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Advanced Textbooks in Control and Signal Processing

System Identification

An Introduction

Authors: Keesman, Karel J.

  • Uses a practical example-based approach to show students how identification really works
  • Teaches students the fundamentals of systems identification without unduly complicated mathematics
  • On-line solutions manual will assist the instructor with planning out-of-class assignments and already-practicing engineers with self-study
  • Takes account of the most recent developments in system identification
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eBook $69.99
price for USA
  • ISBN 978-0-85729-522-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Softcover $99.00
price for USA
  • ISBN 978-0-85729-521-7
  • with online files
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
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About this Textbook

System Identification: an Introduction shows the (student) reader how to approach the system identification problem in a systematic fashion. Essentially, system identification is an art of modelling, where appropriate choices have to be made concerning the level of approximation, given prior system’s knowledge, noisy data and the final modelling objective. The system identification process is basically divided into three 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.

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.

The book uses essentially semi-physical or grey-box modelling 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 model applications, as control, prediction and experimental design, 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 www.springer.com/978-0-85729-521-7) will both help students to assimilate what they have learnt 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: an Introduction will help academic instructors teaching control-related courses 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.

 

About the authors

Karel Keesman received his Ph.D. for his work on set-membership identification and prediction of ill-defined systems, with application to a water quality system at the University of Twente in 1989. His main research interests focus on identification, modelling and control of uncertain dynamic systems with a biological component, as bioreactors, environmental and ecological systems, with more than 120 papers in international journals and refereed proceedings. For more than 25 years he is active in the field of system identification, in which he developed and applied identification methods to a wide range of problems.

Reviews

From the reviews:

“The book presents a systematic overview of the fundamental problems and methods in the modern system identification theory. The material is divided into four parts covering data based non-parametric identification methods, time-invariant system identification, time-varying system identification and model validation problems. … Each chapter of the book is finished with references, historical notes and exercises to be solved by the reader. … Numerous examples … demonstrate the practical applicability of the presented methods. The book can be recommended for students and practitioners for self-study.” (Zygmunt Hasiewicz, Zentralblatt MATH, Vol. 1230, 2012)


Table of contents (9 chapters)

Buy this book

eBook $69.99
price for USA
  • ISBN 978-0-85729-522-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Softcover $99.00
price for USA
  • ISBN 978-0-85729-521-7
  • with online files
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
System Identification
Book Subtitle
An Introduction
Authors
Series Title
Advanced Textbooks in Control and Signal Processing
Copyright
2011
Publisher
Springer-Verlag London
Copyright Holder
Springer-Verlag London Limited
eBook ISBN
978-0-85729-522-4
DOI
10.1007/978-0-85729-522-4
Softcover ISBN
978-0-85729-521-7
Series ISSN
1439-2232
Edition Number
1
Number of Pages
XXVI, 323
Number of Illustrations and Tables
72 b/w illustrations, 37 illustrations in colour
Topics