INDUSTRIAL APPLICATIONS OF FUZZY LOGIC AND INTELLIGENT SYSTEMS
Edited by
John Yen, Reza Langari and Lotfi A. Zadeh
With a special emphasis on real functioning systems, this edited volume written
by leading researchers from Japan, the United States, and Europe - co-edited by
Lotfi A. Zadeh - brings you a functional understanding of the industrial
applications of fuzzy logic in one self-contained volume. Application areas
covered range from sensors, motors, robotics, and autonomous vehicles to
process control and consumer products.
Key Features include:
* An introduction to fuzzy logic and its application in control
engineering
* Applications of fuzzy logic to supervisory control
* Tools and developement environments for fuzzy control
* The history of the developement of fuzzy control applications in Japan
* A survey of fuzzy logic applications in Europe
* Novel applications such as hardware implementation of fuzzy control
systems
Especially suitable for industrial practitioners who want to explore the real
world of fuzzy and intelligent systems applications, this book addresses the
broad range of potential uses of fuzzy logic. The many success stories contained
in the book about fuzzy logic applications offer valuble insights into suitable
usage as well as the practical benefits of this emerging technology.
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Ordering Information
INDUSTRIAL APPLICATIONS OF FUZZY LOGIC AND INTELLIGENT SYSTEMS
Edited by
John Yen, Reza Langari and Lotfi A. Zadeh
Published by
IEEE Press
$64.95 ($52.00 member)
April 1995
Hardcover 352pp
IEEE Order No. PC4002
ISBN: 0-7803-1048-9
For orders please contact:
IEEE PRESS Marketing
Attn: Special Sales
PO Box 1331
445 Hoes Lane
Piscataway, NJ 08855-1331
Fax : (908)981-8062
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>From the foreword by H.-J. Zimmermann:
``Each chapter is authored by researchers who not only have international
reputations in fuzzy technology but also have been personally involved in the
developement and application of the technology. From the broad spectrum of the
applications of fuzzy technology, those that are best known in the engineering
professions are highlighted: fuzzy control, consumer products, robotics, and
sensors. These topics have been supplemented by important and recent
developements, such as the combination of conventional contollers with fuzzy
contollers and the common applications of both fuzzy technology and neural
networks technology.
With readers that are not entirely familiar with fuzzy set theory in mind, the
editors have also included an introductory chapter on fuzzy logic control.
Altogether, this book is an excellent combination of basic introductory theory,
interesting applications, and historical surveys.''
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CONTENTS
Foreword (by H.-J. Zimmermann)
Preface (by J. Yen, R. Langari, and L. A. Zadeh)
PART 1 - BASICS OF FUZZY LOGIC
Chapter 1 Introduction to Fuzzy Logic Control,
R. Langari and J. Yen
1.1 Introduction
1.2 Applications of Fuzzy Logic
1.2.1 Modus Operandi of Fuzzy Logic
1.3 Fuzzy versus Classical Set Theory
1.3.1 Problematic Cases of Classical Sets
1.3.2 Implications in Decision and Control Problems
1.3.3 Fuzzy Sets
1.3.4 Continuous versus Discrete Universe of Disclosure
1.3.5 Algebraic Description of Fuzzy Sets
1.3.6 Term Sets or Vocabularies
1.3.7 Linguistic Hedges
1.3.8 Complement of a Fuzzy Set
1.3.9 Conjunction and Disjunction of Fuzzy Sets
1.3.10 Linguistic Variable
1.3.11 Possibility Distribution
1.4 Fuzzy Logic
1.4.1 Representation of Rules
1.4.2 Inference as Composition of Relations
1.4.3 Inference with Multiple Rules
1.5 Fuzzy Logic and its Role in Control Engineering
1.6 Paradigm for Fuzzy Control
1.7 Fuzzy Control Design
1.8 Rationale and Merits of Fuzzy Control
1.9 Conclusions
References
Bibliography
PART 2 - FUZZY LOGIC APPLICATIONS IN JAPAN
Chapter 2 History of Industrial Applications
of Fuzzy Logic in Japan, K. Hirota
2.1 Beginning of Fuzzy Research in Japan
2.2 Activities in IFSA Japan Charter
2.3 Industrial Applications and the First Fuzzy Vogue
2.4 Two Big National Fuzzy Research Projects
2.5 Japan Society for Fuzzy Theory and Systems
2.6 Fuzzy Home Electronics and the Second Fuzzy Vogue
2.7 Toward a Prosperous Fuzzy Society
Chapter 3 Fuzzy Logic Applications at OMRON
Corporation, S. Isaka
3.1 Introduction
3.2 Temperature Controller
3.2.1 Introduction
3.2.2 Controller Structure
3.2.3 Control Parameter Tuning
3.2.4 Results
3.3 Health Management System (HMS)
3.3.1 Introduction
3.3.2 System Organization
3.3.3 Halth-Management Concept
3.4 Conclusions
References
Chapter 4 Survey of Fuzzy Logic Applications
in Image-Processing Equipment, H. Takagi
4.1 Introduction
4.2 Cameras
4.2.1 Canon: Autofocus
4.2.2 Minolta: Autofocus, Autoexposure, and Autozoom
4.3 Camcorders
4.3.1 Sanyo: Aufocus, Autoexposure, and Auto-White-
Balancing
4.3.2 Canon: Autofocus System for Camcorders
4.3.3 Matsushita Electric: Image Stabilization for Camcorders
4.4 Photocopying Machines
4.4.1 Canon: Electrophotography Process
4.4.2 Ricoh: Electrophotography Process
4.4.3 Sanyo: Toner Supply Contol
4.4.4 Matsushita: Autoexposure and Toner Control
4.4.5 Sanyo: Color Copying
4.5 Television Equipment
4.5.1 Sanyo: Television Sets
4.5.2 Others
4.6 Codecs
4.7 Stepper Alignment in Semiconductor Manufacturing
4.8 Conclusions
Acknowledgments
References
Chapter 5 Applications of Neural Networks
and Fuzzy Logic to Consumer Products, H. Takagi
5.1 Introduction
5.1.1 Fuzzy Systems
5.1.2 Combining Fuzzy Technology with Neural Networks
5.1.3 Issues in Consumer Product Design
5.2 Types of Applications
5.3 Application I: Non-Consumer-Trainable Applications
5.3.1 Developement Tools
5.3.2 Independence of Fuzzy Logic
5.3.3 Correcting Mechanisms
5.3.4 Cascade Combination
5.4 Application II: Consumer-Trainable Neural Nets
5.4.1 Reducing Preheating Time
5.4.2 Correction According to Personal Preference
5.4.3 Adjusting the Control Program to the User's
Environment
5.4.4 Predicting Precooling Time
5.5 Towards Future Systems
References
Chapter 6 Knowledge Processing Based on Fuzzy
Associative Memory and its Application
to a Helicopter Control, T. Takagi, T. Yamaguchi,
and S. Yamamoto
6.1 Introduction
6.2 Fuzzy Associative Memory-Based Knowledge Processing
6.2.1 FAMOUS
6.2.2 Conceptual Fuzzy Sets
6.2.3 Features of Fuzzy Associative Memory-Based
Knowledge Processing
6.3 The Flying Vehicle System
6.3.1 The Experimental System
6.3.2 Two-Degree-of-Freedom Fuzzy Model for Flight
6.3.3 Hovering Flight by Means of the SFK
6.3.4 Circular Flight Using DFK
6.4 Conclusions
References
PART 3 - FUZZY LOGIC APPLICATIONS IN THE UNITED STATES
Chapter 7 Fuzzy Logic Hierarchical Contoller
for a Recuperative Turboshaft Engine: Form Mode
Selection to Mode Modeling, P. P. Bonissone
and K. H. Chiang
7.1 Introduction
7.2 The Gas Turbine
7.2.1 Plant
7.2.2 Control Strategies
7.2.3 The Current Control Scheme
7.3 The Fuzzy Logic Mode Selector
7.3.1 Controls and Fuzzy Logic
7.3.2 Mode Selector Implementation
7.3.3 Tuning
7.4 The Fuzzy Logic Low-Level Controllers
7.4.1 Conventional PI Controllers
7.4.2 Fuzzy Logic PI Controllers
7.4.3 Two-Dimensional Sliding Mode Controllers
7.4.4 Implementation
7.5 Conclusions
References
Chapter 8 Progress in Research on Autonomous
Vehicle Motion Planning, E. H. Ruspini, A. Saffiotti,
and K. Konolige
8.1 Introduction
8.2 Motion COntrol
8.3 Task Execution
8.4 Self-Localization
8.5 Experiments
8.6 Conclusions
Acknowledgments
References
Chapter 9 Autonomous Navigation of a Mobile
Robot Using Behaviorist Theory and VLSI Fuzzy
Inference Chips, F. G. Pin and H. Watanabe
9.1 Introduction
9.2 The VLSI Fuzzy Inferencing System
9.3 Building Fuzzy Behaviors and Rule Bases
9.4 Experiments and Sample Results
9.5 Conclusions
References
Chapter 10 Artificial Intelligence, Fuzzy Logic,
and Sensor Clusters, M. AbdelRahman
10.1 Background
10.2 Enter Artificial Intelligence
10.2.1 Knowledge-Based Systems (KBSs)
10.2.2 Artificial Neural Systems (ANSs)
10.2.3 Fuzzy Logic
10.3 New Sensor Products with Fuzzy Logic Rules
10.3.1 Color Sensor
10.4 Sensor Clusters and Food Processing
10.5 Conclusions
Chapter 11 Intelligent Sensor Systems for Space
Operations, R. N. Lea and Y. Jani
11.1 Introduction
11.2 Tracking Control for Proximity Operations
11.3 Designs of Fuzzy Logic Based Controllers
11.4 Test Cases for Proximity Operations
11.5 Results from Software Simulations
11.6 Conclusions
References
Chapter 12 Two Automated Tuning Methods
for Fuzzy Logic-Based Process Control, J. Yen,
W. C. Daugherity, H. Wang, and B. Rathakrishnan
12.1 Introduction
12.1.1 Motivations
12.1.2 Two Automated Tuning Methods
12.2 Description of the Plant
12.3 Automated Tuning Using Fuzzy Meta-Rules
12.4 Automated Tuning Using Reinforcement-Based
Self-Learning
12.4.1 Description
12.4.2 Design Issues
12.4.3 Learning Rules
12.5 Evaluation
12.5.1 Results of Meta-Rule_Based Automatic Tuning
12.5.2 Results of Reinforcement Based Tuning
12.5.3 Discussion
12.6 Conclusions
Acknowledgments
References
Chapter 13 On Fuzzy Control
of Nonchlorofluorocarbon Air-Conditioning Systems,
M. Jamshidi
13.1 Introduction
13.2 Thermoelectric Cells and System Design
13.3 Fuzzy Logic
13.4 Software Simulations of Fuzzy Controllers
13.4.1 A Togai Fuzzy_C Simulation
13.4.2 The NeuraLogix Fuzzy Microcontoller Simulation
13.5 Hardware Implementation
13.6 Conclusions
Acknowledgments
References
PART 4 - FUZZY LOGIC APPLICATIONS IN EUROPE
Chapter 14 Fuzzy Logic Applications in Europe,
C. von Altrock
14.1 History of Fuzzy Logic Applications in Europe
14.1.1 1974: First Control Applications in Europe
14.1.2 1978: Fuzzy Logic in Japan
14.1.3 1982: First Decision Support Applications in Europe
14.1.4 1988: Japanese Fuzzy Products Reach Europe
14.1.5 1990: Fuzzy Logic Awareness in Europe
14.2 A Survey of Fuzzy Logic Applications in Europe
14.2.1 Areas of Fuzzy Logic Applications
14.2.2 Complexity of the Fuzzy Logic Systems
14.2.3 Companies Experiences with Fuzzy Logic
14.3 Case Studies
14.3.1 Fuzzy European Home Appliances
14.3.2 Intelligent NiCd Battery Charger
14.3.2 Fuzzy Data Analysis in Fire Detectors
14.3.4 Fuzzy Logic State Estimation for a Home Heating
System
14.3.5 Industrial Sensors Using Fuzzy Logic
14.3.6 Fuzzy Logic in Automotive Engineering
14.3.7 Robotic Applications in Europe
14.3.8 Test Stand Automation
14.3.9 Crane Control Using Fuzzy Logic
14.3.10 Fuzzy Logic for Chemical Process Control
14.3.11 Robust Control of a Waste Incineration Plant
14.3.12 Wastewater Treatment Plant Control
14.4 Further Development
14.4.1 The Limiting Factor of Further Penetration: Education
14.4.2 Applications in Decision Support and Data Analysis
References
Bibliography
PART 5 - SURVEY OF TOOLS
Chapter 15 Software Tools for Fuzzy Control, S. Chiu
15.1 Introduction
15.2 CubiCalc
15.3 TILShell
15.4 fuzzyTech
15.5 FIDE (Fuzzy Inference Development Environment)
15.6 RT/Fuzzy (Real-Time Fuzzy Logic Block)
15.7 Fuzzy Knowledge Builder
15.8 Fuzz-C
15.9 Conclusions
15.10 Disclaimer
References
Company Addresses
INDEX
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