist and published by Springer. This book was released on 2015-04-24 with total page 781 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a treatise on the theory and modeling of second-order stationary processes, including an exposition on selected application areas that are important in the engineering and applied sciences. The foundational issues regarding stationary processes dealt with in the beginning of the book have a long history, starting in the 1940s with the work of Kolmogorov, Wiener, Cramér and his students, in particular Wold, and have since been refined and complemented by many others. Problems concerning the filtering and modeling of stationary random signals and systems have also been addressed and studied, fostered by the advent of modern digital computers, since the fundamental work of R.E. Kalman in the early 1960s. The book offers a unified and logically consistent view of the subject based on simple ideas from Hilbert space geometry and coordinate-free thinking. In this framework, the concepts of stochastic state space and state space modeling, based on the notion of the conditional independence of past and future flows of the relevant signals, are revealed to be fundamentally unifying ideas. The book, based on over 30 years of original research, represents a valuable contribution that will inform the fields of stochastic modeling, estimation, system identification, and time series analysis for decades to come. It also provides the mathematical tools needed to grasp and analyze the structures of algorithms in stochastic systems theory.

Exact and Approximate Modeling of Linear Systems

Author : Ivan Markovsky
Publisher : SIAM
ISBN 13 : 0898716039
Total Pages : 210 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Exact and Approximate Modeling of Linear Systems by : Ivan Markovsky

Download or read book Exact and Approximate Modeling of Linear Systems written by Ivan Markovsky and published by SIAM. This book was released on 2006-01-31 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exact and Approximate Modeling of Linear Systems: A Behavioral Approach elegantly introduces the behavioral approach to mathematical modeling, an approach that requires models to be viewed as sets of possible outcomes rather than to be a priori bound to particular representations. The authors discuss exact and approximate fitting of data by linear, bilinear, and quadratic static models and linear dynamic models, a formulation that enables readers to select the most suitable representation for a particular purpose. This book presents exact subspace-type and approximate optimization-based identification methods, as well as representation-free problem formulations, an overview of solution approaches, and software implementation. Readers will find an exposition of a wide variety of modeling problems starting from observed data. The presented theory leads to algorithms that are implemented in C language and in MATLAB.

Modeling and Identification of Linear Parameter-Varying Systems

Author : Roland Toth
Publisher : Springer Science & Business Media
ISBN 13 : 364213811X
Total Pages : 337 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Modeling and Identification of Linear Parameter-Varying Systems by : Roland Toth

Download or read book Modeling and Identification of Linear Parameter-Varying Systems written by Roland Toth and published by Springer Science & Business Media. This book was released on 2010-06-13 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through the past 20 years, the framework of Linear Parameter-Varying (LPV) systems has become a promising system theoretical approach to h- dle the controlof mildly nonlinear and especially position dependent systems which are common in mechatronic applications and in the process ind- try. The birth of this system class was initiated by the need of engineers to achieve better performance for nonlinear and time-varying dynamics, c- mon in many industrial applications, than what the classical framework of Linear Time-Invariant (LTI) control can provide. However, it was also a p- mary goal to preserve simplicity and “re-use” the powerful LTI results by extending them to the LPV case. The progress continued according to this philosophy and LPV control has become a well established ?eld with many promising applications. Unfortunately, modeling of LPV systems, especially based on measured data (which is called system identi?cation) has seen a limited development sincethebirthoftheframework. Currentlythisbottleneck oftheLPVfra- work is halting the transfer of the LPV theory into industrial use. Without good models that ful?ll the expectations of the users and without the und- standing how these models correspond to the dynamics of the application, it is di?cult to design high performance LPV control solutions. This book aims to bridge the gap between modeling and control by investigating the fundamental questions of LPV modeling and identi?cation. It explores the missing details of the LPV system theory that have hindered the formu- tion of a well established identi?cation framework.

Least Squares Support Vector Machines

Author : Johan A. K. Suykens
Publisher : World Scientific
ISBN 13 : 9789812381514
Total Pages : 318 pages
Book Rating : 4.3/5 (815 download)

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Book Synopsis Least Squares Support Vector Machines by : Johan A. K. Suykens

Download or read book Least Squares Support Vector Machines written by Johan A. K. Suykens and published by World Scientific. This book was released on 2002 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on Least Squares Support Vector Machines (LS-SVMs) which are reformulations to standard SVMs. LS-SVMs are closely related to regularization networks and Gaussian processes but additionally emphasize and exploit primal-dual interpretations from optimization theory. The authors explain the natural links between LS-SVM classifiers and kernel Fisher discriminant analysis. Bayesian inference of LS-SVM models is discussed, together with methods for imposing spareness and employing robust statistics. The framework is further extended towards unsupervised learning by considering PCA analysis and its kernel version as a one-class modelling problem. This leads to new primal-dual support vector machine formulations for kernel PCA and kernel CCA analysis. Furthermore, LS-SVM formulations are given for recurrent networks and control. In general, support vector machines may pose heavy computational challenges for large data sets. For this purpose, a method of fixed size LS-SVM is proposed where the estimation is done in the primal space in relation to a Nystrom sampling with active selection of support vectors. The methods are illustrated with several examples.

The Statistical Theory of Linear Systems

Author : E. J. Hannan
Publisher : SIAM
ISBN 13 : 1611972183
Total Pages : 418 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis The Statistical Theory of Linear Systems by : E. J. Hannan

Download or read book The Statistical Theory of Linear Systems written by E. J. Hannan and published by SIAM. This book was released on 2012-05-31 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally published: New York: Wiley, c1988.

Identification of Linear Systems

Author : J. Schoukens
Publisher : Elsevier
ISBN 13 : 0080912567
Total Pages : 353 pages
Book Rating : 4.0/5 (89 download)

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Book Synopsis Identification of Linear Systems by : J. Schoukens

Download or read book Identification of Linear Systems written by J. Schoukens and published by Elsevier. This book was released on 2014-06-28 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concentrates on the problem of accurate modeling of linear systems. It presents a thorough description of a method of modeling a linear dynamic invariant system by its transfer function. The first two chapters provide a general introduction and review for those readers who are unfamiliar with identification theory so that they have a sufficient background knowledge for understanding the methods described later. The main body of the book looks at the basic method used by the authors to estimate the parameter of the transfer function, how it is possible to optimize the excitation signals. Further chapters extend the estimation method proposed. Applications are then discussed and the book concludes with practical guidelines which illustrate the method and offer some rules-of-thumb.

Errors-in-Variables Methods in System Identification

Author : Torsten Söderström
Publisher : Springer
ISBN 13 : 3319750011
Total Pages : 485 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Errors-in-Variables Methods in System Identification by : Torsten Söderström

Download or read book Errors-in-Variables Methods in System Identification written by Torsten Söderström and published by Springer. This book was released on 2018-04-07 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a non-trivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuous-time models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find. A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including: instrumental variables methods; methods based on bias-compensation; covariance matching methods; and prediction error and maximum-likelihood methods. The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems. Errors-in-Variables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving over-determined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems.

Principles of System Identification

Author : Arun K. Tangirala
Publisher : CRC Press
ISBN 13 : 143989602X
Total Pages : 908 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Principles of System Identification by : Arun K. Tangirala

Download or read book Principles of System Identification written by Arun K. Tangirala and published by CRC Press. This book was released on 2018-10-08 with total page 908 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master Techniques and Successfully Build Models Using a Single Resource Vital to all data-driven or measurement-based process operations, system identification is an interface that is based on observational science, and centers on developing mathematical models from observed data. Principles of System Identification: Theory and Practice is an introductory-level book that presents the basic foundations and underlying methods relevant to system identification. The overall scope of the book focuses on system identification with an emphasis on practice, and concentrates most specifically on discrete-time linear system identification. Useful for Both Theory and Practice The book presents the foundational pillars of identification, namely, the theory of discrete-time LTI systems, the basics of signal processing, the theory of random processes, and estimation theory. It explains the core theoretical concepts of building (linear) dynamic models from experimental data, as well as the experimental and practical aspects of identification. The author offers glimpses of modern developments in this area, and provides numerical and simulation-based examples, case studies, end-of-chapter problems, and other ample references to code for illustration and training. Comprising 26 chapters, and ideal for coursework and self-study, this extensive text: Provides the essential concepts of identification Lays down the foundations of mathematical descriptions of systems, random processes, and estimation in the context of identification Discusses the theory pertaining to non-parametric and parametric models for deterministic-plus-stochastic LTI systems in detail Demonstrates the concepts and methods of identification on different case-studies Presents a gradual development of state-space identification and grey-box modeling Offers an overview of advanced topics of identification namely the linear time-varying (LTV), non-linear, and closed-loop identification Discusses a multivariable approach to identification using the iterative principal component analysis Embeds MATLAB® codes for illustrated examples in the text at the respective points Principles of System Identification: Theory and Practice presents a formal base in LTI deterministic and stochastic systems modeling and estimation theory; it is a one-stop reference for introductory to moderately advanced courses on system identification, as well as introductory courses on stochastic signal processing or time-series analysis.The MATLAB scripts and SIMULINK models used as examples and case studies in the book are also available on the author's website: http://arunkt.wix.com/homepage#!textbook/c397

Trends in Control

Author : Alberto Isidori
Publisher : Springer Science & Business Media
ISBN 13 : 1447130618
Total Pages : 424 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Trends in Control by : Alberto Isidori

Download or read book Trends in Control written by Alberto Isidori and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the text of the plenary lectures and the mini-courses of the European Control Conference (ECC 95) held in Rome, Italy, September 5-September 8, 1995. In particular, the book includes nine essays in which a selected number of prominent authorities present their views on some of the most recent developments in the theory and practice of control systems design and three self-contained sets of lecture notes. Some of the essays are focused on the topic of robust control. The article by J. Ackermann describes how to robustly control the rotational motions of a vehicle, to the purpose of simplifying the driver's task. The contribution by H. K wakernaak presents a detailed discussion of the requirements that performance and robustness impose on control systems design and of the symmetric roles of sensitivity and complementary sensitivity functions. The article by P. Boulet, B. A. Francis, P. C . Hughes and T. Hong describes an experimental testbed facility, called Daisy, whose dynamics emulate those of a real large flexible space structure and whose purpose is to test advanced identification and control design methods. The article of K. Glover discusses recent advances in uncertain system modeling, analysis and design, with ref erence to a flight control case study that has been test flown. The other essays describe advances in fundamental problems of control theory. The article by V. A. Yakubovich is a survey of certain new infinite horizon linear-quadratic optimization problems. The contribution by A. S.

Advances in Neural Information Processing Systems 19

Author : Bernhard Schölkopf
Publisher : MIT Press
ISBN 13 : 0262195682
Total Pages : 1668 pages
Book Rating : 4.2/5 (621 download)

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Book Synopsis Advances in Neural Information Processing Systems 19 by : Bernhard Schölkopf

Download or read book Advances in Neural Information Processing Systems 19 written by Bernhard Schölkopf and published by MIT Press. This book was released on 2007 with total page 1668 pages. Available in PDF, EPUB and Kindle. Book excerpt: The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation and machine learning. This volume contains the papers presented at the December 2006 meeting, held in Vancouver.