Fuzzy Algorithms for Control

  • H. B. Verbruggen
  • H.-J. Zimmermann
  • R. Babuška

Part of the International Series in Intelligent Technologies book series (ISIT, volume 14)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. The Position and State of the Art of Fuzzy Systems

    1. Front Matter
      Pages 1-1
    2. H. B. Verbruggen, P. M. Bruijn
      Pages 3-15
    3. D. Dubois, H. Prade, L. Ughetto
      Pages 17-57
    4. K.-E. Årzén, M. Johansson, R. Babuška
      Pages 59-81
    5. R. Babuška, M. Setnes
      Pages 83-106
  3. Design and Analysis Issues

    1. Front Matter
      Pages 109-109
    2. A. Ollero, F. Cuesta, J. P. Marin, A. García-Cerezo
      Pages 127-157
    3. J. M. Sousa, Uzay Kaymak, Henk B. Verbruggen
      Pages 159-183
    4. M. Setnes, V. Lacrose, A. Titli
      Pages 185-218
  4. Application of Fuzzy Systems

    1. Front Matter
      Pages 221-221
    2. H.-J. Zimmermann, J. Angstenberger, R. Weber
      Pages 223-242
    3. A. Ollero, G. Ulivi, F. Cuesta
      Pages 301-324
    4. G. Schram, M. A. Fernández-Montesinos, H. B. Verbruggen
      Pages 325-348
  5. Back Matter
    Pages 349-352

About this book

Introduction

Fuzzy Algorithms for Control gives an overview of the research results of a number of European research groups that are active and play a leading role in the field of fuzzy modeling and control. It contains 12 chapters divided into three parts.
Chapters in the first part address the position of fuzzy systems in control engineering and in the AI community. State-of-the-art surveys on fuzzy modeling and control are presented along with a critical assessment of the role of these methodologists in control engineering.
The second part is concerned with several analysis and design issues in fuzzy control systems. The analytical issues addressed include the algebraic representation of fuzzy models of different types, their approximation properties, and stability analysis of fuzzy control systems. Several design aspects are addressed, including performance specification for control systems in a fuzzy decision-making framework and complexity reduction in multivariable fuzzy systems.
In the third part of the book, a number of applications of fuzzy control are presented. It is shown that fuzzy control in combination with other techniques such as fuzzy data analysis is an effective approach to the control of modern processes which present many challenges for the design of control systems. One has to cope with problems such as process nonlinearity, time-varying characteristics for incomplete process knowledge. Examples of real-world industrial applications presented in this book are a blast furnace, a lime kiln and a solar plant. Other examples of challenging problems in which fuzzy logic plays an important role and which are included in this book are mobile robotics and aircraft control.
The aim of this book is to address both theoretical and practical subjects in a balanced way. It will therefore be useful for readers from the academic world and also from industry who want to apply fuzzy control in practice.

Keywords

algorithms artificial intelligence control engineering fuzzy logic fuzzy system

Editors and affiliations

  • H. B. Verbruggen
    • 1
  • H.-J. Zimmermann
    • 2
  • R. Babuška
    • 1
  1. 1.Delft University of TechnologyNetherlands
  2. 2.RWTH AachenAachenGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-011-4405-6
  • Copyright Information Kluwer Academic Publishers 1999
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-94-010-5893-3
  • Online ISBN 978-94-011-4405-6
  • Series Print ISSN 1382-3434
  • About this book
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