Fuzzy Reasoning in Information, Decision and Control Systems

1. Front Matter

   Pages I-xviii

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2. General Issues

   1. Front Matter

      Pages 1-1

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   2. Fuzzy Sets and Fuzzy Reasoning: An Introduction

      • S. G. Tzafestas, A. N. Venetsanopoulos, S. Terzakis

      Pages 3-29

   3. On The Validation of Fuzzy Knowledge Bases

      • Didier Dubois, Henri Prade

      Pages 31-49

   4. Software Representation of Fuzzy Sets and Logic

      • Sozo Yamamoto

      Pages 51-68

   5. Fuzzy Dynamic Systems: Analysis, Control and Identification

      • A. N. Venetsanopoulos, S. G. Tzafestas, S. Terzakis

      Pages 69-96

3. Neuro-Fuzzy Systems

   1. Front Matter

      Pages 97-97

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   2. Neural Net Applications in Fuzzy Systems

      • Hiroshi Kawamura, Akinori Tani

      Pages 99-119

   3. Neuro-Fuzzy Expert Systems: Overview with a Case Study

      • Sushmita Mitra, Sankar K. Pal

      Pages 121-143

   4. Fuzzy Reasoning Through A General Neural Network Model

      • S. G. Tzafestas, G. B. Stamou, K. Watanabe

      Pages 145-161

4. Fuzzy Controllers

   1. Front Matter

      Pages 163-163

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   2. Demystification of Fuzzy Control

      • R. Jager, H. B. Verbruggen, P. M. Bruijn

      Pages 165-197

   3. Analysis, Design, Implementation and Critical Appreciation of Fuzzy Logic Controller

      • Kumar S. Ray

      Pages 199-275

   4. Fuzzy Controller Design: A Sliding Mode Approach

      • Chung-Chun Kung, Sinn-Cheng Lin

      Pages 277-306

   5. Multivariable Fuzzy Sliding Mode Control by Using a Simplex of Control Vectors

      • Giorgio Bartolini, Antonella Ferrrara

      Pages 307-328

   6. Knowledge Representation and Information Processing in Intelligent Controllers

      • Kaoru Hirota, Witold Pedrycz

      Pages 329-343

5. Fuzzy Reasoning and Estimation Methodologies

   1. Front Matter

      Pages 345-345

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   2. Fuzzy Parameter and State Estimation

      • S. G. Tzafestas, S. Terzakis, A. N. Venetsanopoulos

      Pages 347-368

   3. A Fuzzy Reasoning Methodology for Rule-Based Systems

      • Shyi-Ming Chen

      Pages 369-386

   4. Computing the Multivalued Shape of a Pattern Class

      • Deba Prasad Mandal, C. A. Murthy

      Pages 387-418

Great progresses have been made in the application of fuzzy set theory and fuzzy logic. Most remarkable area of application is 'fuzzy control', where fuzzy logic was first applied to plant control systems and its use is expanding to consumer products. Most of fuzzy control systems uses fuzzy inference with max-min or max-product composition, similar to the algorithm that first used by Mamdani in 1970s. Some algorithms are developed to refine fuzzy controls systems but the main part of algorithm stays the same. Triggered by the success of fuzzy control systems, other ways of applying fuzzy set theory are also investigated. They are usually referred to as 'fuzzy expert sys­ tems', and their purpose are to combine the idea of fuzzy theory with AI based approach toward knowledge processing. These approaches can be more generally viewed as 'fuzzy information processing', that is to bring fuzzy idea into informa­ tion processing systems.

• Processing
• Software
• biomedical engineering
• control
• fuzzy logic
• information processing
• logic
• model
• network
• robot

• National Technical University of Athens School of Electrical and Computer Engine, Zografou, Athens, Greece

  S.G. Tzafestas

• University of Toronto Dept. Electrical & Computer Engineering, Toronto, Canada

  Anastasios N. Venetsanopoulos

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