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Cover image for Advanced control unleashed : plant performance management for optimum benefit
Title:
Advanced control unleashed : plant performance management for optimum benefit
Publication Information:
Research Triangle Park, N.C. : Instrumentation, Systems, and Automation Society, 2003
Physical Description:
xvii, 434 p. : ill. ; 27 cm. + 1 CD-ROM (12 cm.)
ISBN:
9781556178153
General Note:
Accompanied by CD-ROM : CP 032100
Added Author:

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30000010320962 TS156.8 A33 2003 Open Access Book Book
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Summary

Summary

This book is a guide for both experienced engineers as well as newcomers to advanced control. It serves as a bridge between theoretical concepts and effective practical implementations. The major topics are: Setting a foundation, finding the opportunities, and estimating the benefits for advanced control; Using Auto Tuners; Applying Model Predictive Control and integrating optimization techniques; Getting the most out of Dynamic Estimators, Abnormal Situation Management, and Fuzzy Logic Control; Employing dynamic simulations of processes and control systems for design, prototyping and training; Setting up an online system for automated analysis and evaluation of control system and process performance. Each topic is summarized to capture important concepts, rules of thumb and best practices. This book includes a CD with practical design, simulation, and implementation examples. This interactive learning environment includes overviews by the authors and video demonstrations that make key examples in the book come alive. Configuration and case files are supplied for a hands-on experience, and PowerPoint files suitable for lectures on each unit are included on the CD.Reading the book and observing the simulation exercises offers the shortest path for getting the most value out of applying advanced control. The book should be a good companion for every engineer practicing advanced control.


Table of Contents

Acknowledgmentp. xiii
About the Authorsp. xv
Forewordp. xvii
Chapter 1 Introductionp. 1
Chapter 2 Setting the Foundationp. 5
Practicep. 5
Overviewp. 5
Opportunity Assessmentp. 12
Examplesp. 15
Applicationp. 20
General Procedurep. 20
Application Detailp. 26
Rules of Thumbp. 74
Theoryp. 76
Process Time Constants and Gainsp. 76
Process Time Delayp. 79
Ultimate Gain and Periodp. 80
Peak and Integrated Errorp. 82
Feedforward Controlp. 84
Dead Time from Valve Dead Bandp. 84
Nomenclaturep. 85
Referencesp. 86
Chapter 3 APC Pathwaysp. 89
Practicep. 89
Overviewp. 89
Opportunity Assessmentp. 94
Examplesp. 103
Applicationp. 106
General Procedurep. 106
Application Detailp. 108
Rules of Thumbp. 115
Referencesp. 116
Chapter 4 Evaluating System Performancep. 119
Practicep. 119
Overviewp. 119
Opportunity Assessmentp. 121
Examplesp. 125
Applicationp. 129
General Procedurep. 129
Application Detailsp. 131
Rules of Thumbp. 143
Guided Tourp. 144
Theoryp. 147
Using Statistics for Control Performance Evaluationp. 150
Extending the Concept to the Multi-variable Environmentp. 153
Addressing Advanced Controlp. 154
Diagnostic Toolsp. 156
Referencesp. 160
Chapter 5 Abnormal Situation Managementp. 163
Practicep. 163
Overviewp. 163
Opportunity Assessmentp. 165
Examplesp. 166
Applicationp. 168
General Procedurep. 168
Application Detailsp. 169
Rules of Thumbp. 171
Guided Tourp. 173
Theoryp. 177
Introduction to Expert Systemsp. 177
Rulesp. 178
Inference Enginep. 180
Factsp. 181
Referencesp. 182
Chapter 6 Automated Tuningp. 183
Practicep. 183
Overviewp. 183
Opportunity Assessmentp. 185
Examplesp. 187
Applicationp. 197
General Procedurep. 197
Application Detailp. 200
Rules of Thumbp. 202
Guided Tourp. 206
Theoryp. 208
Introduction to Auto Tunersp. 208
Basics of Relay-Oscillation Tuningp. 210
Model Based Tuningp. 218
Robustness Based Tuningp. 221
Adaptive Controlp. 225
Referencesp. 237
Chapter 7 Fuzzy Logic Controlp. 239
Practicep. 239
Overviewp. 239
Opportunity Assessmentp. 240
Examplesp. 240
Applicationp. 241
General Procedurep. 241
Rules of Thumbp. 242
Guided Tourp. 242
Theoryp. 244
Introduction to Fuzzy Logic Controlp. 244
Building a Fuzzy Logic Controllerp. 247
Fuzzy Logic PID Controllerp. 251
Fuzzy Logic Control Nonlinear PI Relationshipp. 254
FPID and PID Relationsp. 257
Automation of Fuzzy Logic Controller Commissioningp. 258
Referencesp. 259
Chapter 8 Properties Estimationp. 261
Practicep. 261
Overviewp. 261
Opportunity Assessmentp. 263
Example--Dynamic Linear Estimatorp. 265
Examples - Neural Networksp. 269
Applicationp. 274
General Procedurep. 274
Application Detailp. 279
Rules of Thumbp. 289
Guided Tourp. 289
Theoryp. 294
Dynamic Linear Estimatorp. 294
Neural Networksp. 296
Referencesp. 305
Chapter 9 Model Predictive Controlp. 307
Practicep. 307
Overviewp. 307
Opportunity Assessmentp. 310
Examplesp. 316
Applicationp. 337
General Procedurep. 337
Application Detailp. 339
Rules of Thumbp. 353
Guided Tourp. 355
Theoryp. 362
The Basics of Process Modelingp. 364
Identifying the Process Modelp. 367
Unconstrained Model Predictive Controlp. 369
Integrating Constraints Handling, Optimization and Model Predictive Controlp. 373
Referencesp. 381
Chapter 10 Virtual Plantp. 383
Practicep. 383
Overviewp. 383
Opportunity Assessmentp. 386
Examplesp. 387
Applicationp. 389
General Procedurep. 389
Online Adaptationp. 393
Application Detailp. 395
Rules of Thumbp. 399
Guided Tourp. 400
Theoryp. 403
Referencesp. 408
Appendix A Additional Opportunity Assessment Questionsp. 409
Appendix B Batch-to-Continuous Transitionp. 415
Appendix C Definitionsp. 419
Appendix D Top 20 Mistakesp. 425
Indexp. 431
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