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Applied System Identification

1994 Mathematics
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Release : 1994
Genre : Mathematics
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Applied System Identification by : Jer-Nan Juang

Download or read book Applied System Identification written by Jer-Nan Juang. This book was released on 1994. Available in PDF, EPUB and Kindle. Book excerpt: System identification is the process of developing or improving a mathematical representation of a physical system using experimental data. Over the past decade, several system identification techniques have been developed within different disciplines. This text/reference brings together the significant advances over the past decade into a single unified source -- with common mathematical notation that will enable readers from a variety of engineering areas -- e.g., aerospace, electrical, civil, and mechanical engineering --to apply system identification to engineering systems. Focuses on the three types of identification in engineering structures -- modal parameter identification; structural-model parameter identification; and control-model identification. For researchers and engineers, students, and teachers in vibrations, controls and system identification.

System Identification

2011-05-16 Technology & Engineering
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Release : 2011-05-16
Genre : Technology & Engineering
Kind : eBook
Book Rating : 225/5 ( reviews)

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Book Synopsis System Identification by : Karel J. Keesman

Download or read book System Identification written by Karel J. Keesman. This book was released on 2011-05-16. Available in PDF, EPUB and Kindle. Book excerpt: System Identification shows the student reader how to approach the system identification problem in a systematic fashion. The process is divided into three basic steps: experimental design and data collection; model structure selection and parameter estimation; and model validation, each of which is the subject of one or more parts of the text. Following an introduction on system theory, particularly in relation to model representation and model properties, the book contains four parts covering: • data-based identification – non-parametric methods for use when prior system knowledge is very limited; • time-invariant identification for systems with constant parameters; • time-varying systems identification, primarily with recursive estimation techniques; and • model validation methods. A fifth part, composed of appendices, covers the various aspects of the underlying mathematics needed to begin using the text. The book uses essentially semi-physical or gray-box modeling methods although data-based, transfer-function system descriptions are also introduced. The approach is problem-based rather than rigorously mathematical. The use of finite input–output data is demonstrated for frequency- and time-domain identification in static, dynamic, linear, nonlinear, time-invariant and time-varying systems. Simple examples are used to show readers how to perform and emulate the identification steps involved in various control design methods with more complex illustrations derived from real physical, chemical and biological applications being used to demonstrate the practical applicability of the methods described. End-of-chapter exercises (for which a downloadable instructors’ Solutions Manual is available from fill in URL here) will both help students to assimilate what they have learned and make the book suitable for self-tuition by practitioners looking to brush up on modern techniques. Graduate and final-year undergraduate students will find this text to be a practical and realistic course in system identification that can be used for assessing the processes of a variety of engineering disciplines. System Identification will help academic instructors teaching control-related to give their students a good understanding of identification methods that can be used in the real world without the encumbrance of undue mathematical detail.

Subspace Methods for System Identification

2005-06-15 Technology & Engineering
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Release : 2005-06-15
Genre : Technology & Engineering
Kind : eBook
Book Rating : 814/5 ( reviews)

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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. This book was released on 2005-06-15. 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.

Application of System Identification in Engineering

2014-05-04 Technology & Engineering
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Release : 2014-05-04
Genre : Technology & Engineering
Kind : eBook
Book Rating : 282/5 ( reviews)

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Book Synopsis Application of System Identification in Engineering by : H.G. Natke

Download or read book Application of System Identification in Engineering written by H.G. Natke. This book was released on 2014-05-04. Available in PDF, EPUB and Kindle. Book excerpt: System identification is a powerful tool in engineering. Its various methods in the frequency and in the time domain have been extensively discussed in earlier CISM courses. The aim of this course is to describe the state of the art in specific application areas, such as estimation of eigenquantities (in the aerospace industry, in civil engineering, in naval engineering etc.), noise source detection, fault detection by investigation of dynamic properties, such as machine sound characteristics, and the identification of the dynamic behaviour of flow induced systems (e.g. aerolastic problems). Geotechnical applications are also among the fields of interest. The lecture notes contain demonstrations of several methods and include a valuation by combining various kinds of experience. Such complex information includes not only theoretical aspects of identification but also advice on practical handling, for example concerning testing effort and data handling.

Errors-in-Variables Methods in System Identification

2018-12-26 Technology & Engineering
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Release : 2018-12-26
Genre : Technology & Engineering
Kind : eBook
Book Rating : 255/5 ( reviews)

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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. This book was released on 2018-12-26. 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.

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