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 forself-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.
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 forself-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.
System Identification: An Introduction
323
System Identification: An Introduction
323
Product Details
| ISBN-13: | 9780857295217 |
|---|---|
| Publisher: | Springer London |
| Publication date: | 05/25/2011 |
| Series: | Advanced Textbooks in Control and Signal Processing , #2 |
| Edition description: | 2011 |
| Pages: | 323 |
| Product dimensions: | 6.10(w) x 9.25(h) x 0.04(d) |