Mastering System Identification in 100 Exercises (eBook)
282 Seiten
Wiley (Verlag)
978-1-118-21850-1 (ISBN)
Johan Schoukens, PhD, serves as a full-time professor in the ELEC Department at the Vrije Universiteit Brussel. He has been a Fellow of IEEE since 1997 and was the recipient of the 2003 IEEE Instrumentation and Measurement Society Distinguished Service Award. Rik Pintelon, PhD, serves as a full-time professor at the Vrije Universiteit Brussel in the ELEC Department. He has been a Fellow of IEEE since 1998 and is the recipient of the 2012 IEEE Joseph F. Keithley Award in Instrumentation and Measurement (IEEE Technical Field Award). Yves Rolain, PhD, serves as a full-time professor at the Vrije Universiteit Brussel in the ELEC department. He has been a Fellow of IEEE since 2006 and was the recipient of the 2004 IEEE Instrumentation and Measurement Society Technical Award.
System identification is a very important topic for both
off-line simulation studies and also on-line control applications,
in particular for non-linear systems whose parameters change with
the operating conditions.
The book "Mastering System Identification in 100
Exercises" does a thorough job of explaining and illustrating
the system identification theory and its application in modeling
systems for off-line simulation studies. The major emphasis of the
book is on frequency domain models, that are well suited for
off-line studies, and also as the authors say, "is partly due
to the authors' background and experience". A small
part of the book is devoted to time-domain modeling.
The one hundred exercises are arranged in 7 Chapters. Chapter 1
provides a basic introduction to the mathematical techniques
commonly used in parameter estimation, with the type of signals,
random or periodic, introduced in Chapter 2. Measurement of
frequency response functions, excitation signals and noise
estimation are introduced by the exercises in Chapter 3. With this
background, the reader is equipped to estimate the plant and noise
dynamics for linear systems in Chapter 4. Noise plays a significant
part in estimation practice and a good deal of attention is devoted
to noise characterization and estimation. These and related
aspects, including the linear approximation of non-linear systems,
are extensively covered in the following two chapters, i.e.
Chapters 5 and 6. Identification of parameters with non-linearities
is illustrated by the exercises in Chapter 7.
The exercises given in the book are supported by solutions using
MATLAB programs.
The noise in measurements used to estimate a system model is
given a thorough treatment in the book. For a reader not conversant
with estimation theory, the book provides a gradual and well
organized approach starting from basic to more advanced problem
solution.
As mentioned above, on-line system model identification for
real-time control is also a very important topic. Such
identification, done primarily in time domain, also has the added
constraint of limited time for computation in real-time. The
standard off-line identification procedures need significant
modifications to make them suitable for real-time application. That
aspect of system identification is missing from this book as it is
primarily devoted to model identification for off-line simulation
studies. It would have been desirable to indicate that somehow in
the title.
- Professor Om Malik, University of Calgary
Erscheint lt. Verlag | 2.4.2012 |
---|---|
Sprache | englisch |
Themenwelt | Mathematik / Informatik ► Mathematik |
Technik ► Elektrotechnik / Energietechnik | |
Technik ► Maschinenbau | |
Wirtschaft ► Betriebswirtschaft / Management ► Unternehmensführung / Management | |
Schlagworte | Control Process & Measurements • Control Systems Technology • Electrical & Electronics Engineering • Elektrotechnik u. Elektronik • Maschinenbau • mechanical engineering • Mess- u. Regeltechnik • Regelungstechnik • Signal Processing • Signalverarbeitung |
ISBN-10 | 1-118-21850-7 / 1118218507 |
ISBN-13 | 978-1-118-21850-1 / 9781118218501 |
Haben Sie eine Frage zum Produkt? |
Größe: 27,3 MB
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