Fuzzy Logic with Engineering Applications, 4th Edition

✍ Scribed by Timothy J. Ross

• Publisher: Wiley
• Year: 2017
• Tongue: English
• Leaves: 583
• Edition: 4
• Category: Library

✦ Synopsis

The latest update on this popular textbook

The importance of concepts and methods based on fuzzy logic and fuzzy set theory has been rapidly growing since the early 1990s and all the indications are that this trend will continue in the foreseeable future. Fuzzy Logic with Engineering Applications, Fourth Edition is a new edition of the popular textbook with 15% of new and updated material. Updates have been made to most of the chapters and each chapter now includes new end-of-chapter problems.

Key features:

• New edition of the popular textbook with 15% of new and updated material.
• Includes new examples and end-of-chapter problems.
• Has been made more concise with the removal of out of date material.
• Covers applications of fuzzy logic to engineering and science.
• Accompanied by a website hosting a solutions manual and software.

The book is essential reading for graduates and senior undergraduate students in civil, chemical, mechanical and electrical engineering as wells as researchers and practitioners working with fuzzy logic in industry.

✦ Table of Contents

Title Page
Copyright
Contents
About the Author
Preface to the Fourth Edition
Chapter 1 Introduction
The Case for Imprecision
A Historical Perspective
The Utility of Fuzzy Systems
Limitations of Fuzzy Systems
The Illusion: Ignoring Uncertainty and Accuracy
Uncertainty and Information
Fuzzy Sets and Membership
Chance versus Fuzziness
Intuition of Uncertainty: Fuzzy versus Probability
Sets as Points in Hypercubes
Summary
References
Problems
Chapter 2 Classical Sets and Fuzzy Sets
Classical Sets
Operations on Classical Sets
Properties of Classical (Crisp) Sets
Mapping of Classical Sets to Functions
Fuzzy Sets
Fuzzy Set Operations
Properties of Fuzzy Sets
Alternative Fuzzy Set Operations
Summary
References
Problems
Chapter 3 Classical Relations and Fuzzy Relations
Cartesian Product
Crisp Relations
Cardinality of Crisp Relations
Operations on Crisp Relations
Properties of Crisp Relations
Composition
Fuzzy Relations
Cardinality of Fuzzy Relations
Operations on Fuzzy Relations
Properties of Fuzzy Relations
Fuzzy Cartesian Product and Composition
Tolerance and Equivalence Relations
Crisp Equivalence Relation
Crisp Tolerance Relation
Fuzzy Tolerance and Equivalence Relations
Value Assignments
Cosine Amplitude
Max–Min Method
Other Similarity Methods
Other Forms of the Composition Operation
Summary
References
Problems
Chapter 4 Properties of Membership Functions, Fuzzification, and Defuzzification
Features of the Membership Function
Various Forms
Fuzzification
Defuzzification to Crisp Sets
λ-Cuts for Fuzzy Relations
Defuzzification to Scalars
Summary
References
Problems
Chapter 5 Logic and Fuzzy Systems
Part I: Logic
Classical Logic
Tautologies
Contradictions
Equivalence
Exclusive Or and Exclusive Nor
Logical Proofs
Deductive Inferences
Fuzzy Logic
Approximate Reasoning
Other Forms of the Implication Operation
Part II: Fuzzy Systems
Natural Language
Linguistic Hedges
Fuzzy (Rule-Based) Systems
Aggregation of Fuzzy Rules
Graphical Techniques of Inference
Summary
References
Problems
Chapter 6 Historical Methods of Developing Membership Functions
Membership Value Assignments
Intuition
Inference
Rank Ordering
Neural Networks
Genetic Algorithms
Inductive Reasoning
Summary
References
Problems
Chapter 7 Automated Methods for Fuzzy Systems
Definitions
Batch Least Squares Algorithm
Recursive Least Squares Algorithm
Gradient Method
Clustering Method
Learning from Examples
Modified Learning from Examples
Summary
References
Problems
Chapter 8 Fuzzy Systems Simulation
Fuzzy Relational Equations
Nonlinear Simulation Using Fuzzy Systems
Fuzzy Associative Memories (FAMs)
Summary
References
Problems
Chapter 9 Decision Making with Fuzzy Information
Fuzzy Synthetic Evaluation
Fuzzy Ordering
Nontransitive Ranking
Preference and Consensus
Multiobjective Decision Making
Fuzzy Bayesian Decision Method
Decision Making under Fuzzy States and Fuzzy Actions
Example Summary
Summary
References
Problems
Chapter 10 Fuzzy Classification and Pattern Recognition
Fuzzy Classification
Classification by Equivalence Relations
Crisp Relations
Fuzzy Relations
Cluster Analysis
Cluster Validity
c-Means Clustering
Hard c-Means (HCM)
Fuzzy c-Means (FCM)
Fuzzy c-Means Algorithm
Classification Metric
Hardening the Fuzzy c-Partition
Similarity Relations from Clustering
Fuzzy Pattern Recognition
Single-Sample Identification
Multifeature Pattern Recognition
Summary
References
Problems
Chapter 11 Fuzzy Control Systems
Control System Design Problem
Control (Decision) Surface
Assumptions in a Fuzzy Control System Design
Simple Fuzzy Logic Controllers
Examples of Fuzzy Control System Design
Aircraft Landing Control Problem
Fuzzy Engineering Process Control
Classical Feedback Control
Classical PID Control
Fuzzy Control
Multi-Input, Multi-Output (MIMO) Control Systems
Fuzzy Statistical Process Control
Measurement Data: Traditional SPC
Plant Simulation
Establishing Fuzzy Membership Values
Attribute Data: Traditional SPC
Industrial Applications
Summary
References
Problems
Chapter 12 Applications of Fuzzy Systems Using Miscellaneous Models
Fuzzy Optimization
One-Dimensional Optimization
Fuzzy Cognitive Mapping
Concept Variables and Causal Relations
Paths and Cycles
Indirect Effect
Total Effect
Indeterminacy
Fuzzy Cognitive Maps
Adjacency Matrix
Threshold Function
Feedback
Min–Max Inference Approach
Genetically Evolved Fuzzy Cognitive Maps
Agent-Based Models
Fuzzy Arithmetic and the Extension Principle
Extension Principle
Crisp Functions, Mapping, and Relations
Functions of Fuzzy Sets: Extension Principle
Fuzzy Algebra
Fuzzy Arithmetic
Data Fusion
Kalman Filter in Data Fusion
Summary
References
Problems
Chapter 13 Monotone Measures: Belief, Plausibility, Probability, and Possibility
Monotone Measures
Belief and Plausibility
Evidence Theory
Probability Measures
Possibility and Necessity Measures
Possibility Distributions as Fuzzy Sets
Possibility Distributions Derived from Empirical Intervals
Deriving Possibility Distributions from Overlapping Intervals
Redistributing Weight from Nonconsonant to Consonant Intervals
Comparison of Possibility Theory and Probability Theory
Summary
References
Problems
Index
EULA

✦ Subjects

Technology & Engineering, Electrical, Mechanical