Process Control: A Practical Approach

621 Pages·2016·9.275 MB·English

by  Myke King

Process Control
A Practical Approach

Process Control
A Practical Approach
Second Edition
Myke King
Whitehouse Consulting, Isle of Wight, UK
This edition first published 2016
© 2016 John Wiley & Sons, Ltd
First Edition published in 2011
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Library of Congress Cataloging‐in‐Publication Data
Names: King, Myke, 1951– author.
Title: Process control : a practical approach / Myke King.
Description: Second edition. | Chichester, West Sussex, United Kingdom : John Wiley & Sons Inc., 2016. |
Includes bibliographical references and index.
Identifiers: LCCN 2015044557 (print) | LCCN 2015045760 (ebook) | ISBN 9781119157748 (print) | ISBN 9781119157755 (epdf) |
ISBN 9781119157762 (epub) | ISBN 9781119157779 (Obook) | ISBN 9781119157755 (Adobe PDF) | ISBN 9781119157762 (ePub)
Subjects: LCSH: Chemical process control.
Classification: LCC TP155.75 .K56 2016 (print) | LCC TP155.75 (ebook) | DDC 660/.2815–dc23
LC record available at http://lccn.loc.gov/2015044557
A catalogue record for this book is available from the British Library.
Cover image: gettyimages/imagewerkz
Set in 10/12pt Times by SPi Global, Pondicherry, India
1 2016
Contents
Preface x
About the Author xv
1. Introduction 1
2. Process Dynamics 3
2.1 Definition 3
2.2 Cascade Control 10
2.3 Model Identification 12
2.4 Integrating Processes 26
2.5 Other Types of Process 29
2.6 Robustness 31
3. PID Algorithm 35
3.1 Definitions 35
3.2 Proportional Action 36
3.3 Integral Action 41
3.4 Derivative Action 43
3.5 Versions of Control Algorithm 49
3.6 Interactive PID Controller 51
3.7 Proportional‐on‐PV Controller 56
3.8 Nonstandard Algorithms 64
3.9 Tuning 65
3.10 Ziegler‐Nichols Tuning Method 66
3.11 Cohen‐Coon Tuning Method 72
3.12 Tuning Based on Penalty Functions 73
3.13 Manipulated Variable Overshoot 77
3.14 Lambda Tuning Method 80
3.15 IMC Tuning Method 80
3.16 Choice of Tuning Method 83
3.17 Suggested Tuning Method for Self‐Regulating Processes 84
3.18 Tuning for Load Changes 87
3.19 Tuning for SP Ramps 89
3.20 Tuning for Unconstrained MV Overshoot 91
3.21 PI Tuning Compared to PID Tuning 92
3.22 Tuning for Large Scan Interval 94
3.23 Suggested Tuning Method for Integrating Processes 97
3.24 Measure of Robustness 99
3.25 Implementation of Tuning 100
vi Contents
3.26 Tuning Cascades 101
3.27 Loop Gain 104
3.28 Adaptive Tuning 105
3.29 Initialisation 106
3.30 Anti‐Reset Windup 108
3.31 On‐Off Control 109
4. Level Control 112
4.1 Use of Cascade Control 112
4.2 Parameters Required for Tuning Calculations 113
4.3 Tight Level Control 120
4.4 Averaging Level Control 122
4.5 Error‐Squared Controller 129
4.6 Gap Controller 132
4.7 Impact of Noise on Averaging Control 134
4.8 Potential Disadvantage of Averaging Level Control 136
4.9 General Approach to Tuning 137
4.10 Three‐Element Level Control 139
5. Signal Conditioning 143
5.1 Instrument Linearisation 143
5.2 Process Linearisation 145
5.3 Control of pH 147
5.4 Constraint Conditioning 151
5.5 Pressure Compensation of Distillation Tray Temperature 153
5.6 Compensation of Gas Flow Measurement 153
5.7 Filtering 155
5.8 Exponential Filter 157
5.9 Nonlinear Exponential Filter 161
5.10 Moving Average Filter 161
5.11 Least Squares Filter 163
5.12 Tuning the Filter 169
5.13 Control Valve Characterisation 170
5.14 Equal Percentage Valve 172
5.15 Split‐Range Valves 178
6. Feedforward Control 184
6.1 Ratio Algorithm 185
6.2 Bias Algorithm 188
6.3 Deadtime and Lead‐Lag Algorithms 190
6.4 Tuning 194
6.5 Laplace Derivation of Dynamic Compensation 199
7. Deadtime Compensation 201
7.1 Smith Predictor 201
7.2 Internal Model Control 206
7.3 Dahlin Algorithm 206
Contents vii
8. Multivariable Control 210
8.1 Constraint Control 210
8.2 SISO Constraint Control 211
8.3 Signal Selectors 213
8.4 Relative Gain Analysis 217
8.5 Niederlinski Index 226
8.6 Condition Number 227
8.7 Steady State Decoupling 229
8.8 Dynamic Decoupling 231
8.9 MPC Principles 237
8.10 Parallel Coordinates 239
8.11 Enhanced Operator Displays 240
8.12 MPC Performance Monitoring 242
9. Inferentials and Analysers 248
9.1 Inferential Properties 248
9.2 Assessing Accuracy 256
9.3 Laboratory Update of Inferential 262
9.4 Analyser Update of Inferential 266
9.5 Monitoring On‐Stream Analysers 268
10. Combustion Control 270
10.1 Fuel Gas Flow Correction 270
10.2 Measuring NHV 278
10.3 Dual Firing 280
10.4 Heater Inlet Temperature Feedforward 281
10.5 Fuel Pressure Control 284
10.6 Firebox Pressure 287
10.7 Combustion Air Control 288
10.8 Boiler Control 299
10.9 Fired Heater Pass Balancing 300
11. Compressor Control 306
11.1 Polytropic Head 306
11.2 Load Control (Turbo‐Machines) 310
11.3 Load Control (Reciprocating Machines) 314
11.4 Anti‐Surge Control 315
12. Distillation Control 322
12.1 Key Components 325
12.2 Relative Volatility 325
12.3 McCabe‐Thiele Diagram 328
12.4 Cut and Separation 333
12.5 Effect of Process Design 345
12.6 Basic Controls 350
12.7 Pressure Control 350
12.8 Level Control 364
viii Contents
12.9 Tray Temperature Control 382
12.10 Pressure Compensated Temperature 393
12.11 Inferentials 402
12.12 First‐Principle Inferentials 411
12.13 Feedforward on Feed Rate 413
12.14 Feed Composition Feedforward 416
12.15 Feed Enthalpy Feedforward 418
12.16 Decoupling 419
12.17 Multivariable Control 424
12.18 On‐Stream Analysers 433
12.19 Towers with Sidestreams 433
12.20 Column Optimisation 435
12.21 Optimisation of Column Pressure 438
12.22 Energy/Yield Optimisation 441
13. APC Project Execution 444
13.1 Benefits Study 444
13.2 Benefit Estimation for Improved Regulatory Control 445
13.3 Benefits of Closed‐Loop Real‐Time Optimisation 455
13.4 Basic Controls 458
13.5 Basic Control Monitoring 459
13.6 Inferential Properties 464
13.7 Organisation 464
13.8 Vendor Selection 468
13.9 Safety in APC Design 471
13.10 Alarms 471
14. Statistical Methods 473
14.1 Central Limit Theorem 473
14.2 Generating a Normal Distribution 475
14.3 Quantile Plots 477
14.4 Calculating Standard Deviation 478
14.5 Skewness and Kurtosis 480
14.6 Correlation 480
14.7 Confidence Interval 481
14.8 Westinghouse Electric Company Rules 484
14.9 Gamma Function 485
14.10 Student t Distribution 486
14.11 χ2 Distribution 489
14.12 F Distribution 492
14.13 Akaike Information Criterion 497
14.14 Adjusted R2 499
14.15 Levene’s Test 500
14.16 Box‐Wetz Ratio 501
14.17 Regression Analysis 502
14.18 Outliers 513
14.19 Model Identification 514
Contents ix
14.20 Autocorrelation and Autocovariance 518
14.21 Artificial Neural Networks 527
14.22 Repeatability 533
14.23 Reproducibility 533
14.24 Six‐Sigma 535
14.25 Data Reconciliation 535
15. Mathematical Techniques 540
15.1 Fourier Transform 540
15.2 Recursive Filters 548
15.3 Lagrangian Interpolation 553
15.4 Padé Approximation 557
15.5 Laplace Transform Derivations 560
15.6 Laplace Transforms for Processes 563
15.7 Laplace Transforms for Controllers 569
15.8 I‐PD versus PI‐D Algorithm 572
15.9 Direct Synthesis 573
15.10 Predicting Filter Attenuation 578
15.11 Stability Limit for PID Control 579
15.12 Ziegler‐Nichols Tuning from Process Dynamics 583
15.13 Partial Fractions 586
15.14 z‐Transforms and Finite Difference Equations 588
References 594
Index 596