A Learner’s Guide to Fuzzy Logic Systems, Second Edition  book cover
SAVE
£3.40
1st Edition

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




  • Any relevant sales tax will be applied during the checkout process.
ISBN 9780429287831
Published June 21, 2019 by CRC Press
126 Pages 25 B/W Illustrations

FREE Standard Shipping

What are VitalSource eBooks?




Prices & shipping based on shipping country


Preview

Book Description

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.

Table of Contents

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

...
View More

Author(s)

Biography

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.