"System Identification: An Introduction" by Karel J. Keesman (Repost)

This book is designed to help students and practitioners to understand the system identification process, to read the identification literature and to make appropriate choices in this process.

The book uses essentially semi-physical or grey-box modelling methods although data-based, transfer-function system descriptions are also introduced.

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.

This book 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.


Contents
Series Editors' Foreword
Preface
Acknowledgements
1: Introduction
Part I: Data-based Identification
2: System Response Methods
3: Frequency Response Methods
4: Correlation Methods
Part II: Time-invariant Systems Identification
5: Static Systems Identification
6: Dynamic Systems Identification
Part III: Time-varying Systems Identification
7: Time-varying Static Systems Identification
8: Time-varying Dynamic Systems Identification
Part IV: Model Validation
9: Model Validation Techniques
Appendix
References
Index