Identification of Dynamic Systems

An Introduction with Applications

Rolf Isermann, Marco Münchhof (Autoren)

Buch | Softcover

XXV, 705 Seiten

2014 | 2011
Springer Berlin (Verlag)
978-3-642-42267-6 (ISBN)

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Many applications, from controls engineering to economics, require precise dynamic models. This book discusses methods for determination of dynamic models based on measurements taken at the process.

Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.

Prof. Dr.-Ing. Rolf Isermann leitet das Fachgebiet Regelungstechnik und Prozessautomatisierung im Institut für Automatisierungstechnik der TU Darmstadt. Seine Arbeit für die Mechatronik wurde mit dem Top Ten Award des renommierten MIT (Massachusetts Institute of Technology ) ausgezeichnet.

Introduction .- Mathematical Models of Linear Dynamic Systems and Stochastic Signals

Part I: Identification of Non-Parametric Models in the Frequency Domain - Continuous Time Signals

Part II: Identification with Non-Parametric Models - Continuous and Discrete Time

Part III: Identification with Parametric Models - Discrete Time Signals

Part IV: Identification with Parametric Models - Continuous Time Signals

PartV: Identification of Multi-Variable Systems

Part VI: Identification of Non-Linear Systems

Part VII: Miscellaneous Issues

Part VIII Applications

Part IX Appendix.

From the reviews:

"The book being reviewed may serve as a useful entry guidebook to the assembling of mathematical models for actual physical systems, some of which are even pictured. The gamut of problems that the book's material addresses is illustrated, over about seventy-five pages, with fifteen concrete examples ... . One remarkable feature of the book is an effort made to help the reader in the process of choice of models and methods through overview tables and diagrams." (A. F. Gualtierotti, Mathematical Reviews, Issue 2011 m)

"The book presents a broad spectrum of methods and approaches to dynamic system identification in a simple and unified manner. ... Each chapter is completed with a set of problems to be solved by the reader and a list of references. The book can be recommended as a good overview of contemporary parametric system identification techniques." (Zygmunt Hasiewicz, Zentralblatt MATH, Vol. 1230, 2012)

Erscheint lt. Verlag	23.11.2014
Zusatzinfo	XXV, 705 p. With Based on the book: Isermann: Identifikation dynamischer Systeme 1, 2.
Verlagsort	Berlin
Sprache	englisch
Maße	155 x 235 mm
Gewicht	1104 g
Themenwelt	Mathematik / Informatik ► Informatik ► Software Entwicklung
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Mathematik / Informatik ► Mathematik ► Algebra
	Mathematik / Informatik ► Mathematik ► Analysis
	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
	Naturwissenschaften ► Physik / Astronomie
	Technik
Schlagworte	Complexity • Frequency Response • linear systems • Nonlinear Systems • Parameter Estimation • System Identification
ISBN-10	3-642-42267-5 / 3642422675
ISBN-13	978-3-642-42267-6 / 9783642422676
Zustand	Neuware