Identifikation Dynamischer Systeme: Band 1: Frequenzgangmessung, Fourieranalyse, Korrelationsanalyse, Einf Hrung in Die Parametersch Tzung - Hardcover

Hardcover

ISBN 10: 354012635X ISBN 13: 9783540126355

Synopsis

For many applications, ranging from controls engineering to natural sciences and economics, precise dynamic models must be derived. In the vast majority of applications, such precise models cannot be derived by theoretical considerations only. The book discusses methods, which allow the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification respectively.

After a short introduction into the required methodology of continuous-time and discrete-time linear systems, the focus is first on the identification of non-parametric models with continuous-time signals employing methods such as Fourier transform, measurement of the frequency response and correlation analysis. Then, the parameter estimation for parametric models is presented with a focus on the method of Least Squares, followed by some of its most prominent modifications. Issues such as parameter estimation for time-variant processes, parameter estimation in closed-loop, parameter estimation for differential equations, continuous time processes and efficient implementations of the algorithms are discussed. The different methods are compared and an outlook is given on non-linear system identification methods, such as neural networks and look-up tables.

Real experimental data are given on CD-ROM, allowing to test many of the methods presented in the book with real measurements. Powerpoint slides for a 12-14 week graduate level course can be made available to teachers

About this title

From the Back Cover:

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, machine tools, industrial robots, pumps, vehicles 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 nonparametric 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.

About this edition

• ISBN 10: 354012635X
• ISBN 13: 9783540126355
• Binding: Hardcover