Logo - springer
Slogan - springer

Engineering - Control Engineering | System Identification

System Identification

An Introduction

Keesman, Karel J.

2011, XXVI, 323p. 109 illus., 37 illus. in color. With online files/update.

Available Formats:

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.


(net) price for USA

ISBN 978-0-85729-522-4

digitally watermarked, no DRM

Included Format: PDF and EPUB

download immediately after purchase

learn more about Springer eBooks

add to marked items


Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.


(net) price for USA

ISBN 978-0-85729-521-7

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days

add to marked items

  • 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

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.


Content Level » Upper undergraduate

Keywords » Control Applications - Control Engineering - Dynamic Systems - Parameter Estimation - Parameter Estimation Textbook - System Identification - System Identification Textbook - Time Series

Related subjects » Applications - Control Engineering - Robotics - Signals & Communication

Table of contents / Preface / Sample pages 

Popular Content within this publication 



Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Control.

Additional information