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    ISA ADV CNTRL FNDTN-2013 Advanced Control Foundation Tools Techniques and Applications.pdf

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    ISA ADV CNTRL FNDTN-2013 Advanced Control Foundation Tools Techniques and Applications.pdf

    1、Advanced Control Foundation:Tools, Techniques and ApplicationsAdvContFound2013.book Page i Sunday, September 9, 2012 4:29 PMAdvContFound2013.book Page ii Sunday, September 9, 2012 4:29 PMAdvanced ControlFoundation:Tools, Techniques and ApplicationsTerrence BlevinsWilly K. WojsznisMark NixonAdvContFo

    2、und2013.book Page iii Sunday, September 9, 2012 4:29 PMNoticeThe information presented in this publication is for the general education of the reader. Because neither the author(s) nor the publisher has any control over the use of the information by the reader, both the author(s) and the publisher d

    3、isclaim any and all liability of any kind arising out of such use. The reader is expected to exercise sound professional judgment in using any of the information presented in a particular application.Additionally, neither the author(s) nor the publisher has investigated or considered the effect of a

    4、ny patents on the ability of the reader to use any of the information in a particular application. The reader is responsible for reviewing any possible patents that may affect any particular use of the information presented.Any references to commercial products in the work are cited as examples only

    5、. Neither the author(s) nor the publisher endorses any referenced commercial product. Any trademarks or tradenames referenced belong to the respective owner of the mark or name. Neither the author(s) nor the publisher makes any representation regarding the availability of any referenced commercial p

    6、roduct at any time. The manufacturers instructions on use of any commercial product must be followed at all times, even if in conflict with the information in this publication.Copyright 2013 International Society of Automation (ISA)All rights reserved. Printed in the United States of America. 10 9 8

    7、 7 6 5 4 3 2ISBN: 978-1-937560-55-3No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without the prior written permission of the publisher.ISA67 Alexander DriveP.O. Box 12277

    8、Research Triangle Park, NC 27709Library of Congress Cataloging-in-Publication Data in processAdvContFound2013.book Page iv Sunday, September 9, 2012 4:29 PMDedicationThis book is dedicated to Karen Blevins, Susan Wojsznis, and Nancy Nixon, who have provided encouragement and support throughout our c

    9、areers.AdvContFound2013.book Page v Sunday, September 9, 2012 4:29 PMAdvContFound2013.book Page vi Sunday, September 9, 2012 4:29 PMviiAcknowledgmentsThe authors wish to express their appreciation to Grant Wilson and Peter Zornio for supporting advanced control research and work on this book, and to

    10、 Jim Nyquist, John Berra, Mike Sheldon, Duncan Schleiss, John Caldwell, Dawn Marruchella, Darrin Kuchle, Jay Col-clazer, Nathan Pettus, Bruce Greenwald, Jim Hoffmaster, Ron Eddie and Gil Pareja from Emerson Process Management for their inspira-tion and support of advanced control initiatives. Also,

    11、we would like to express our deepest thanks to Bud Keyes, former Senior Vice Presi-dent of Technology, Emerson Process Management for his initiative in establishing the DeltaV advanced control program. In our work, we have benefited from communications with Karl strm from Lund University, Tom Edgar

    12、from the University of Texas, Joe Qin from the University of Southern California, and Dale Seborg from the Univer-sity of California, Santa Barbara on both basic and advanced control topics. The authors wish to thank Joanne Salazar, Glenn McLaughin, and Deborah Franke for their help with the web sit

    13、e for this book and Brenda Forsythe and Jim Sipowicz for the creative book cover design. We want to thank Joan Forbes and Cary Laird for their thorough review of the first draft and many editing suggestions. We also want to thank technical editor Scott Bogue for his excellent review of the final dra

    14、ft. In addition, we appreciate the input provided by ISA, and thank Susan Colwell, Manager, Publications Development, ISA, for her sup-port in the publication of this book. Over the years we have benefited from working with many others in the design and implementation of advanced control tools. The

    15、authors are deeply indebted to the developers of the advanced control tools that were the basis for writing this book. This includes Vasiliki Tzovla, Ron Ottenbacher, Dirk Thiele, Ashish Mehta, Yan Zhang, Peter Wojsz-AdvContFound2013.book Page vii Sunday, September 9, 2012 4:29 PMviii ADVANCED CONTR

    16、OL FOUNDATION: TOOLS, TECHNIQUES AND APPLICATIONSnis, Ian Nadas, Paul Muston, Bob Havekost, Paul Daly, Adam Qui, Chris Worek, Ken Beoughter, Dan Christensen, Ling Zhou, Ian Lloyd, and Vivi Hidayat. Also, we would like to recognize the valuable con-tribution of Tom Aneweer, Dennis Stevenson, Dick See

    17、mann, Yang Zhang, Steve Morrison, Mike Ott, Chuck Johnston, Randy Reiss, Greg McMillan, Todd Maras, Michael Boudreau, David Rehbein, Pat Dixon, Quay Finefrock, Shelli Callender, and Sai Ganesamoorthi. We grate-fully acknowledge the support of the many customers we have worked with in field testing a

    18、dvanced control products. In particular, the following individuals supported evaluation of these tools in their plants: John Traylor, Texas Eastman; Mark Sowell, Solutia; Romeo Ancheta, Husky Energy; Derrick Vanderkraats, Canfor; Bruce Johnson and Efren Hernandez, Lubrizol; Bruce Eldridge, Frank Sei

    19、bert, Ricardo Dunia, Eric Chen, Robert Montgomery, and Stephen W. Briggs, Uni-versity of Texas, Austin, Pickle Research Center; Scott Broadley, Presi-dent, Broadley-James; and Dan Coyne and Paul Oram, BP. Our special thanks goes to the Lubrizol team led by Bob Wojewodka for their feed-back on the de

    20、velopment of data analytics. The authors greatly appreciate the effort of Emerson Process Manage-ment Systems and Solutions control engineers progressing advanced control applications in petrochemical, oil and gas, chemical, life sci-ence, pulp and paper, power, and other industries. Our thanks go t

    21、o James Beall, Lou Heavner, Pete Sharpe, Doug White, Jim Dunbar, Eliz-abeth Alagar, and many others.It has been gratifying to work with Terry Chmelyk, Don Umbach, John Peterson, and Mike Begin and the rest of Spartan Controls team in field testing new advanced control technologies. The lime kiln exa

    22、m-ple in this book is an example of their work in this area. Also, we greatly appreciate the work done by the Spartan Control and Emerson Process Management teams in applying real-time optimization and MPC in a wide variety of applications. The application examples derived from the valuable field ex

    23、perience of Chris Hawkins, George Buchanan, Andrew Riley from Emerson Process Management, UK, Terrance Chmelyk, Saul Mtakula, Manny Sidhu, and Carl Sheehan from Spartan Controls, Barry Hirtz from Canfor, and by Stewart McLeod from Catalyst Paper greatly enriched this bookWe are indebted and thankful

    24、 as well to many of those not listed here who impacted the development of Emerson Process Managements advanced control products or contributed to the successful application of these products and inspired us to write this book.AdvContFound2013.book Page viii Sunday, September 9, 2012 4:29 PMixContent

    25、sAcknowledgments viiAbout the Authors xviiForeword xxiChapter 1 INTRODUCTION 1Chapter 2 MAXIMIZING RETURN ON CONTROL SYSTEM INVESTMENT 72.1 Economic Incentive, 92.1.1 Ammonia Plant Example, 132.2 Reducing Process Variation Achieving Control Objectives, 192.2.1 Single Loop Control, 192.2.2 Multi-Loop

    26、 Techniques, 212.3 Advanced Control , 292.3.1 Pulp Bleaching, 292.3.2 Primary Reformer Temperature Control, 302.4 Balancing Complexity with Benefits, 32Bibliography, 33Chapter 3 EVALUATING CONTROL SYSTEM PERFORMANCE 353.1 Evaluating Control Performance, 383.2 Improving Control Utilization, 42AdvCont

    27、Found2013.book Page ix Sunday, September 9, 2012 4:29 PMx ADVANCED CONTROL FOUNDATION: TOOLS, TECHNIQUES AND APPLICATIONS3.2.1 Transmitter Problems, 433.2.2 Incorrect Tuning , 443.2.3 Valve/Actuator Diagnostics, 463.2.4 Changing Process Gain, 473.2.5 Incorrect Split Range Setup, 493.2.6 Loop Interac

    28、tion, 513.3 Addressing Process Variability, 523.3.1 Changing Process Gain and Dynamics, 543.3.2 Unmeasured Process Disturbances, 543.3.3 Process Dynamics, 563.3.4 Loop Interaction, 563.3.5 Changing Limit Conditions, 573.3.6 Quality Parameter Lab Measurement, 573.4 Application Example, 583.5 Workshop

    29、 Exercises Introduction, 623.6 Evaluating Control System Performance Workshop, 643.7 Technical Basis , 653.7.1 Control Performance Monitoring Infrastructure, 663.7.2 Control Performance Evaluation Algorithms, 68Bibliography, 75Chapter 4 ON-DEMAND TUNING 774.1 Process Identification, 774.1.1 Simulati

    30、on of Loop Response, 864.2 On-Demand Tuning Workshop, 894.3 Technical Basis, 904.3.1 Basics of Relay Oscillation Tuning, 924.3.2 Model-Based Tuning, 1014.3.3 Robustness-Based Tuning, 1044.3.4 Some Alternate Tuning Approaches, 109Bibliography, 110Chapter 5 ADAPTIVE TUNING 1135.1 Adaptive Control Exam

    31、ples, 1145.1.1 Continuous Reactor Control, 1145.1.2 Batch Reactor, 1145.1.3 Hydrogen to Nitrogen (H/N) Ratio in Ammonia Production, 1165.1.4 Neutralizer, 1175.1.5 Plant Master Control, 119AdvContFound2013.book Page x Sunday, September 9, 2012 4:29 PMCONTENTS xi5.2 Application Example, 1195.2.1 Enabl

    32、ing Model Identification, 1205.2.2 Applying Models to Loop Tuning, 1235.3 Adaptive Tuning Workshop, 1255.4 Technical Basis, 1265.4.1 Model-Free Adaptive Tuning, 1275.4.2 Model-Based Recursive Adaptive Tuning, 1325.4.3 Discrete Fourier Transform Adaptation Technique, 1335.4.4 Adaptive Tuning with Mod

    33、el Switching and Parameter Interpolation, 134Bibliography, 142Chapter 6 FUZZY LOGIC CONTROL 1456.1 Application Example, 1506.2 Fuzzy Logic Control Workshop, 1526.3 Technical Basis, 1536.3.1 Introduction to Fuzzy Logic Control, 1536.3.2 Building a Fuzzy Logic Controller, 1566.3.3 Fuzzy Logic PID Cont

    34、roller, 1616.3.4 Fuzzy Logic Control Nonlinear PI Relationship, 1656.3.5 FPI and PI Relationships, 1676.3.6 Automatic Tuning of a Fuzzy PID Controller , 169Bibliography, 170Chapter 7 NEURAL NETWORKS FOR PROPERTY ESTIMATION 1717.1 Example Pulp and Paper Industry, 1737.2 Property Estimator Application

    35、 Example, 1767.3 Neural Networks for Property Estimation Workshop, 1827.4 Technical Basis, 1837.4.1 Data Collection, 1857.4.2 Identification of Input Delay, 1867.4.3 Input Sensitivity, 1877.4.4 Determining Input Weights, 1887.4.5 Nodes in the Hidden Layer, 1907.4.6 Correction for Process Changes, 19

    36、1Bibliography, 192AdvContFound2013.book Page xi Sunday, September 9, 2012 4:29 PMxii ADVANCED CONTROL FOUNDATION: TOOLS, TECHNIQUES AND APPLICATIONSChapter 8 INTELLIGENT PID 1958.1 Recovery from Process Saturation, 1978.2 Control Using Wireless Transmitter, 1998.3 Application Examples, 2068.3.1 Cont

    37、rol of a Bioreactor Using Wireless Devices, 2078.3.2 Compressor Surge Control , 2108.4 Intelligent PID Workshop, 2158.5 Technical Basis, 2178.5.1 Wireless Control , 2178.5.2 Recovery from Process Saturation, 2188.5.3 Extension to Include Rate, 220Bibliography, 221Chapter 9 CONTINUOUS DATA ANALYTICS

    38、2239.1 Application Example, 2379.1.1 Defining Model Inputs, 2399.1.2 Model Building, 2419.2 Viewing Data Analytics On-line, 2459.3 Continuous Data Analytics Workshop, 2479.4 Technical Basis, 2489.4.1 Data Formatting for Predictive Model Development, 2499.4.2 Process Monitoring and Predictive Algorit

    39、hms Review, 2509.4.3 Data Preprocessing and Scaling, 2549.4.4 PCA Modeling and On-line Fault Detection, 2569.4.5 PLS Modeling and On-line Prediction, 258Bibliography, 260Chapter 10 BATCH DATA ANALYTICS 26110.1 Batch Production Challenges, 26210.1.1 Role of Data Analytics in Facing Batch Production C

    40、hallenges, 26410.1.2 Batch Analytics Overview, 26810.1.3 Application of Batch Analytics to Specialty Chemicals Produc-tion , 27110.2 Data Analytics Application Example Modeling and On-line Operation, 27510.2.1 Defining Model Input, 27810.2.2 Viewing Data Analytics On-line , 28210.3 Batch Data Analyt

    41、ics Workshop, 285AdvContFound2013.book Page xii Sunday, September 9, 2012 4:29 PMCONTENTS xiii10.4 Technical Basis, 28610.4.1 Feedstock Property Modeling, 28710.4.2 Data Preprocessing and Validation, 29010.4.3 Multi-stage Batch Modeling, 29110.4.4 Alignment of Batch Data and On-line Model , 29410.4.

    42、5 Data Arrangement Unfolding, 29810.4.6 PCA Modeling and On-line Fault Detection, 29910.4.7 PLS Modeling and On-line Quality Prediction, 303Bibliography, 305Chapter 11 SIMPLE MPC 30711.1 MPC as a Replacement for PID, 30911.2 Commissioning MPC, 31011.3 MPC Replacement for PID with Feedforward, 31611.

    43、4 MPC Replacement for PID Override, 31711.5 Using MPC to Address Process Interactions, 31811.6 Application Examples, 32011.6.1 Evaporator Control, 32111.6.2 Dryer Control, 32211.6.3 Rotary Kiln Control, 32411.6.4 Pulp Brightness Control, 32711.6.5 MPC Control at Changing Production Rate, 32811.6.6 B

    44、atch Reactor Control, 33111.7 MPC Application Development Procedure , 33311.7.1 Process Analysis and MPC Configuration Design, 33511.7.2 Process Testing, 33611.7.3 Process Model Generation, 33711.7.4 Controller Generation, 33811.7.5 MPC Simulation and Tuning Validation, 33911.7.6 MPC Control Evaluat

    45、ion and Tuning Adjustment, 33911.8 Simple MPC Workshop, 34011.9 Technical Basis, 34011.9.1 The Basics of Process Modeling , 34511.9.2 Process Model Identification, 34911.9.3 Unconstrained Model Predictive Control, 35111.9.4 Integrating Constraints Handling, Optimization and Model Predictive Control,

    46、 356Bibliography, 361AdvContFound2013.book Page xiii Sunday, September 9, 2012 4:29 PMxiv ADVANCED CONTROL FOUNDATION: TOOLS, TECHNIQUES AND APPLICATIONSChapter 12 MPC INTEGRATED WITH OPTIMIZATION 36312.1 Application Example Multiple Effect Evaporator, 36512.1.1 Evaporator Process Overview, 36612.1.

    47、2 Project Motivation and Design Considerations, 36712.1.3 Why Use Model Predictive Control?, 36712.1.4 Model Predictive Control Strategy Development , 36812.1.5 Model Development and Verification, 37012.1.6 MPC Operation, Tuning and Optimization, 37112.1.7 Dealing with Major Process Constraints , 37

    48、212.1.8 Evaporator Flush Control , 37312.1.9 Solids Measurement, 37412.1.10 Operational Results , 37412.1.11 Summary, 37512.1.12 Recent Work and Future Opportunities, 37512.1.13 Acknowledgments, 37612.2 Application Example CTMP Refiner, 37612.2.1 Process Description, 37712.2.2 Electrical Energy Cons

    49、umption Model, 37812.2.3 Process Model Identification, 37912.2.4 MPC Control Strategy, 38012.2.5 Results, 38312.2.6 Summary, 38412.2.7 Acknowledgments , 38512.3 Application Example Heavy Oil Fractionator, 38512.4 MPC Integrated with Optimization Workshop, 40812.5 Technical Basis, 40812.5.1 MPC Operation Overview, 41012.5.2 On-line Multi-objective Optimizer Functionality Overview, 41612.5.3 Multi-objective MPC Optimization Background, 41712.5.4 Multi-objective Optimization Function for Infeasibility Han-dling , 41912.5.5 Multi-objective Optimization Functi


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