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Intelligent Observer and Control Design for Nonlinear Systems

  • Book
  • © 2000

Overview

Editors:
  1. Dierk Schröder

    1. Institute for Electrical Drive Systems, Technical University of Munich, München, Germany

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  • Application-oriented monograph focussing on a novel and complex type of control systems
  • Written on an engineering level, including fundamentals, advanced methods and applications
  • The applied techniques originate from new methods like artificial intelligence, fuzzy logic, neural networks etc.

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Table of contents (13 chapters)

  1. Front Matter

    Pages I-XIII
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  2. Introduction — Control Aspects

    • Dierk Schröder
    Pages 1-18

  3. Motion Control

    • Dierk Schröder
    Pages 19-65

  4. Learning in Control Engineering

    • Ulrich Lenz
    Pages 67-81

  5. Neural Networks and Fuzzy Controllers as Nonlinear Function Approximators

    • Michael Beuschel
    Pages 83-103

  6. Systematic Intelligent Observer Design for Plants Characterized by an Isolated Nonlinearity

    • Ulrich Lenz
    Pages 105-134

  7. Identification of Separable Nonlinearities

    • Franz Hangl
    Pages 135-148

  8. Identification and Compensation of Friction

    • Thomas Frenz
    Pages 149-165

  9. Detection and Identification of Backlash

    • Dieter Strobl
    Pages 167-188

  10. Nonlinear Observer Structures for the Identification of Isolated Nonlinearities in Rolling Mills

    • Stephan Straub
    Pages 189-215

  11. Input-Output Linearization of Nonlinear Dynamical Systems: an Introduction

    • Kurt Fischle
    Pages 217-233

  12. Stable Model Reference Neurocontrol

    • Kurt Fischle
    Pages 235-254

  13. Dynamic Neural Network Compositions for Stable Identification of Nonlinear Systems with Known and Unknown Structures

    • Stephan Straub
    Pages 255-282

  14. Further Strategies for Nonlinear Control with Neural Networks

    • Martin Rau, Anne Angermann
    Pages 283-327

  15. Back Matter

    Pages 329-339
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Keywords

About this book

Control theory of nonlinear systems, in which either the linear part is known but the relevant nonlinearities in place, kind or parameters are unknown, or both the linear and the nonlinear parts are partially or even most unknown, is a new, demanding and highly interesting field. This book treats the problem by focussing on the role of learning. Intelligent learning techniques are able to determine the unknown components of nonlinear systems. These processes are always stable and convergent. The methods presented can be used both on-line and off-line. They have applications in mechatronics, hydraulics and combustion engines.

Editors and Affiliations

  • Institute for Electrical Drive Systems, Technical University of Munich, München, Germany

    Dierk Schröder

Bibliographic Information

  • Book Title: Intelligent Observer and Control Design for Nonlinear Systems

  • Editors: Dierk Schröder

  • DOI: https://doi.org/10.1007/978-3-662-04117-8

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2000

  • Hardcover ISBN: 978-3-540-63639-7Published: 18 November 1999

  • Softcover ISBN: 978-3-642-08346-4Published: 14 October 2010

  • eBook ISBN: 978-3-662-04117-8Published: 17 April 2013

  • Edition Number: 1

  • Number of Pages: XIII, 339

  • Topics: Control, Robotics, Mechatronics, Vibration, Dynamical Systems, Control, Systems Theory, Control

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