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Fuzzy Algorithms for Control book cover, ISBN 9780792384618

Fuzzy Algorithms for Control

by Verbruggen, H. B.; Zimmermann, H. J.; Babuska, Robert

ISBN13: 9780792384618
ISBN10: 079238461X
eBook ISBN(s): 9789401144056
Format: Hardcover
Copyright: 1999-03-01
Publisher: Kluwer Academic Pub

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Summary

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.

Table of Contents

Preface

ix

Part I THE POSITION AND STATE OF THE ART OF FUZZY SYSTEMS

3

(108)

1 Fuzzy Systems in Control Engineering

3

(14)

H.B. Verbruggen

P.M. Bruijn

1.1 Introduction

3

(1)

1.2 Control engineering: solutions and limitations

4

(3)

1.3 Advanced control

7

(2)

1.4 Fuzzy control

9

(3)

1.5 Misunderstandings and possibilities

12

(2)

1.6 Conclusions

14

(1)

References

14

(3)

2 Fuzzy Logic, Control Engineering and Artificial Intelligence

17

(42)

D. Dubois

H. Prade

L. Ughetto

2.1 Introduction

17

(3)

2.2 Background on approximate reasoning

20

(8)

2.3 Approximate reasoning vs. fuzzy logic controllers

28

(14)

2.4 Validation of fuzzy rule bases

42

(4)

2.5 Interpolation with fuzzy rules

46

(7)

2.6 Conclusions

53

(1)

References

54

(5)

3 Fuzzy Control Versus Conventional Control

59

(24)

K.-E. Arzen

M. Johansson

R. Babuska

3.1 Introduction

59

(1)

3.2 Fuzzy control systems

60

(6)

3.3 Industrial fuzzy control

66

(2)

3.4 Modern nonlinear fuzzy control

68

(10)

3.5 Summary

78

(1)

References

78

(5)

4 Data-Driven Construction of Transparent Fuzzy Models

83

(28)

R. Babuska

M. Setnes

4.1 Introduction

83

(3)

4.2 Fuzzy model structure

86

(1)

4.3 Fuzzy clustering

87

(3)

4.4 Extraction of an initial rule base

90

(2)

4.5 Simplification and reduction of the rule base

92

(3)

4.6 Example: Fuzzy modeling and control of an HVAC System

95

(8)

4.7 Conclusions

103

(1)

References

104

(7)

Part II DESIGN AND ANALYSIS ISSUES

111

(112)

5 Fuzzy Logic Normal Forms for Control Law Representation

111

(16)

I. Perfilieva

5.1 Introduction

111

(2)

5.2 Fuzzy logic control models and their normal forms

113

(4)

5.3 Functional realization of normal forms

117

(2)

5.4 Approximation and representation of real-valued real continuous functions

119

(4)

5.5 Conclusions

123

(1)

Appendix: Proof of Theorem 2

124

(1)

References

125

(2)

6 Stability Analysis of Fuzzy Control Loops

127

(32)

A. Ollero

J.P. Marin

A. Garcia-Cerezo

R. Cuesta

6.1 Introduction

127

(1)

6.2 Fuzzy control engineering practice and stability

128

(8)

6.3 Input-output methods for stability analysis

136

(6)

6.4 Lyapunov approaches

142

(11)

6.5 Conclusions and perspectives

153

(1)

References

154

(5)

7 Performance Criteria: Classical and Fuzzy Design

159

(26)

J. M. Sousa

U. Kaymak

H.B. Verbruggen

7.1 Introduction

159

(3)

7.2 Design specifications

162

(3)

7.3 Classical performance specifications

165

(3)

7.4 Classical performance criteria

168

(4)

7.5 Fuzzy performance criteria

172

(2)

7 6 Fuzzy performance criteria in model-based predictive control

174

(7)

7.7 Summary and suggestions for further research

181

(1)

References

182

(3)

8 Complexity Reduction Methods for Fuzzy Systems

185

(38)

M. Setnes

V. Lacrose

A. Titli

8.1 Introduction

185

(1)

8.2 Elimination and selection

186

(10)

8.3 Rule base simplification

196

(6)

8.4 Dimensionality reduction

202

(9)

8.5 Structured systems

211

(3)

8.6 Concluding remarks

214

(2)

References

216

(7)

Part III APPLICATION OF FUZZY SYSTEMS

223

9 Intelligent Data Analysis and Fuzzy Control

223

H.- J. Zimmermann

L. Angstenberger

R. Weber

9.1 Basic principles of data analysis

223

(2)

9.2 Methods for fuzzy data analysis

225

(6)

9.3 Tools for data analysis

231

(3)

9.4 Fuzzy data analysis and fuzzy control

234

(2)

9.5 Industrial applications

236

(5)

9.6 Conclusions

241

(1)

References

241

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