Identification of Dynamic Systems

An Introduction with Applications

  • Rolf Isermann
  • Marco Münchhof

Table of contents

  1. Front Matter
    Pages i-xxv
  2. Rolf Isermann, Marco Münchhof
    Pages 1-32
  3. Identification of Non-Parametric Models in The Frequency Domain — Continuous Time Signals

    1. Front Matter
      Pages 75-75
    2. Rolf Isermann, Marco Münchhof
      Pages 77-98
    3. Rolf Isermann, Marco Münchhof
      Pages 99-120
    4. Rolf Isermann, Marco Münchhof
      Pages 121-145
  4. Identification of Non-Parametric Models with Correlation Analysis — Continuous and Discrete Time

    1. Front Matter
      Pages 147-147
    2. Rolf Isermann, Marco Münchhof
      Pages 149-178
    3. Rolf Isermann, Marco Münchhof
      Pages 179-200
  5. Identification with Parametric Models — Discrete Time Signals

    1. Front Matter
      Pages 201-201
    2. Rolf Isermann, Marco Münchhof
      Pages 203-221
    3. Rolf Isermann, Marco Münchhof
      Pages 223-290
    4. Rolf Isermann, Marco Münchhof
      Pages 291-318
    5. Rolf Isermann, Marco Münchhof
      Pages 319-333
    6. Rolf Isermann, Marco Münchhof
      Pages 335-351
    7. Rolf Isermann, Marco Münchhof
      Pages 353-366
  6. Identification with Parametric Models — Continuous Time Signals

    1. Front Matter
      Pages 367-367
    2. Rolf Isermann, Marco Münchhof
      Pages 369-377

About this book

Introduction

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.

Keywords

Frequency Response Linear Systems Nonlinear Systems Parameter Estimation System Identification

Authors and affiliations

  • Rolf Isermann
    • 1
  • Marco Münchhof
    • 2
  1. 1.Inst. Automatisierungstechnik, FG Regelungstechnik undTU DarmstadtDarmstadtGermany
  2. 2.Inst. AutomatisierungstechnikTU DarmstadtDarmstadtGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-78879-9
  • Copyright Information Springer-Verlag Berlin Heidelberg 2011
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-78878-2
  • Online ISBN 978-3-540-78879-9
  • About this book