Industrial Electronics Handbook

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Industrial Electronics Handbook
Industrial Electronics Handbook

by: J.David Irwin (Editor)

Topics include: backpropagating utility, elastic fuzzy logic, defuzzification neuron, neurocontrol designs, fuzzy aggregation connectives, dual subroutine, micromachined circuits, saliency method, visual stimulus image, reluctance step motor, load resonant converters, matrix tactile sensor, multifield variable, building latency, desired root location, membrane inductors, pressure sensor market, recognition accelerator, resonant switch converters, commutating groups, instantaneous power failure, discriminant variates, computational intelligence chapter, industrial electronic circuits, numerical array processor

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Expert systems

Neural networks

Soft computing

Evolutionary systems

Computational intelligence

Hybrid systems

Virtual reality

Asynchronous transfer mode technology

Micro systems technology

Multisensor fusion and integration

Fuzzy systems

From traditional topics that form the core of industrial electronics, to new and emerging concepts and technologies, The Industrial Electronics Handbook, in a single volume, has the field covered. Nowhere else will you find so much information on so many major topics in the field. For facts you need every day, and for discussions on topics you have only dreamed of, The Industrial Electronics Handbook is an ideal reference.


Table of Contents

PART I: FUNDAMENTALS OF INDUSTRIAL ELECTRONICS

Fundamental Supporting Technologies

Electronics

Digital Control Circuits

Computer Architecture

Signal Processing

Data Acquisition and Measurement Systems

Sensors

Measurement System Architecture

Power Electronics

Overview

Overview of Devices and Components

Converters

Motor Drives

Mains Disturbances

Electromagnetic Compatibility for Drives

Factory Communications

Evolution of Factory Communication

Open Systems Interconnection Basic Reference Model

Local Area Networks

The Manufacturing Automation Protocol (MAP)

Essential Communications Protocols

System Control

Control System Fundamentals

Modeling for System Control

Basic Feedback Concept

Stability Analysis

PID Control

Bode Diagram Method

Root Locus Method

Pole Placement Design

Smith Predictor Technique

Internal Model Control

Model Predictive Control

Dynamic Matrix Control

Disturbance Observation-Cancellation Technique

Phase-Lock-Loop Based Control

Variable Structure Control Technique

Digital Computation

Digital Control

Estimation and Identification

Fuzzy Logic Based Control

Neural Network Based Control

Programmable Logic Controller (PLC)

Adaptive Control

Hardware Compensating Networks

m Synthesis and Analysis

Factory Automation

An Overview of Factory Automation

Types of Automated Manufacturing Systems

Production Management Architecture

Production Management Techniques

Automated Manufacturing System Development Methodology

Hybrid Systems and Control

Virtual Manufacturing Environment

Signal Processing for Factory Production Line

Robots

PART II: INTELLIGENT ELECTRONICS AND EMERGING TECHNOLOGIES

Expert Systems and Neural Networks

Current Applications of Expert Systems in Industrial Electronics

Expert Systems Methodology

Expert Systems and Their Use in Complex Engineering Systems

Current Trends in Neural Networks for Industrial Electronics

The Basic Ideas in Neural Networks

Neural Networks on a Chip

Commercially Available Neural Network Chips

Implementing Neural Networks in Silicon

An Avionics Application: MIMD Neural Network Processor

From Backpropagation to Neurocontrol

CMAC Architecture for Color Correction

Temporal Signal Processing

Feature Selection for Pattern Recognition Using Multilayer Perceptrons

Wavelets for Pattern Recognition: Wavelet Based Segmentation and Resistive Grid Averaging for Local Feature Extraction

Fractals for Pattern Recognition: A PDP Approach to Localized Fractal Dimension Computation with Segmentation Boundaries

Multilayer Perceptron with ALOPEX and Backpropagation

Supervised Neural Networks for Handwritten Digit Recognition in Industrial Processing

Neocognition

Studies of Pattern Recognition with Self-Learning Layered Neural Networks

Analog 3-D Neuroprocessor for Fast Frame Focal Plane Image Processing

Simulated Annealing, Boltzmann Machine, and Hardware Annealing

Radial Basis Function (RBF) Neural Networks

Hardware Implemented Radial Basis Function (RBF): The IBM Zero Instruction Set

The RCE Neural Network

Probabilistic Neural Networks Model

General Regression Neural Networks Model

On Classifiers: An Overview

Fuzzy Systems and Soft Computing

Applications of Fuzzy Systems and Soft Computing for Industrial Electronics

Fuzzy Numbers: The Application of Fuzzy Algebra to Safety and Risk Analysis

Fuzzy Systems

Fuzzy Hardware

Fuzzy Modeling and Applications: Controls, Vision, Decisions

Fuzzy Logic Control: Basics and Applications

Development of an Intelligent Unmanned Helicopter Based on Fuzzy Systems

Fuzzy/Neural Modeling

NeuFuz - A Combined Neural Net/Fuzzy Logic Tool

Neural Network Learning in Fuzzy Systems

Neurocontrol and Elastic Fuzzy Logic: Capabilities, Concepts, and Applications

Integrated Health Monitoring and Control in Rotocraft Machines

Autonomous Neural Control in Flexible Space Structures

Fuzzy Pattern Recognition

Neural Fuzzy Systems in Handwritten Digit Recognition

Fuzzy Algorithms for Learning Vector Quantization

Adaptive Resonance Theory

Future Directions for Fuzzy Systems and Soft Computing in Industrial Electronics

Evolutionary Systems, Computational Intelligence, and Hybrid Systems Applications

Applications of Evolutionary Systems for Industrial Electronics

Evolutionary Computation

Genetic Algorithms

Fuzzy Evolutionary/GA Systems

Information Fusion by Fuzzy Set Operations and Genetic Algorithms

Neural Evolutionary/GA Systems and Applications

Computational Intelligence Applications in Industrial Electronics

Hybrid Artificial Intelligence Systems

Application Techniques (Combining Fuzzy Logic, Artificial Neural Networks, and Probabilistic Reasoning: Soft Computing)

Synthesis of Fuzzy, Artificial Intelligence, Neural Networks, and Genetic Algorithm for Hierarchical Intelligence Control Top-Down and Bottom-Up Hybrid Method

Advanced Tools for Adaptive Nonlinear Modeling and Control of Power in Large Systems

Application of Model Reference Adaptive Control and Adaptive Time-Delay RBF Networks

Emerging Technologies

Current Applications in Virtual Reality

Micro-Electro-Mechanical System (MEMS)

Multisensor Fusion and Integration for Intelligent Systems

Index


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