| Introduction to Advanced Process Control Concepts | p. 1 |
| Process Time Constant | p. 1 |
| Domain Transformations | p. 3 |
| Laplace Transformation | p. 5 |
| Discrete Approximations | p. 7 |
| z-Transforms | p. 9 |
| Advanced and Modified z-Transforms | p. 13 |
| Common Elements in Control | p. 16 |
| The Smith Predictor | p. 18 |
| Feed-forward Control | p. 21 |
| Feed-forward Control in a Smith Predictor | p. 23 |
| Dahlin's Control Algorithm | p. 26 |
| References | p. 31 |
| Process Simulation | p. 33 |
| Simulation using Matlab Simulink | p. 33 |
| Simulation of Feed-forward Control | p. 37 |
| Control Simulation of a 2x2 System | p. 39 |
| Simulation of Dahlin's Control Algorithm | p. 43 |
| Process Modeling and Identification | p. 45 |
| Model Applications | p. 45 |
| Types of Models | p. 46 |
| White Box and Black Box Models | p. 46 |
| Linear and Non-linear Models | p. 48 |
| Static and Dynamic Models | p. 48 |
| Distributed and Lumped Parameter Models | p. 48 |
| Continuous and Discrete Models | p. 49 |
| Empirical (linear) Dynamic Models | p. 50 |
| Model Structure Considerations | p. 50 |
| Parametric Models | p. 52 |
| Non-parametric Models | p. 54 |
| Model Identification | p. 57 |
| Introduction | p. 57 |
| Identification of Parametric Models | p. 57 |
| Identification of Non-parametric Models | p. 69 |
| References | p. 70 |
| Identification Examples | p. 73 |
| SISO Furnace Parametric Model Identification | p. 73 |
| MISO Parametric Model Identification | p. 79 |
| MISO Non-parametric Identification of a Non-integrating Process | p. 83 |
| MIMO Identification of an Integrating and Non-integrating Process | p. 85 |
| Design of Plant Experiments | p. 88 |
| Nature of Input Sequence | p. 88 |
| PRBS Type Input | p. 89 |
| Step Type Input | p. 90 |
| Type of Experiment | p. 91 |
| Data File Layout | p. 92 |
| Conversion of Model Structures | p. 92 |
| Example and Comparison of Open and Closed Loop Identification | p. 97 |
| References | p. 102 |
| Linear Multivariable Control | p. 103 |
| Interaction in Multivariable Systems | p. 103 |
| The Relative Gain Array | p. 103 |
| Properties of the Relative Gain Array | p. 104 |
| Some Examples | p. 105 |
| The Dynamic Relative Gain Array | p. 107 |
| Dynamic Matrix Control | p. 108 |
| Introduction | p. 108 |
| Basic DMC Formulation | p. 108 |
| One Step DMC | p. 112 |
| Prediction Equation and Unmeasurable Disturbance Estimation | p. 115 |
| Restriction of Excessive Moves | p. 116 |
| Expansion of DMC to Multivariable Problems | p. 118 |
| Equal Concern Errors | p. 119 |
| Constraint Handling | p. 120 |
| Constraint Formulation | p. 121 |
| Properties of Commercial MPC Packages | p. 124 |
| References | p. 126 |
| Multivariable Optimal Constraint Control Algorithm | p. 127 |
| General Overview | p. 127 |
| Model Formulation for Systems with Dead Time | p. 129 |
| Model Formulation for Multivariable Processes | p. 130 |
| Model Formulation for Multivariable Processes with Time Delays | p. 132 |
| Model Formulation in Case of a Limited Control Horizon | p. 132 |
| Mocca Control Formulation | p. 133 |
| Non-linear Transformations | p. 134 |
| Practical Implementation Guidelines | p. 135 |
| Case Study | p. 136 |
| Control of a Fluidized Catalytic Cracker | p. 140 |
| Examples of Case Studies in MATLAB | p. 144 |
| Control of Integrating Processes | p. 148 |
| Lab Exercises | p. 150 |
| Use of MCPC for Constrained Multivariable Contro | p. 156 |
| References | p. 159 |
| Internal Model Control | p. 161 |
| Introduction | p. 161 |
| Factorization of Multiple Delays | p. 162 |
| Filter Design | p. 164 |
| Feed-forward IMC | p. 164 |
| Example of Controller Design | p. 165 |
| LQ Optimal Inverse Design | p. 167 |
| References | p. 168 |
| Nonlinear Multivariable Control | p. 171 |
| Non-linear Model Predictive Control | p. 171 |
| Non-linear Quadratic DMC | p. 174 |
| Generic Model Control | p. 176 |
| Basic Algorithm | p. 176 |
| Examples of the GMC Algorithm | p. 179 |
| The Differential Geometry Concept | p. 179 |
| Problem Description | p. 181 |
| Model Representation | p. 181 |
| Process Constraints | p. 182 |
| Control Objectives | p. 184 |
| GMC Application to the CSTR System | p. 186 |
| Relative Degree of the CSTR System | p. 186 |
| Cascade Control Algorithm | p. 187 |
| Discussion of the GMC Algorithm | p. 188 |
| Simulation of Reactor Control | p. 188 |
| One Step Reference Trajectory Control | p. 193 |
| Predictive Horizon Reference Trajectory Control | p. 195 |
| References | p. 198 |
| Optimization of Process Operation | p. 201 |
| Introduction to Real-time Optimization | p. 201 |
| Optimization and its Benefits | p. 201 |
| Hierarchy of Optimization | p. 202 |
| Issues to be Addressed in Optimization | p. 204 |
| Degrees of Freedom Selection for Optimization | p. 206 |
| Procedure for Solving Optimization Problems | p. 207 |
| Problems in Optimization | p. 208 |
| Model Building | p. 209 |
| Phases in Model Development | p. 210 |
| Fitting Functions to Empirical Data | p. 211 |
| The Least Squares Method | p. 213 |
| The Objective Function | p. 216 |
| Function Extrema | p. 216 |
| Conditions for an Extremum | p. 217 |
| Unconstrained Functions: one Dimensional Problems | p. 218 |
| Newton's Method | p. 218 |
| Quasi-Newton Method | p. 219 |
| Polynomial Approximation | p. 219 |
| Unconstrained Multivariable Optimization | p. 219 |
| Introduction | p. 219 |
| Newton's Method | p. 221 |
| Linear Programming | p. 222 |
| Example | p. 222 |
| Degeneracies | p. 224 |
| The Simplex Method | p. 225 |
| The Revised Simplex Method | p. 229 |
| Sensitivity Analysis | p. 230 |
| Non-linear Programming | p. 231 |
| The Lagrange Multiplier Method | p. 231 |
| Other Techniques | p. 232 |
| Hints for Increasing the Effectiveness of NLP Solutions | p. 232 |
| References | p. 233 |
| Optimization Examples | p. 235 |
| AMPL: a Multi-purpose Optimizer | p. 235 |
| Example of an Optimization Problem | p. 235 |
| AMPL Formulation of the Problem | p. 237 |
| General Structure of an AMPL Model | p. 237 |
| General AMPL Rules | p. 238 |
| Detailed Review of the Transportation Example | p. 239 |
| Optimization Examples | p. 243 |
| Optimization of a Separation Train | p. 243 |
| A Simple Blending Problem | p. 246 |
| A Simple Alkylation Reactor Optimization | p. 248 |
| Gasoline Blending | p. 251 |
| Optimization of a Thermal Cracker | p. 253 |
| Steam Net Optimization | p. 257 |
| Turbogenerator Optimization | p. 260 |
| Alkylation Plant Optimization | p. 263 |
| References | p. 268 |
| Integration of Control and Optimization | p. 273 |
| Introduction | p. 273 |
| Description of the Desalination Plant | p. 273 |
| Production Maximization of Desalination Plant | p. 274 |
| Linear Model Predictive Control of Desalination Plant | p. 276 |
| Reactor problem definition | p. 279 |
| Multivariable Non-linear Control of the Reactor | p. 282 |
| References | p. 284 |
| MCPC software guide | p. 285 |
| Installation | p. 285 |
| Model identification | p. 285 |
| General process information | p. 286 |
| Identification data | p. 286 |
| Output details | p. 287 |
| Controller design | p. 289 |
| Control simulation | p. 291 |
| Dealing with constraints | p. 293 |
| Saving a project | p. 294 |
| Comparison of control strategies for a hollow shaft reactor | p. 295 |
| Introduction | p. 295 |
| Model Equations | p. 295 |
| Proportional Integral Control | p. 299 |
| Linear Multivariable Control | p. 300 |
| Non-linear Multivariable Control | p. 302 |
| References | p. 304 |
| Table of Contents provided by Publisher. All Rights Reserved. |