The book is up-to-date in the field of system identification. It contains a large amount of code and references to the Matlab System Identification Toolbox. With the book being so thick, it may seem overwhelming to contemplate using it as a textbook for a single, introductory, one-semester course on system identification. However, in the preface, the author does provide some helpful suggestions on which sections to use for a beginner course and which to use for a more advanced course. Nevertheless, the book will serve as an excellent reference for students and instructors alike looking to learn about the field. I make this latter statement because what the author has bravely attempted to do with this book is to create a onestop resource for system identification. The focus of the book is on discrete-time, linear time invariant, open-loop identification. The structure of the book is hierarchical but also very accessible at different places, depending on the reader’s background. The book contains 26 chapters divided into five parts.
[1]
Keith R. Godfrey,et al.
Perturbation signals for system identification
,
1993
.
[2]
Lennart Ljung,et al.
System Identification: Theory for the User
,
1987
.
[3]
Liuping Wang,et al.
From Plant Data to Process Control: Ideas for Process Identification and PID Design
,
2000
.
[4]
Gwilym M. Jenkins,et al.
Time series analysis, forecasting and control
,
1971
.
[5]
David W. Clarke,et al.
Generalized predictive control - Part I. The basic algorithm
,
1987,
Autom..
[6]
P. Eykhoff.
System Identification Parameter and State Estimation
,
1974
.
[7]
Lennart Ljung,et al.
Modeling Of Dynamic Systems
,
1994
.