ISBN: 3790815470
TITLE: Soft Computing and Fractal Theory for Intelligent Manufacturing
AUTHOR: Castillo, Melin
TOC:

Preface V
Chapter 1 Introduction
Chapter 2 Type-l Fuzzy Logic 5
2.1 Type-l Fuzzy Set Theory 6
2.2 Fuzzy Rules and Fuzzy Reasoning 12
2.2.1 Fuzzy Relations 12
2.2.2 Fuzzy Rules 15
2.3 Fuzzy Inference Systems 18
2.4 Fuzzy Modelling 30
2.5 Summary 31
Chapter 3 Type-2 Fuzzy Logic 33
3.1 Type-2 Fuzzy Sets 34
3.2 Operations of Type-2 Fuzzy Sets 37
3.3 Type-2 Fuzzy Systems 39
3.3.1 Singleton Type-2 Fuzzy Logic Systems 40
3.3.2 Non-Singleton Fuzzy Logic Systems 44
3.3.3 Sugeno Type-2 Fuzzy Systems 45
3.4 Summary 46
Chapter 4 Supervised Learning Neural Networks 47
4.1 Backpropagation for Feedforward Networks 48
4.1.1 The Backpropagation Learning Algorithm 48
4.1.2 Backpropagation Multilayer Perceptrons 51
4.1.3 Methods for Speeding up Backpropagation 57
4.2 Radial Basis Function Networks 59
4.3 Adaptive Neuro-Fuzzy Inference Systems 64
4.3.1 ANFIS Architecture 64
4.3.2 Learning Algorithm 67
4.4 Summary 73
Chapter 5 Unsupervised Learning Neural Networks 75
5.1 Competitive Learning Networks 75
5.2 Kohonen Self-Organizing Networks 80
5.3 Learning Vector Quantization 85
5.4 The Hopfield Network 89
5.5 Summary 92
Chapter 6 Genetic Algorithms and Simulated Annealing 93
6.1 Genetic Algorithms 95
6.2 Modifications to Genetic Algorithms 102
6.2.1 Chromosome Representation 102
6.2.2 Objective Function and Fitness 102
6.2.3 Selection Methods 104
6.2.4 Genetic Operations 105
6.2.5 Parallel Genetic Algorithm 106
6.3 Simulated Annealing 109
6.4 Applications of Genetic Algorithms 112
6.4.1 Evolving Neural Networks 113
6.4.1.1 Evolving Weights in a Fixed Network 113
6.4.1.2 Evolving Network Architectures 116
6.4.2 Evolving Fuzzy Systems 122
6.5 Summary 125
Chapter 7 Dynamical Systems Theory 127
7.1 Basic Concepts of Dynamical Systems 127
7.2 Controlling Chaos 132
7.2.1 Controlling Chaos through Feedback 138
7.2.1.1 Ott-Grebogi-Yorke Method 138
7.2.1.2 Pyragas's Control Methods 140
7.2.1.3 Controlling Chaos by Chaos 141
7.2.2 Controlling Chaos without Feedback 143
7.2.2.1 Control through Operating Conditions 143
7.2.2.2 Control by System Design 143
7.2.2.3 Taming Chaos 147
7.2.3 Method Selection 148
7.3 Summary 149
Chapter 8 Plant Monitoring and Diagnostics 151
8.1 Monitoring and Diagnosis 152
8.2 Fractal Dimension of a Geometrical Object 154
8.3 Fuzzy Estimation of the Fractal Dimension 157
8.4 Plant Monitoring with Fuzzy-Fractal Approach 158
8.5 Experimental Results 162
8.6 Summary 165
Chapter 9 Adaptive Control of Non-Linear Plants 167
9.1 Fundamental Adaptive Fuzzy Control Concept 168
9.2 Basic Concepts of Stepping Motors 171
9.2.1 Variable Reluctance Motors 172
9.2.2 Unipolar Motors 173
9.2.3 Bipolar Motors 174
9.2.4 Dynamics of the Stepping Motor 174
9.2.5 Control of the Stepping Motor 177
9.3 Fuzzy Logic Controller of the Stepping Motor 178
9.4 Hardware Implementation of ANFIS 180
9.5 Experimental Results 181
9.6 Summary 184
Chapter 10 Automated Quality Control in Sound Speaker Manufacturing 185
10.1 Introduction 185
10.2 Basic Concepts of Sound Speakers 186
10.2.1 Sound Basics 187
10.2.2 Making Sound 187
10.2.3 Chunks of the Frequency Range 190
10.2.4 Boxes of Sound 193
10.2.5 Alternative Speaker Designs 197
10.3 Description of the Problem 198
10.4 Fractal Dimension of a Sound Signal 200
10.5 Experimental Results 202
10.6 Summary 206
Chapter 11 Intelligent Manufacturing of Television Sets 207
11.1 Introduction 207
11.2 Imaging System of the Television Set 208
11.2.1 The Cathode Ray Tube 208
11.2.2 Phosphor 209
11.2.3 The Black-and-White TV Signal 211
11.2.4 Adding Color 213
11.3 Breeder Genetic Algorithm for Optimization 216
11.3.1 Genetic Algorithm for Optimization 217
11.4 Automated Electrical Tuning of Television Sets 218
11.5 Intelligent System for Control 221
11.6 Simulation Results 225
11.7 Summary 225
Chapter 12 Intelligent Manufacturing of Batteries 227
12.1 Intelligent Control of the Battery Charging Process 228
12.1.1 Problem Description 229
12.1.2 Fuzzy Method for Control 230
12.1.3 Neuro-Fuzzy Method for Control 232
12.1.4 Neuro-Fuzzy-Genetic Method for Control 234
12.2 Hardware Implementation of the Fuzzy Controller for the Charging Process 
236
12.2.1 Introduction 236
12.2.2 Fuzzy Control 237
12.2.3 Implementation of the Fuzzy Controller 246
12.2.4 Experimental Results 250
12.3 Automated Quality Control of Batteries 250
12.3.1 Introduction 251
12.3.2 Fuzzy Controller 253
12.3.3 Fuzzy Control Implementation 262
12.4 Summary 266
Bibliography 267
Index 281
END
