The industrial electronics handbook /
editor-in-chief, J. David Irwin.
- Boca Raton, Fla. : CRC Press, c1997.
- xxxvi, 1686 p. : ill. ; 29 cm.
- The electrical engineering handbook series .
Includes bibliographical references and index.
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
CONTRIBUTORS Kenneth Agehed Royal Institute of Technology (Sweden)
Marcelo Ang, Jr. National University of Singapore (Singapore)
Fumihito Arai Nagoya University (Japan)
Tamio Arai University of Tokyo (Japan)
Tom Baginski Auburn University
Vrej Barkhordarian International Rectifier Corporation El Segundo, California
Antal Bejczy Jet Propulsion Laboratory Califomia Institute of Technology