Advanced Practical Process Control, w. CD-ROM

DMC Formulation.- 5.2.3 One Step DMC.- 5.2.4 Prediction Equation and Unmeasurable Disturbance Estimation.- 5.2.5 Restriction of Excessive Moves.- 5.2.6 Expansion of DMC to Multivariable Problems.- 5.2.7 Equal Concern Errors.- 5.2.8 Constraint Handling.- 5.2.9 Constraint Formulation.- 5.3 Properties of Commercial MPC Packages.- References.- 6 Multivariable Optimal Constraint Control Algorithm.- 6.1 General Overview.- 6.2 Model Formulation for Systems with Dead Time.- 6.3 Model Formulation for Multivariable Processes.- 6.4 Model Formulation for Multivariable Processes with Time Delays.- 6.5 Model Formulation in Case of a Limited Control Horizon.- 6.6 Mocca Control Formulation.- 6.7 Non-linear Transformations.- 6.8 Practical Implementation Guidelines.- 6.9 Case Study.- 6.10 Control of a Fluidized Catalytic Cracker.- 6.11 Examples of Case Studies in MATLAB.- 6.12 Control of Integrating Processes.- 6.13 Lab Exercises.- 6.14 Use of MCPC for Constrained Multivariable Control.- References.- 7 Internal Model Control.- 7.1 Introduction.- 7.2 Factorization of Multiple Delays.- 7.3 Filter Design.- 7.4 Feed-forward IMC.- 7.5 Example of Controller Design.- 7.6 LQ Optimal Inverse Design.- References.- 8 Nonlinear Multivariable Control.- 8.1 Non-linear Model Predictive Control.- 8.2 Non-linear Quadratic DMC.- 8.3 Generic Model Control.- 8.3.1 Basic Algorithm.- 8.3.2 Examples of the GMC Algorithm.- 8.3.3 The Differential Geometry Concept.- 8.4 Problem Description.- 8.4.1 Model Representation.- 8.4.2 Process Constraints.- 8.4.3 Control Objectives.- 8.5 GMC Application to the CSTR System.- 8.5.1 Relative Degree of the CSTR System.- 8.5 2 Cascade Control Algorithm.- 8.6 Discussion of the GMC Algorithm.- 8.7 Simulation of Reactor Control.- 8.8 One Step Reference Trajectory Control.- 8.9 Predictive Horizon Reference Trajectory Control.- References.- 9 Optimization of Process Operation.- 9.1 Introduction to Real-time Optimization.- 9.1.1 Optimization and its Benefits.- 9.1.2 Hierarchy of Optimization.- 9.1.3 Issues to be Addressed in Optimization.- 9.1.4 Degrees of Freedom Selection for Optimization.- 9.1.5 Procedure for Solving Optimization Problems.- 9.1.6 Problems in Optimization.- 9.2 Model Building.- 9.2.1 Phases in Model Development.- 9.2.2 Fitting Functions to Empirical Data.- 9.2.3 The Least Squares Method.- 9.3 The Objective Function.- 9.3.1 Function Extrema.- 9.3.2 Conditions for an Extremum.- 9.4 Unconstrained Functions: one Dimensional Problems.- 9.4.1 Newton's Method.- 9.4.2 Quasi-Newton Method.- 9.4.3 Polynomial Approximation.- 9.5 Unconstrained Multivariable Optimization.- 9.5.1 Introduction.- 9.5.2 Newton's Method.- 9.6 Linear Programming.- 9.6.1 Example.- 9.6.2 Degeneracies.- 9.6.3 The Simplex Method.- 9.6.4 The Revised Simplex Method.- 9.6.5 Sensitivity Analysis.- 9.7 Non-linear Programming.- 9.7.1 The Lagrange Multiplier Method.- 9.7.2 Other Techniques.- 9.7.3 Hints for Increasing the Effectiveness of NLP Solutions.- References.- 10 Optimization Examples.- 10.1 AMPL: a Multi-purpose Optimizer.- 10.1.1 Example of an Optimization Problem.- 10.1.2 AMPL Formulation of the Problem.- 10.1.3 General Structure of an AMPL Model.- 10.1.4 General AMPL Rules.- 10.1.5 Detailed Review of the Transportation Example.- 10.2 Optimization Examples.- 10.2.1 Optimization of a Separation Train.- 10.2.2 A Simple Blending Problem.- 10.2.3 A Simple Alkylation Reactor Optimization.- 10.2.4 Gasoline Blending.- 10.2.5 Optimization of a Thermal Cracker.- 10.2.6 Steam Net Optimization.- 10.2.7 Turbogenerator Optimization.- 10.2.8 Alkylation Plant Optimization.- References.- 11 Integration of Control and Optimization.- 11.1 Introduction.- 11.2 Description of the Desalination Plant.- 11.3 Production Maximization of Desalination Plant.- 11.4 Linear Model Predictive Control of Desalination Plant.- 11.5 Reactor problem definition.- 11.6 Multivariable Non-linear Control of the Reactor.- References.- Appendix I. MCPC software guide.- I.1 Installation.- I.2 Model identification.- I.2.1 General process information.- I.2.2 Identification data.- I.2.3 Output details.- I.3 Controller design.- I.4 Control simulation.- I.5 Dealing with constraints.- I.6 Saving a project.- Appendix II. Comparison of control strategies for a hollow shaft reactor.- II.1 Introduction.- II.2 Model Equations.- II.3 Proportional Integral Control.- II.4 Linear Multivariable Control.- II.5 Non-linear Multivariable Control.- References.