Process Dynamics and Control: Modeling for Control and Prediction Book

Foreword     xi
Preface     xiii
Acknowledgement     xv
Introduction to Process Modeling     1
Application of Process Models     1
Dynamic Systems Modeling     2
Modeling Steps     5
Use of Diagrams     16
Types of Models     20
Continuous versus Discrete Models     23
References     23
Process Modeling Fundamentals     25
System States     25
Mass Relationship for Liquid and Gas     29
Energy Relationship     38
Composition Relationship     48
Extended Analysis of Modeling for Process Operation     57
Environmental Model     57
Procedure for the Development of an Environmental Model for Process Operation     58
Example: Mixer     68
Example: Evaporator with Variable Heat Exchanging Surface     69
Design for Process Modeling and Behavioral Models     71
Behavioral Model     71
Example: Mixer     77
Transformation Techniques     81
Introduction     81
Laplace Transform     81
Useful Properties of Laplace Transform: limit functions     83
Transfer Functions     84
Discrete Approximations     89
z-Transforms     90
References     95
Linearization of Model Equations     97
Introduction     97
Non-linear Process Models     97
Some General Linearization Rules     100
Linearization of Model of the Level Process     102
Linearization of the Evaporator model     103
Normalization of the Transfer Function     105
Linearization of the Chemical Reactor Model     105
Operating Points     109
Introduction     109
Stationary System and Operating Point     109
Flow Systems     110
Chemical System     111
Stability in the Operating Point     113
Operating Point Transition     116
Process Simulation     119
Using Matlab Simulink     119
Simulation of the Level Process     119
Simulation of the Chemical Reactor     124
References     126
Frequency Response Analysis     127
Introduction     127
Bode Diagrams     129
Bode Diagram of Simulink Models      135
References     137
General Process Behavior     139
Introduction     139
Accumulation Processes     140
Lumped Process with Non-interacting Balances     142
Lumped Process with Interacting Balances     144
Processes with Parallel Balances     148
Distributed Processes     151
Processes with Propagation Without Feedback     154
Processes with Propagation With Feedback     157
Analysis of a Mixing Process     161
The Process     161
Mixer with Self-adjusting Height     164
Dynamics of Chemical Stirred Tank Reactors     169
Introduction     169
Isothermal First-order Reaction     169
Equilibrium Reactions     172
Consecutive Reactions     175
Non-isothermal Reactions     178
Dynamic Analysis of Tubular Reactors     185
Introduction     185
First-order Reaction     186
Equilibrium Reaction     188
Consecutive Reactions     188
Tubular Reactor with Dispersion     188
Dynamics of Adiabatic Tubular Flow Reactors     192
References     194
Dynamic Analysis of Heat Exchangers     195
Introduction     195
Heat Transfer from a Heating Coil     195
Shell and Tube Heat Exchanger with Condensing Steam     198
Dynamics of a Counter-current Heat Exchanger     205
References     206
Dynamics of Evaporators and Separators     207
Introduction     207
Model Description     208
Linearization and Laplace Transformation     209
Derivation of the Normalized Transfer Function     210
Response Analysis     211
General Behavior     212
Example of Some Responses     212
Separation of Multi-phase Systems     213
Separator Model     214
Model Analysis     215
Derivation of the Transfer Function     217
Dynamic Modeling of Distillation Columns     219
Column Environmental Model     219
Assumptions and Simplifications     220
Column Behavioral Model     221
Component Balances and Equilibria     222
Energy Balances     225
Tray Hydraulics     228
Tray Pressure Drop     233
Column Dynamics     236
Notation      240
Greek Symbols     242
References     243
Dynamic Analysis of Fermentation Reactors     245
Introduction     245
Kinetic Equations     245
Reactor Models     247
Dynamics of the Fed-batch Reactor     248
Dynamics of Ideally Mixed Fermentation Reactor     252
Linearization of the Model for the Continuous Reactor     254
References     258
Physiological Modeling: Glucose-Insulin Dynamics and Cardiovascular Modeling     259
Introduction to Physiological Models     259
Modeling of Glucose and Insulin Levels     260
Steady-state Analysis     262
Dynamic Analysis     263
The Bergman Minimal Model     264
Introduction to Cardiovascular Modeling     264
Simple Model Using Aorta Compliance and Peripheral Resistance     265
Modeling Heart Rate Variability using a Baroreflex Model     268
References     271
Introduction to Black Box Modeling     273
Need for Different Model Types     273
Modeling steps     274
Data Preconditioning     275
Selection of Independent Model Variables     275
Model Order Selection     276
Model Linearity     277
Model Extrapolation     277
Model Evaluation     277
Basics of Linear Algebra     279
Introduction     279
Inner and Outer Product     280
Special Matrices and Vectors     281
Gauss-Jordan Elimination, Rank and Singularity     281
Determinant of a matrix     283
The Inverse of a Matrix     284
Inverse of a Singular Matrix     285
Generalized Least Squares     287
Eigen Values and Eigen Vectors     288
References     290
Data Conditioning     291
Examining the Data     291
Detecting and Removing Bad Data     292
Filling in Missing Data     295
Scaling of Variables     295
Identification of Time Lags     296
Smoothing and Filtering a Signal     297
Initial Model Structure     302
References     304
Principal Component Analysis     305
Introduction     305
PCA Decomposition     306
Explained Variance     308
PGA Graphical User Interface     309
Case Study: Demographic data     310
Case Study: Reactor Data     313
Modeling Statistics     314
References     316
Partial Least Squares     317
Problem Definition     317
The PLS Algorithm     318
Dealing with Non-linearities     319
Dynamic Extensions of PLS     320
Modeling Examples     321
References     325
Time-series Identification     327
Mechanistic Non-linear Models     327
Empirical (linear) Dynamic Models     327
The Least Squares Method     328
Cross-correlation and Autocorrelation     329
The Prediction Error Method     331
Identification Examples     332
Design of Plant Experiments     337
References     340
Discrete Linear and Non-linear State Space Modeling     341
Introduction     341
State Space Model Identification     342
Examples of State Space Model Identification     343
References     348
Model Reduction     349
Model Reduction in the Frequency Domain     349
Transfer Functions in the Frequency Domain      350
Example of Basic Frequency-weighted Model Reduction     351
Balancing of Gramians     353
Examples of Model State Reduction Techniques     356
References     360
Neural Networks     361
The Structure of an Artificial Neural Network     361
The Training of Artificial Neural Networks     363
The Standard Back Propagation Algorithm     364
Recurrent Neural Networks     367
Neural Network Applications and Issues     370
Examples of Models     372
References     379
Fuzzy Modeling     381
Mamdani Fuzzy Models     381
Takagi-Sugeno Fuzzy Models     382
Modeling Methodology     384
Example of Fuzzy Modeling     384
Data Clustering     386
Non-linear Process Modeling     391
References     397
Neuro Fuzzy Modeling     399
Introduction     399
Network Architecture     399
Calculation of Model Parameters     401
Identification Examples     403
References     410
Hybrid Models     413
Introduction     413
Methodology      414
Approaches for Different Process Types     424
Bioreactor Case Study     436
Literature     438
Introduction to Process Control and Instrumentation     439
Introduction     439
Process Control Goals     440
The Measuring Device     444
The Control Device     449
The Controller     451
Simulating the Controlled Process     452
References     453
Behaviour of Controlled Processes     455
Purpose of Control     455
Controller Equations     457
Frequency Response Analysis of the Process     458
Frequency Response of Controllers     460
Controller Tuning Guidelines     462
References     464
Design of Control Schemes     465
Procedure     465
Example: Desulphurization Process     472
Optimal Control     475
Extension of the Control Scheme     478
Final Considerations     485
Control of Distillation Columns     487
Control Scheme for a Distillation Column     487
Material and Energy Balance Control     495
Summary      500
References     501
Impact of Vapor Flow Variations on Liquid Holdup     501
Ratio Control for Liquid and Vapor Flow in the Column     502
Control of a Fluid Catalytic Cracker     503
Introduction     503
Initial Input-output Variable Selection     505
Extension of the Basic Control Scheme     509
Selection of the Final Control Scheme     510
References     514
Modeling an Extraction Process     515
Problem Analysis     515
Dynamic Process Model Development     517
Dynamic Process Model Analysis     521
Dynamic Process Simulation     524
Process Control Simulation     530
Hints     534
Index     535