The emergence of fuzzy logic and its applications has dramatically changed the face of industrial control engineering. Over the last two decades, fuzzy logic has allowed control engineers to meet and overcome the challenges of developing effective controllers for increasingly complex systems with poorly defined dynamics. Today's engineers need a working knowledge of the principles and techniques of fuzzy logic-Intelligent Control provides it.
The author first introduces the traditional control techniques and contrasts them with intelligent control. He then presents several methods of representing and processing knowledge and introduces fuzzy logic as one such method. He highlights the advantages of fuzzy logic over other techniques, indicates its limitations, and describes in detail a hierarchical control structure appropriate for use in intelligent control systems. He introduces a variety of applications, most in the areas of robotics and mechatronics but with others including air conditioning and process/production control. One appendix provides discussion of some advanced analytical concepts of fuzzy logic, another describes a commercially available software system for developing fuzzy logic application.
Intelligent Control is filled with worked examples, exercises, problems, and references. No prior knowledge of the subject nor advanced mathematics are needed to comprehend much of the book, making it well-suited as a senior undergraduate or first-year graduate text and a convenient reference tool for practicing professionals.
Introduction
Conventional Control Techniques
Summary
Problems
References
KNOWLEDGE REPRESENTATION AND PROCESSING
Introduction
Knowledge and Intelligence
Logic
Semantic Networks
Frames
Production Systems
Summary
Problems
References
FUNDAMENTALS OF FUZZY LOGIC
Introduction
Fuzzy Sets
Fuzzy Logic Operations
Some Definitions
Fuzzy Relations
Composition and Inference
Membership Function Estimation
Summary
Problems
References
FUZZY LOGIC CONTROL
Introduction
Basics of Fuzzy Control
Decision Making with Crisp Measurements
Defuzzification
Architectures of Fuzzy Control
Summary
Problems
References
KNOWLEDGE-BASED TUNING
Introduction
Theoretical Background
Analytical Framework
Computational Efficiency
Dynamic Switching of Fuzzy Resolution
Illustrative Example
Summary
Problems
References
KNOWLEDGE-BASED CONTROL OF ROBOTS
Introduction
Robotic Control System
Application to Robots
In-Loop Direct Control
High-Level Fuzzy Control
Control Hierarchy
System Development
Servo Expert Development
Summary
Problems
References
SERVO MOTOR TUNING
Introduction
System Development
Results
Theory of Rule Base Decoupling
Experimental Illustration
Summary
Problems
References
HIERARCHICAL FUZZY CONTROL
Introduction
General Concepts
Hierarchical Model
Effect of Information Processing
Application in Process Control
Summary
Problems
References
INTELLIGENT RESTRUCTURING OF PRODUCTION SYSTEMS
Introduction
Theoretical Framework
Implementation Using a Blackboard Architecture
Case Study
Summary
Problems
References
FUTURE APPLICATIONS
Introduction
Intelligence in Automation
Intelligent Multiagent Control
Reconfigurable Autonomous Manipulators
Intelligent Fusion of Sensors and Actuators
Mechatronics Era
Conclusion
Problems
References
APPENDIX A: Further Topics on Fuzzy Logic
APPENDIX B: Software Tools for Fuzzy Logic Applications
Index
"de Silva's book excels as an introduction to the design and implementation of intelligent control systems based on fuzzy logic…a well-rounded and well-balanced blend of research results and industrial applications."
-F. Karray in IEEE Spectrum, October 1996
