Mastering System Identification in 100 Exercises [Paperback]

This book enables readers to understand system identification and linear system modeling through 100 practical exercises without requiring complex theoretical knowledge. The contents encompass state-of-the-art system identification methods, with both time and frequency domain system identification methods covered, including the pros and cons of each. Each chapter features MATLAB exercises, discussions of the exercises, accompanying MATLAB downloads, and larger projects that serve as potential assignments in this learn-by-doing resource.

Preface xiii

Acknowledgments xv

Abbreviations xvii

1 Identification 1

1.1 Introduction 1

1.2 Illustration of Some Important Aspects of System Identification 2

Exercise 1 .a (Least squares estimation of the value of a resistor) 2

Exercise 1 .b (Analysis of the standard deviation) 3

Exercise 2 (Study of the asymptotic distribution of an estimate) 5

Exercise 3 (Impact of noise on the regressor (input) measurements) 6

Exercise 4 (Importance of the choice of the independent variable or input) 7

Exercise 5.a (combining measurements with a varying SNR: Weighted least squares estimation) 8

Exercise 5.b (Weighted least squares estimation: A study of the variance) 9

Exercise 6 (Least squares estimation of models that are linear in the parameters) 11

Exercise 7 (Characterizing a 2-dimensional parameter estimate) 12

1.3 Maximum Likelihood Estimation for Gaussian and Laplace Distributed Noise 14

Exercise 8 (Dependence of the optimal cost function on the distribution of the disturbing noise) 14

1.4 Identification for Skew Distributions with Outliers 16

Exercise 9 (Identification in thelã…