A Learner's Guide to Fuzzy Logic Systems, Second Edition

This book presents an introductory coverage of fuzzy logic, including basic principles from an interdisciplinary perspective. It includes concept of evolving a fuzzy set and fuzzy set operations, fuzzification rule base design and defuzzification and simple guidelines for fuzzy sets design and selected applications. Les mer
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Om boka

This book presents an introductory coverage of fuzzy logic, including basic principles from an interdisciplinary perspective. It includes concept of evolving a fuzzy set and fuzzy set operations, fuzzification rule base design and defuzzification and simple guidelines for fuzzy sets design and selected applications. Preliminary concepts of Neural Networks and Genetic Algorithm are added features with relevant examples and exercises. It is primarily intended for undergraduate and postgraduate students and researchers to facilitate education in the ever-increasing field of fuzzy logic as medium between human intelligence and machine.

Fakta

Innholdsfortegnelse

Chapter-1


Unravelling Uncertainty through simple examples













1.1 Introduction
















1.2 Examples
















1.3 A simple view of fuzzy logic
















1.4 Learning ability
















1.5 Different phases of uncertainty
















1.6 Probability and uncertainty
















1.7 Conclusion


1.8 Questions





Chapter-2


Fuzzy Sets


2.1 Introduction


2.2 Classical Sets (Crisp Sets)


2.3 Concept of a Fuzzy Set


2.4 Basic Properties and Characteristics of Fuzzy Sets


2.5 Fuzzy Set Operations


2.6 Conclusion


Questions


Chapter 3


Fuzzy Reasoning


3.1 Introduction


3.2 A Conventional Control System


3.3 Major Components of a Fuzzy Logic System


3.4 Fuzzification


3.5 Inference Engine


3.6 Conclusion


Questions





Chapter-4


Design Aspects of Fuzzy Systems


4.1 introduction


4.2 A few Suggestions on Fuzzy System Design


4.3 Extracting Information from Knowledge Engineer


4.4 Adaptive Fuzzy Control


4.5 Rule Base Design Using Dynamic Response Analysis


4.6 Fuzzy Decision-Making


4.7 Neuro-Fuzzy Systems


4.8 Fuzzy Genetic Algorithms


4.9 Fuzzy Logic for Genetic Algorithms


4.10 DC Motor Speed Control Using Fuzzy Logic Principle


4.11 Fuzzy Logic-Based Washing Machine


4.12 Conclusion

Om forfatteren

Dr. K. Sundareswaran, obtained his M.Tech. (Hons.) in power electronics from the university of Calicut, and Ph.D. from Bharathidasan University, Tiruchirappalli. He is currently working as Professor in the department of Electrical and electronics Engineering, National Institute of Technology, Tiruchirappalli.


From 2005 to 2006, he was a Professor with the Department of Electrical Engineering, National Institute of Technology, Calicut, Kerala, India. He is currently a Professor with the Department of Electrical and Electronics Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India. His research interests include power electronics, renewable energy systems, and biologically inspired optimization techniques.