Identification And System Parameter Estimation
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System Identification
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Author : R. Isermann
language : en
Publisher: Elsevier
Release Date : 2014-05-23
System Identification written by R. Isermann and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-05-23 with Technology & Engineering categories.
System Identification is a special section of the International Federation of Automatic Control (IFAC)-Journal Automatica that contains tutorial papers regarding the basic methods and procedures utilized for system identification. Topics include modeling and identification; step response and frequency response methods; correlation methods; least squares parameter estimation; and maximum likelihood and prediction error methods. After analyzing the basic ideas concerning the parameter estimation methods, the book elaborates on the asymptotic properties of these methods, and then investigates the application of the methods to particular model structures. The text then discusses the practical aspects of process identification, which includes the usual, general procedures for process identification; selection of input signals and sampling time; offline and on-line identification; comparison of parameter estimation methods; data filtering; model order testing; and model verification. Computer program packages are also discussed. This compilation of tutorial papers aims to introduce the newcomers and non-specialists in this field to some of the basic methods and procedures used for system identification.
Identification Of Continuous Time Systems
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Author : Allamaraju Subrahmanyam
language : en
Publisher: CRC Press
Release Date : 2019-12-06
Identification Of Continuous Time Systems written by Allamaraju Subrahmanyam and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-06 with Technology & Engineering categories.
Models of dynamical systems are required for various purposes in the field of systems and control. The models are handled either in discrete time (DT) or in continuous time (CT). Physical systems give rise to models only in CT because they are based on physical laws which are invariably in CT. In system identification, indirect methods provide DT models which are then converted into CT. Methods of directly identifying CT models are preferred to the indirect methods for various reasons. The direct methods involve a primary stage of signal processing, followed by a secondary stage of parameter estimation. In the primary stage, the measured signals are processed by a general linear dynamic operation—computational or realized through prefilters, to preserve the system parameters in their native CT form—and the literature is rich on this aspect. In this book: Identification of Continuous-Time Systems-Linear and Robust Parameter Estimation, Allamaraju Subrahmanyam and Ganti Prasada Rao consider CT system models that are linear in their unknown parameters and propose robust methods of estimation. This book complements the existing literature on the identification of CT systems by enhancing the secondary stage through linear and robust estimation. In this book, the authors provide an overview of CT system identification, consider Markov-parameter models and time-moment models as simple linear-in-parameters models for CT system identification, bring them into mainstream model parameterization via basis functions, present a methodology to robustify the recursive least squares algorithm for parameter estimation of linear regression models, suggest a simple off-line error quantification scheme to show that it is possible to quantify error even in the absence of informative priors, and indicate some directions for further research. This modest volume is intended to be a useful addition to the literature on identifying CT systems.
System Identification Parameter And State Estimation
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Author : P. Eykhoff
language : en
Publisher: Chichester ; New York : Wiley
Release Date : 1974-05-23
System Identification Parameter And State Estimation written by P. Eykhoff and has been published by Chichester ; New York : Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 1974-05-23 with Mathematics categories.
Identification And System Parameter Estimation
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Author : Rolf Isermann
language : en
Publisher:
Release Date : 1980
Identification And System Parameter Estimation written by Rolf Isermann and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1980 with Estimation theory categories.
Identification And System Parameter Estimation
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Author :
language : en
Publisher:
Release Date : 1980
Identification And System Parameter Estimation written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1980 with Estimation theory categories.
Identification And System Parameter Estimation 1982
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Author : G. A. Bekey
language : en
Publisher: Elsevier
Release Date : 2016-06-06
Identification And System Parameter Estimation 1982 written by G. A. Bekey and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-06 with Technology & Engineering categories.
Identification and System Parameter Estimation 1982 covers the proceedings of the Sixth International Federation of Automatic Control (IFAC) Symposium. The book also serves as a tribute to Dr. Naum S. Rajbman. The text covers issues concerning identification and estimation, such as increasing interrelationships between identification/estimation and other aspects of system theory, including control theory, signal processing, experimental design, numerical mathematics, pattern recognition, and information theory. The book also provides coverage regarding the application and problems faced by several engineering and scientific fields that use identification and estimation, such as biological systems, traffic control, geophysics, aeronautics, robotics, economics, and power systems. Researchers from all scientific fields will find this book a great reference material, since it presents topics that concern various disciplines.
System Identification
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Author : Karel J. Keesman
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-05-16
System Identification written by Karel J. Keesman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-16 with Technology & Engineering categories.
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.
Identification And System Parameter Estimation
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Author :
language : en
Publisher:
Release Date : 1992
Identification And System Parameter Estimation written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Estimation theory categories.
System Identification
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Author : Lennart Ljung
language : en
Publisher: Pearson Education
Release Date : 1998-12-29
System Identification written by Lennart Ljung and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-12-29 with Technology & Engineering categories.
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.
Nonlinear System Identification Input Output Modeling Approach
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Author : Robert Haber
language : en
Publisher: Springer
Release Date : 1999-07-31
Nonlinear System Identification Input Output Modeling Approach written by Robert Haber and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-07-31 with Science categories.
The subject of the book is to present the modeling, parameter estimation and other aspects of the identification of nonlinear dynamic systems. The treatment is restricted to the input-output modeling approach. Because of the widespread usage of digital computers discrete time methods are preferred. Time domain parameter estimation methods are dealt with in detail, frequency domain and power spectrum procedures are described shortly. The theory is presented from the engineering point of view, and a large number of examples of case studies on the modeling and identifications of real processes illustrate the methods. Almost all processes are nonlinear if they are considered not merely in a small vicinity of the working point. To exploit industrial equipment as much as possible, mathematical models are needed which describe the global nonlinear behavior of the process. If the process is unknown, or if the describing equations are too complex, the structure and the parameters can be determined experimentally, which is the task of identification. The book is divided into seven chapters dealing with the following topics: 1. Nonlinear dynamic process models 2. Test signals for identification 3. Parameter estimation methods 4. Nonlinearity test methods 5. Structure identification 6. Model validity tests 7. Case studies on identification of real processes Chapter I summarizes the different model descriptions of nonlinear dynamical systems.