Process Control: A Practical Approach

This expanded new edition is specifically designed to meet the needs of the process industry, and closes the gap between theory and practice. * Back-to-basics approach, with a focus on techniques that have an immediate practical application, and heavy maths relegated to the end of the book * Written by an experienced practitioner, highly regarded by major corporations, with 25 years of teaching industry courses * Supports the increasing expectations for Universities to teach more practical process control (supported by IChemE)

Review: "The author is experienced and he dosen't hesitate to tell you what he thinks, making this a good book to increase your practical knowledge of regulatory control." (TCE- The Chemical Engineer, March 2012)

Author Biography: About the Author Myke King is the Director of Whitehouse Consulting, UK, an independent consulting organisation specialising in process control.

Preface.viii About the author.xiii 1 Introduction 16 2 Process Dynamics 18 2.1 Definition 18 2.2 Cascade Control 22 2.3 Model Identification 24 2.4 Integrating Processes 32 2.5 Other Types of Process 35 2.6 Robustness 36 3 PID Algorithm 39 3.1 Definitions 39 3.2 Proportional Action 39 3.3 Integral Action 44 3.4 Derivative Action 45 3.5 Versions of Control Algorithm 49 3.6 Interactive PID Controller 52 3.7 Proportional-on-PV Controller 56 3.8 Nonstandard Algorithms 60 3.9 Tuning 61 3.10 Ziegler-Nichols Tuning Method 62 3.11 Cohen-Coon Tuning Method 67 3.12 Tuning Based on Penalty Functions 68 3.13 Manipulated Variable Overshoot 70 3.14 Lambda Tuning Method 71 3.15 IMC Tuning Method 72 3.16 Choice of Tuning Method 74 3.17 Suggested Tuning Method for Self-Regulating Processes 75 3.18 Tuning for Load Changes 76 3.19 Tuning for SP Ramps 77 3.20 Tuning for Unconstrained MV Overshoot 77 3.21 PI Tuning Compared to PID Tuning 78 3.22 Tuning for Large Scan Interval 78 3.23 Suggested Tuning Method for Integrating Processes 80 3.24 Measure of Robustness 80 3.25 Implementation of Tuning 81 3.26 Tuning Cascades 82 3.27 Loop Gain 82 3.28 Adaptive Tuning 83 3.29 Initialisation 85 3.30 Anti-Reset Windup 86 3.31 On-Off Control 87 4 Level Control 89 4.1 Use of Cascade Control 89 4.2 Parameters Required for Tuning Calculations 90 4.3 Tight Level Control 95 4.4 Averaging Level Control 97 4.5 Error-Squared Controller 101 4.6 Gap Controller 104 4.7 Impact of Noise on Averaging Control 106 4.8 Potential Disadvantage of Averaging Level Control 107 4.9 General Approach to Tuning 108 4.10 Three-Element Level Control 110 5 Signal Conditioning 113 5.1 Instrument Linearisation 113 5.2 Process Linearisation 114 5.3 Control of pH 115 5.4 Constraint Conditioning 117 5.5 Pressure Compensation of Distillation Tray Temperature 118 5.6 Compensation of Gas Flow Measurement 119 5.7 Filtering 121 5.8 Exponential Filter 122 5.9 Nonlinear Exponential Filter 125 5.10 Moving Average Filter 126 5.11 Least Squares Filter 127 5.12 Tuning the Filter 130 5.13 Control Valve Characterisation 131 5.14 Equal Percentage Valve 131 5.15 Split-Range Valves 135 6 Feedforward Control 138 6.1 Ratio Algorithm 139 6.2 Bias Algorithm 141 6.3 Deadtime and Lead-Lag Algorithms 142 6.4 Tuning 144 6.5 Laplace Derivation of Dynamic Compensation 148 7 Deadtime Compensation 150 7.1 Smith Predictor 150 7.2 Internal Model Control 152 7.3 Dahlin Algorithm 152 8 Multivariable control 156 8.1 Constraint Control 156 8.2 SISO Constraint Control 157 8.3 Signal Selectors 158 8.4 Relative Gain Analysis 160 8.5 Niederlinski Index 167 8.6 Condition Number 167 8.7 Steady State Decoupling 169 8.8 Dynamic Decoupling 171 8.9 MPC Principles 174 8.10 Parallel Coordinates 177 8.11 Enhanced Operator Displays 178 8.12 MPC Performance Monitoring 178 9 Inferentials and Analysers 183 9.1 Inferential Properties 183 9.2 Assessing Accuracy 189 9.3 Laboratory Update of Inferential 193 9.4 Analyser Update of Inferential 197 9.5 Monitoring On-Stream Analysers 198 10 Combustion Control 201 10.1 Fuel Gas Flow Correction 201 10.2 Measuring NHV 205 10.3 Dual Firing 207 10.4 Inlet Temperature Feedforward 207 10.5 Fuel Pressure Control 210 10.6 Firebox Pressure 211 10.7 Combustion Air Control 212 10.8 Boiler Control 219 10.9 Fired Heater Pass Balancing 220 11 Compressor Control 226 11.1 Polytropic Head 226 11.2 Load Control (Turbo-Machines) 229 11.3 Load Control (Reciprocating Machines) 231 11.4 Anti-Surge Control 232 12 Distillation Control 237 12.1 Key Components 238 12.2 Relative Volatility 239 12.3 McCabe-Thiele Diagram 241 12.4 Cut and Separation 244 12.5 Effect of Process Design 250 12.6 Basic Controls 252 12.7 Pressure Control 253 12.8 Level Control 260 12.9 Tray Temperature Control 266 12.10 Pressure Compensated Temperature 271 12.11 Inferentials 278 12.12 First-Principle Inferentials 284 12.13 Feedforward on Feed Rate 286 12.14 Feed Composition Feedforward 287 12.15 Feed Enthalpy Feedforward 288 12.16 Decoupling 289 12.17 Multivariable Control 292 12.18 On-Stream Analysers 297 12.19 Towers with Sidestreams 298 12.20 Column Optimisation 299 12.21 Optimisation of Column Pressure 300 12.22 Energy/Yield Optimisation 301 13 APC Project Execution 303 13.1 Benefits Study 303 13.2 Benefit Estimation for Improved Regulatory Control 305 13.3 Benefits of Closed-Loop Real-Time Optimisation 311 13.4 Basic Controls 313 13.5 Basic Control Monitoring 314 13.6 Inferential Properties 318 13.7 Organisation 319 13.8 Vendor Selection 323 13.9 Safety in APC Design 325 13.10 Alarms 326 14 Statistical Methods 328 14.1 Central Limit Theorem 328 14.2 Generating a Normal Distribution 329 14.3 Quantile Plots 330 14.4 Calculating Standard Deviation 331 14.5 Skewness and Kurtosis 333 14.6 Correlation 333 14.7 Confidence Interval 335 14.8 Westinghouse Electric Company Rules 336 14.9 Gamma Function 337 14.10 Student t Distribution 338 14.11 2 Distribution 340 14.12 F Distribution 341 14.13 Akaike Information Criterion 343 14.14 Adjusted R2 345 14.15 Levene s Test 347 14.16 Box-Wetz Ratio 348 14.17 Regression Analysis 349 14.18 Outliers 358 14.19 Model Identification 358 14.20 Autocorrelation and Autocovariance 363 14.21 Artificial Neural Networks 367 14.22 Repeatability 370 14.23 Reproducibility 371 14.24 Six-Sigma 372 14.25 Data Reconciliation 372 15 Mathematical Techniques 376 15.1 Fourier Transform 376 15.2 Recursive Filters 380 15.3 Lagrangian Interpolation 383 15.4 Pade Approximation 386 15.5 Laplace Transform Derivations 390 15.6 Laplace Transforms for Processes 392 15.7 Laplace Transforms for Controllers 396 15.8 I-PD versus PI-D Algorithm 399 15.9 Direct Synthesis 400 15.10 Predicting Filter Attenuation 406 15.11 Stability Limit for PID Control 407 15.12 Ziegler-Nichols Tuning from Process Dynamics 411 15.13 Partial Fractions 414 15.14 Z-Transforms and Finite Difference Equations 416 References 423