**INDUSTRIAL ELECTRONICS**

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**Part-1 Fundamentals of industrial electronics **

Section-1 Supporting technologies

Electronics Darrell vines and tom baginski

Introduction

Diodes

Transistors as switches

Models for transistors

Analog and digital circuits

**2 Digital control circuits marc Courvoisier Michel combacan,and Mario paludetto**

Logic control

Sequence control

Implementation techniques

**3 Computer architecture victor p. nelson **

Hardware organization

Computer software

Imformation representation in digital computers

Specifying instruction operands

CPU registers

Memory organization

Computer instruction types

Interrupts and exceptions

Evaluating instruction set architectures

Computer system design

Input/output device interfaces

Microcontroller architectures

Multiple processor architectures

**4 Signal processing james A. heinen and Russell J. niederjohn **

Introduction

Continuous-time signals

Time-domain analysis of continuous-time signals

Frequency-domain analysis of continuous-time signals

Continuous-time signal processors

Time-domain analysis of continuous-time signal processors

Frequency-domain analysis of continuous-time signal processors

Continuous-time filters

Sampling

Discrete –time signals

Time-domain analysis of discrete-time signals

Frequency-domain analysis of discrete-time signals

Discrete-time signal processors

Time-domain analysis of discrete-time signal processors

Frequency-domain analysis of discrete-time signal processors

Discrete-time filters

Discrete-time analysis of continuous-time signals

Discrete-time processing of continuous-time signals

Section II data acquisition and measurement systems

**5 Sensors Charles W. einolf jr**

Introduction

Passive sensors

Active sensors

**6 Measurement system architecture **

Introduction Patrick L walter

System considerations Patrick L walter

Signal conditioning and filtering david Ryerson

Signal/data transmission components otis Solomon and William boyer

Software data correction William boyer and david Ryerson

Computers in instrumentation systems William boyer

Software for instrumentation systems William boyer

Calibration and testing Richard pettit

Digital signal processing belle upadhyaya

Signal pick-up and interface circuitry Thaddeus roppel

Thermal effects in industrial electronic circuits ray p reed

Lossless waveform compression giridhar mandyam, neeraj magotra Samuel D. stearns D streans ,Li-Zhe tan and wes McCoy

3-D measurement techniques Bernard C. jiang

Section III power electronics

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**7 Introduction to power electronics janos bencze **

Introduction

Power supplies

Electric drives

Application examples

Future trends

**8 Overview: devices and components Malay trivedi,sameer pendhakar, and Krishna shemai**

Introduction

Diode

Thyristor

Transistors

New devices

**9 Devices and components **

Power diodes imre ipsits

Power bipolar junction transistors imre ipsits

Passive networks karoly kurutz

**10 Power MOSFETs Vrej barkhordarian**

Introduction

Static characteristics

Dynamic characteristics

Applications

**11 Insulated gate bipolar transistors Michael robinson,Richard francis,ranadeep **

Introduction

Basic structure and operation

Design considerations

Requirement for anti-parallel diode

Comparison between the power MOSFET,IGBT, and MCT

IGBT data sheet parameters

Appendix: typical IGBT data sheet

**12 Conversion**

AC-DC converters Attila karpati

DC-DC converters istvan nagy

DC-AC conversion Attila karpati

AC-AC conversion sandor halasz

Resonant converters istvan nagy

**13 Motor drives **

Control systems and applications takamasa hori

DC motor control systems takamasa hori

Induction motor control systems takamasa hori, hiroshi nagase and mitsuyuki hombu

Synchronous motor control M.F. rahman and khiang-wee lim

Step motor drives Ronald H. brown

Servo drives Ronald H. brown

Servo drives sandor halasz

Switched reluctance motor drives jozsef borka

**14 Main disturbances **

Power quality James stanislawski

Reactive power and harmonics compensation Gerry heydt

New power converters Prasad enjeti

Uninterruptible power supplies laura steffek john hecklesmiller,dave layden,and brian young

**15 Electromagnetic compatibility for drives walt maslowski **

Compatibility: emissions and immunity

Section IV factory communications

**16 Evolution of factory communication W. timothy **

Point-to-point communications

Network communications

Advantages of network interconnection

Communications requirements for distributed systems

**17 Open systems interconnection basic reference model Robert M. Hines **

Introduction

Physical layer

Datalink layer

Network layer

Transport layer

Session layer

Presentation layer

Application layer

**18 Local area networks **

Ethernet and IEEE802.3 contention bus Alfred C. weaver

IEEE 802.5 token ring john W. sublet

IEEE 802.4 token bus Alfred C. weaver

Field bus jean-dominique decotignic

Fiber distributed data interface Robert W. Christie

Asynchronous transfer mode Curtis L mosffit

**19 Manufacturing automation protocol juan R. Pimentel **

History

Purpose

Description

Standards used

Example of use

**20 Essential communications protocols **

Datalink protocols Bert j. Dempsey

Network protocols debapriya sarkar

Transport layer protocols bert J. Dempsey

Section V system control

**21 Control system fundamentals A.S. hodel **

Modeling

Controller design

Intelligent control

Other control approaches

**22 Modeling for system control A john boye and William L. brogan **

Introduction

Analytical modeling

Defining the problem

Determining the system components

Writing the system equations

Verifying the model

Empirical or experimental modeling

**23 Basic feedback concept T.H Lee, C, C. hang and K. K tan **

Beneficial Effects of feedback

Analysis of design of feedback control systems

Implementation of feedback control systems

**24 Stability analysis N.K sinha **

Stability analysis for linear systems

Stability of linear time-invariant continuous-time systems

Stability of linear time-invariant discrete-time systems

Nonlinear systems

**25 PID control james C. hung **

Introduction

Classical PID control

Remarks

**26 Bode diagram method john parr **

Bode diagram analysis

Mathematical model determination

Correlation of frequency response and time response

Shaping the cutoff response

Compensator design

Design for digital systems

**27 The locus method Robert J. veillette and J. alexis de Abreu-Garcia**

Motivation and background

Root locus analysis

Compensator deisgn by root locus method

Examples

**28 Pole placement design Michael greene and victor trent **

Pole placement

State observation

Discrete implementation

**29 The smith predictor technique john Y. hung **

Background-control of processes having time delay

Basic principle of the smith predictor

A smith predictor design example

**30 Internal model controls james C. hung **

Basic IMC structures

IMC design

Discussion

**31 Model predictive control jay H. lee**

Overview

Applications

**32 Dynamic matrix control james C. hung **

The dynamic matrix

Output projection

Control computation

Remarks

**33 Disturbance observation-cancellation technique kouhei ohnishi **

Why estimate disturbance?

Plant and disturbance

Higher-order disturbance approximation

Disturbance observation

Disturbance cancellation

Examples of application

Conclusions

**34 Phase-locked loop-based control guan-chyun hsieh **

Introduction

Configurations of PLL applications

Analog, digital, and hybrid PLLs

Popular PLL integrated circuits

**35 Variable structure control technique vadim utkin **

Introduction

Mathematical aspects

Sliding mode control design

Chattering problem

Control of manipulators

Control of mobile robots

Control of railway wheel set

Control of torsion oscillations of a flexible shaft

DC motors

Control of DC motors based on a reduced-order model

Conclusion

**36 Digital computations James R. Rowland**

System response

Numerical integration formulas

Exact difference equations for linear systems

Summary

**37 Digital control john Y. hung and victor trent **

Introduction

Discretization of continuous-time systems

Discretization of the servomotor system

Frequency domain design through the w-transform

Root locus design on the unit circle

Simulation comparisons

**38 Estimation and identification Thomas S. denney Jr **

Kalman filters

Other types of kalman filters

Identification

**39 Fuzzy logic-based control Mo-yuen chow **

Introduction to intelligent control

DC motor Dynamics

Fuzzy control

Conclusion and future direction

**40 Neural network-based control dian-cheng zhang **

Control configuration

Design procedure

**41 Programmable logic control (PLC) Ernst dummermuth**

Basic concepts

Hardware components

PLC real-time operating systems

Software components

PLC communications

Selecting the right PLC

**42. Adaptive control Stephen T. hung **

Introduction

Update strategies

Direct adaptive control

Indirect adaptive control

Adaptive/self-tuning behavior

Summary

**43. Hardware compensating networks Royce d. harbor and Charles L. Philips **

Continuous compensation

Other compensation procedures

**44. Synthesis and analysis dan bugajski ,dale Enns mike Jackson , blaise morton **

Defining the interconnection structure

H-synthesis

u-analysis and D scales

D-K iteration

Changing weights

Compensator model reduction

Summary

Section VI Factory automation

**45 An overview of factory automation Richard zurawski **

Introduction

New technologies for factory automation

**46. Types of automated manufacturing systems Ljubisa vlacic,walter wong and Theodore J. Williams **

The hierarchical model presentation of manufacturing activities

Enterprise/factory integration

The methodology for CIE/CIM

Architectures of automated manufacturing systems

Implementations of factory automation systems

Flexible manufacturing systems

**47 Production management architecture Rakesh nagi and jean-marie proth **

Introduction

Production management in the sixties and beyond

Components of the hierarchical production management system

Long-term production plan

Master production scheduling

Capacity requirement planning

MRP philosophy

Application of the MRP

Conclusion

**48 Production management techniques upendra belhe and Andrew kusiak **

Material requirements planning

Manufacturing resource planning

Optimized production technology

Toyota system and just-in-time

The kanban concept

**49 Automated manufacturing system development methodology **

Analysis of foundational properties of specification and design models of industrial automated

Systems Richard zurawski and meng chu zhou

Automated manufacturing system design using analytical techniques sunderesh S. heragu and

Christopher M. Lucarelli

Discrete event simulation mengchu Zhou, Anthony D. robbi and Richard zurawski

**50. Hybrid systems and control tarek M.sobh**

Introduction

Discrete event and hybrid observation under uncertainty

Conclusions

**51. Virtual manufacturing environment Robert G. Wilhelm **

Introduction

Scope for virtual manufacturing

Typical applications

Emerging technology

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**52 Signal processing for factory production lines rokuya ishii **

Introduction

Examples of signal processing systems

**53 Robots **

Robots: qualities and capabilities ray Jarvis

Robot vision ray Jarvis

Ultrasonic sensors Lindsay kleeman

Robot tactile sensing R. Andrew Russell

A robotic sense of smell R. Andrew Russell

Actuators in robotics and automation systems Marcelo H. ang Jr. and choon-seng yee

Control fathi ghorbel

Mobile robots Miguel A. salichs,luis Moreno,diego gachet,arthuro de la escalera and juan R pimental

Teleperators antal k. bejczy

**Part-2 Intelligent electronics and emerging technologies **

**Section VII) Expert systems and neural networks**

**Expert systems **

**54 Current applications of expert systems in industrial electronics **

Mary lou Padgett and Robert Shelton

Emerging trends for systems in industrial electronics

Defining terms

Resources

**55 Expert systems methodology gary riley **

Capturing human expertise in a program

Rule-based programming

Truth table simplification program

**56 Expert systems and their use in complex engineering systems Robert E uhring and lefteri H. tsoukalas **

Introduction

Definition of expert systems

Characteristics of expert systems

Components of an expert system

Knowledge representation and inference

Uncertainty management

State of the art of expert systems

Use of expert systems

Potential implementation issues for expert systems

Legal aspects of expert systems

Use of expert systems in nuclear power plants

Neural networks

**57 Strategies and tactics for the application of neural networks to industrial mary lou Padgett, paul **

Werbos, and teuvo kohonen

Computational intelligence connections and future

Engineering intelligent electronics applications

Summary of basic modeling concepts

Applications

Future

Defining terms

Resources

**58 The basic ideas in neural networks david E. rumelhart ,Bernard widrow, and Michael lehr **

Introduction

Learning by example

Generalization

Hints for successful applications

**59 Neural networks on a chip Clifford lau **

Artificial neural network technology compared with conventional

Examples of chips

Comparisons of NN VLSI microchips

Applications of neural network technology

BMDO/IST demonstration project: 3-D ANN silicon neuron seeker

**60 Commercially available artificial neural network chips seth wolpert **

Introduction

Analog ANN products

Digital ANN products

Hybrid ANN products

Discussion

**61 Implementing neural networks in silicon seth wolpert and evangelia micheli-tznakou **

Introduction

The living neuron

Neurological process modeling

**62 An avionics application: MIMD neural network processor Richard saeks **

NNP architecture

Summary

**63 Backprogation to neurocontrol paul J. werbos **

Neurcontrol: where it is going and why it is crucial

**64 CMAC neural networks and color correction king- lung huang **

Introduction

High-order CMAC neural networks for color correction

Experimental result

Conclusion

**65 Temporal signal processing simon haykin **

Introduction

Temporal neural networks with observable states

Temporal neural networks with hidden states

Conclusions

**66 Feature selection for pattern recognition using multilayer perceptrons dennis W. ruck and steven K. rogers **

Introduction

Background

Methodology

Applications

Conclusions

**67 Wavelets for pattern recognition George w. Rogers, david J. marchette, and Jeffrey L. solka **

Wavelet-based segmentation

Resistive grid local averaging

Examples

**68 Fractals for pattern recognition George W. rogers, carey E. priebe, and Jeffrey L. solka **

A PDP approach to localized fractal dimension computation with segmentation boundaries

**69 Multilayer perceptrons with ALOPEX and back propagation Daniel A. zahner and evangelia micheli-tzanakou **

Introduction

The backpropagation algorithm

The ALOPEX algorithm

Multilayer perceptron network

ALOPEX in VLSI

Discussion

**70 Supervised neural networks for handwritten digit recognition in industrial processing **

**Evangelia micheli-tzanokou **

Introduction

Preprocessing of handwritten digit images

Zernike moments to characterize image patterns

Dimensionality reduction

Analysis of prediction error rates from bootstrapping assessment

Summary

**71 Neocognitron kunihiko fukushima **

Neocognitron

Selective attention model (SAM)

**72 Studies of pattern recognition with self-learning layered neural networks faiq A. fazal and **

**Evangelia micheli-tzanakou **

**Abstract **

Introduction

Neocognitron and pattern classification

Objectives

Methods

Study A

Study B

Summary and discussion

** **

**73 Analog 3-D Neuroprocessor for fast frame focal plane image processing tuan A. duong Sabrina kemeny **

Taher daud, anil, thakoor ,chirs saunders and john carson

Introduction

Neural network architecture

Neural network design and operation

Experimental results

Cascade-back propagation

Six-bit parity problem

Conclusions

**74 Simulated annealing, Boltzmann machine, and hardware annealing tony H. Wu and bing J. sheu **

Simulated annealing

Boltzmann machine

Hardware annealing on Hopfield networks for optimization

Hardware annealing on cellular neural networks

**75 Radial basis function neural networks Thomas lindblad, Clark s Lindsey and age eide **

Introduction

Topology

Operation

Training

Summary

Defining terms

**76 Hardware implemented radial basis function the IBM zero instruction set computer **

**Thomas lindblad ,clark S. Lindsey, and age Eide **

Introduction

The ZISCO36 VLSI chip

Processing and training

Implementing the chip

Summary and extrapolations

**77 The RCE neural network douglas L. reilly **

Introduction

Training the RCE network

RCE network responses

Practical guides to RCE to pattern recognition

RCE network on a commercially available neural network chip

**78 Probabilistic neural networks model Donald F. specht **

Basic PNN

Adaptive PNN

High-speed Classification

Other considerations

Summary

**79 General regression neural network model Donald F. specht **

GRNN

Adaptive GRNN

Summary

**80 Classifiers: an overview wooGon chung and evangelia micheli-tzanakou **

Introduction

Criteria for optimal classifier design

Categorizing the classifiers

Classifiers

Neural networks

Comparison of experimental results

System performance assessment

Analysis of prediction rates from bootstrapping assessment

Section VII fuzzy systems and soft computing

**81 applications of fuzzy systems and soft computing in industrial electronics mary lou Padgett **

Introduction

From basic implementations to new research

** 82 Fuzzy numbers: the application of fuzzy algebra to safety and risk analysis J. arlin cooper **

Background

Analytical processing of input data

Fuzzy-algebra background

Fuzzy-algebra depiction of uncertainty

Examples applications

**83 Fuzzy systems Mo-yuen chow **

Brief description of fuzzy logic

Qualitative to quantitative descripti

Fuzzy operations

Fuzzy control

**84 Fuzzy hardware mary lou Padgett **

Introduction

Challenges and rewards

Approaches

Futures

Defining terms

**85 Fuzzy modeling and applications: controls visions, decisions mary lou Padgett **

Introduction

Engineering approaches

Futures

**86 Fuzzy logic control: basics and applications Robert N. lea,yashvant joni and joseph A. mica **

Introduction

A simple example of fuzzy logic control

The example of the inverted pendulum

Remote manipulator system

Collision avoidance

Summary

**87 Development of an intelligent unmanned helicopter based on fuzzy systems michio sugeno **

Howard A. Winston, isao hirano and satoru kotsu

Introduction

Helicopter hardware system

Software system for helicopter control

Results

Conclusions

**88 Fuzzy and neural modeling mary lou Padgett **

Introduction

Engineering approaches and applications

Futures

**89 NeuFuz: A combined neural net/fuzzy logic tool Thomas lindblad and clark S. Lindsey **

Introduction

Working with the neural network of neufuz4

Working with the fuzzy logic part of neufuz4

Working with the code generator part of neufuz4

Summary

**90 Neural network learning in fuzzy systems yashvant jani and Robert N. lea **

Introduction

Reinforcement learning

Architecture of ARIC

ARIC and 6 DOF space operations

GARIC and attitude control

Six degree-of-freedom proximity operations trajectory controller

**91 Neurocontrol and elastic fuzzy logic: capabilities concepts, and applications paul J. werbos **

Introduction

Neurocontrol in general

Basic principles of design

Supervised learning for neurocontrol

Elastic fuzzy logic: principle and subroutines

Current designs in neurocontrol : A roadmap

Appendix

**92 Integrated health monitoring and control in rotorcraft machines gary G. yen **

Introduction

Artificial neural networks

Fuzzy-based feed forward neural network

FDIA architecture

Simulation study

Conclusions

**93 Autonomous neural control in flexible space structures gary G. yen **

Learning control system

Adaptive time-delay radial function network

Eigen structure bidirectional associative memory

Fault detection and identification

Reconfigurable studies

Conclusion

**94 Fuzzy pattern recognition witold pedrycz **

Introduction remarks-pattern recognition in the framework of fuzzy sets

The general methodological structure of fuzzy modeling

Formation of the feature space

Implicit and explicit knowledge representation in pattern recognition

From supervised to unsupervised pattern recognition-A continuum of classification models

Implicit and explicit knowledge representation in pattern recognition

From supervised to unsupervised pattern recognition-A continuum of classification models

Fuzzy neural structures

Supervised learning

Implicitly supervised pattern recognition

Unsupervised learning

**95 Neural Fuzzy systems in handwritten digit recognition timothy J. Dasey and evangelia micheli-tzanakou **

Introduction

System design

Application to handwritten digits

Discussion

Summary

**96 Fuzzy algorithms for learning vector quantization nicolaos B. karayiannis **

Introduction

Learning vector quantization

Generalized learning vector quantization

Fuzzy learning vector quantization algorithms

GLVQ-F and FLVQ algorithms

Fuzzy algorithms for learning vector quantization

The FALVQ 1 family of algorithms

The FALVQ 2 family of algorithms

The FALVQ 3 family of algorithms

Competition measures

Alternative FALVQ algorithms

Experimental results

Discussion and concluding remarks

**97 Adaptive resonance theory gail A. carpenter and Stephen grossberg **

Math-based learning and error-based learning

ART and fuzzy logic

ART dynamics

Fuzzy art

Fuzzy artmap

Fuzzy art algorithm

Fuzzy ARTMAP algorithm

ART applications

**98 Future directions for fuzzy systems and soft computing in industrial electronics mary lou Padgett and **

**Lotfi A. zadeh **

**99 applications of evolutionary systems in industrial electronics mary lou Padgett and v. rao vemuri **

Introduction

From basic implementations to new research

Defining terms

**100 Evolutionary computation mary lou Padgett **

Introduction

Design of evolutionary systems

Applications

Summary

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