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Buch, Englisch, 434 Seiten
Using First-Principles Models in Process Control
Buch, Englisch, 434 Seiten
ISBN: 978-1-64331-242-2
Verlag: Wiley
Nonlinear Model-Based Control: Using First-Principles Models in Process Control
First-principles models (engineering models) are used in industry for process design, troubleshooting, training, online analysis and supervisory optimization. The author's vision is to use them for control.
Why? They effectively handle nonlinearity, nonstationary behavior and interacting variables with just one tuning coefficient per controlled variable (CV). Using optimization, the controller can handle constraints and shape the manipulated variables to achieve desired controlled variable trajectories. Using first-principles models for control can also enhance the operational staff's understanding of the process, support auxiliary process management, and keep the mathematics at the engineers' comfort level. In addition, unifying all models across diverse process management operations ensures continuity and compatibility.
The book explains four control techniques using first-principles models that have been credibly demonstrated for industrial practice: generic model control, process-model-based control, predictive functional control and horizon predictive control. It illustrates their applications and discusses the pros and cons of each. To provide a better understanding of first-principles models, the book includes examples of setting up functions for controllers and discusses inherent properties such as ease of tuning, the handling of nonlinearity and interaction, feedforward constraints and the range of operation.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Acknowledgments v
About the Author xvii
Rationale/Preface xix
Section 1 Introductory Material 1
Chapter 1 Introduction 3
Chapter 2 Models 27
Chapter 3 Process Simulation 59
Chapter 4 Model Verification and Validation 75
Chapter 5 Control Issues 83
Chapter 6 Control Metrics Goodness 93
Chapter 7 First- and Second-Order Plus Dead Time Models 109
Chapter 8 III-Behaved Dynamics 125
Section 2 Simple Controllers – MISO and Unconstrained 135
Chapter 9 Simple Internal Model Control – Unconstrained 137
Chapter 10 Generic Model Control with Steady-State Models 149
Chapter 11 Simple Model-Based Control – MISO, Unconstrained 163
Chapter 12 Simple Process-Model-Based Control – Unconstrained MISO 185
Chapter 13 Simple Predictive Functional Control – Unconstrained MISO 197
Chapter 14 Simple Horizon Predictive Control – MISO with Constraints 207
Chapter 15 More on MISO Models 229
Chapter 16 Equivalence to PID 235
Section 3 Supporting Techniques for Multivariable Constrained Control 239
Chapter 17 Data and Action Filtering 241
Chapter 18 Steady- and Transient-State Identification 249
Chapter 19 Data Validity 271
Chapter 20 Optimization 277
Section 4 Constrained MIMO Control 291
Chapter 21 Constraints and Balancing Desirables 293
Chapter 22 Multivariable Processes 303
Chapter 23 MIMO Process-Model-Based Control (PMBC) 309
Chapter 24 MIMO Horizon Predictive Control 317
Section 5 Ending 323
Chapter 25 Insight 325
Section 6 Appendixes 343
Appendix A Car Speed Simulator 345
Appendix B In-Line Hot and Cold Water Mixing Simulator 351
Appendix C pH Neutralization Simulator 365
Appendix D Heat Exchanger Simulator 381
Appendix E Nomenclature 395
Bibliography 399
Index 405
