Advanced Process Control: Beyond Single Loop Control

This book fills the gap between basic control configurations (Practical Process Control) and model predictive control (MPC). For those loops whose performance has a direct impact on plant economics or product quality, going beyond simple feedback or cascade can improve control performance, or specifically, reduce the variance about the target. However, the effort required to implement such control technology must be offset by increased economic returns from production operations. The economic aspects of the application of the various advanced control technologies are stressed throughout the book.

Table of Contents:
Preface ix 1 Introduction 1 1.1. Implementing Control Logic 2 1.2. Control Blocks for Process Control 12 1.3. PID Controller 16 1.4. Integrator or Totalizer 23 1.5. Lead-Lag Element 26 1.6. Dead Time 29 1.7. Selector Block 34 1.8. Cutoff Block 35 1.9. Hand Station 36 2 Cascade Control 38 2.1. Jacketed Reactor 38 2.2. Block Diagrams 43 2.3. Problem Element 45 2.4. Cooling Media Disturbances 49 2.5. Effect of Varying Heat Transfer Rate 51 2.6. Cascade Control Modes 55 2.7. Remote Set Point 58 2.8. Output Tracking 60 2.9. Control Modes 62 2.10. Interacting Stages 64 2.11. Tuning Cascades 69 2.12. Windup in Cascade Controls 74 2.13. Integral Tracking 78 2.14. External Reset 81 2.15. Inhibit Increase Inhibit Decrease 83 3 Split-Range Control 86 3.1. Storage Tank Pressure Control 87 3.2. Split Range 95 3.3. Temperature Control Using Liquid Bypass 103 3.4. Recirculating Jacket with Heat and Cool Modes 113 4 Override Control 126 4.1. Limit on the Cooling Water Return Temperature 126 4.2. Example without Windup Protection 131 4.3. Integral Tracking 137 4.4. External Reset 143 4.5. Inhibit Increase Inhibit Decrease 149 4.6. Limits on Heat Transfer 156 4.7. Other Examples 168 5 Valve Position Control 179 5.1. Polymer Pumping Example 180 5.2. Terminal Reheat Systems 185 5.3. Equilibrium Reaction 188 5.4. Reactor with a Once-Through Jacket 192 6 Ratio and Feedforward Control 198 6.1. Simple Ratios 200 6.2. Ratio Control in Digital Systems 206 6.3. Feedback Trim 210 6.4. Dynamic Compensation 220 6.5. Ratio Plus Bias 234 6.6. Characterization Function 238 6.7. Cross-Limiting 247 6.8. Directional Lags 260 6.9. Feedforward Control 262 6.10. Feedforward Control Example 267 7 Loop Interaction 277 7.1. Multivariable Processes 278 7.2. Issues with the P&I Diagram 283 7.3. Steady-State Sensitivities or Gains 292 7.4. Quantitative Measures of Interaction 308 7.5. Loop Pairing 317 7.6. Starch Pumping System 319 7.7. Reducing the Degree of Interaction 331 8 Multivariable Control 345 8.1. Decoupler 347 8.2. Dead-Time Compensation 378 8.3. Model Predictive Control 394 Index 447

About the Author :
Dr. Cecil Smith has over 35 years experience in process control, and his expertise encompasses virtually every control technology being applied in industrial production facilities. His primary focus is on designing a control strategy for a process and then commissioning the controls, that is, the process aspects as opposed to systems aspects.? However, he is proficient with both DCS's, PLC's, PC-based controls, and single-loop microprocessor-based controls, and is capable of resolving both process and system problems. Dr. Smith has equally extensive experience in teaching continuing education courses for practicing engineers on various aspects of process control and instrumentation.

Review :
"This book fills the gap between basic control configurations (Practical Process Control) and model predictive control (MPC). For those loops whose performance has a direct impact on plant economics or product quality, going beyond simple feedback or cascade can improve control performance, or specifically, reduce the variance about the target." (Live-PR, 8 December 2010) "This book fills the gap between basic control configurations (Practical Process Control) and model predictive control (MPC). For those loops whose performance has a direct impact on plant economics or product quality, going beyond simple feedback or cascade can improve control performance, or specifically, reduce the variance about the target." (Yahoo! Finance US, 8 December 2010)