Overview
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
Includes supplementary material: sn.pub/extras
Request lecturer material: sn.pub/lecturer-material
Part of the book series: Advanced Textbooks in Control and Signal Processing (C&SP)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (9 chapters)
-
Data-based Identification
-
Time-invariant Systems Identification
-
Time-varying systems Identification
-
Model Validation
Keywords
About this book
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.
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)
Authors and Affiliations
About the author
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.
Bibliographic Information
Book Title: System Identification
Book Subtitle: An Introduction
Authors: Karel J. Keesman
Series Title: Advanced Textbooks in Control and Signal Processing
DOI: https://doi.org/10.1007/978-0-85729-522-4
Publisher: Springer London
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag London Limited 2011
Softcover ISBN: 978-0-85729-521-7Published: 18 May 2011
eBook ISBN: 978-0-85729-522-4Published: 16 May 2011
Series ISSN: 1439-2232
Series E-ISSN: 2510-3814
Edition Number: 1
Number of Pages: XXVI, 323
Number of Illustrations: 72 b/w illustrations, 37 illustrations in colour
Topics: Control and Systems Theory, Signal, Image and Speech Processing, Systems Theory, Control, Mechatronics