TY  - BOOK
AU  - Roffel,Brian
AU  - Betlem,B.H.
TI  - Advanced practical process control
T2  - Engineering online library
SN  - 9783642621260
AV  - TS156.8 .R63 2004
PY  - 2004///
CY  - Berlin, New York
PB  - Springer
KW  - Process control
N1  - Includes bibliographical references and index; 1 Introduction to Advanced Process Control Concepts; -- 1.1 Process Time Constant; -- 1.2 Domain Transformations; -- 1.3 Laplace Transformation; -- 1.4 Discrete Approximations; -- 1.5 z-Transforms; -- 1.6 Advanced and Modified z-Transforms; -- 1.7 Common Elements in Control; -- 1.8 The Smith Predictor; -- 1.9 Feed-forward Control; -- 1.10 Feed-forward Control in a Smith Predictor; -- 1.11 Dahlin's Control Algorithm; -- References; -- 2 Process Simulation; -- 2.1 Simulation using Matlab Simulink; -- 2.2 Simulation of Feed-forward Control; -- 2.3 Control Simulation of a 2x2 System; -- 2.4 Simulation of Dahlin's Control Algorithm; -- 3 Process Modeling and Identification; -- 3.1 Model Applications; -- 3.2 Types of Models; -- 3.2.1 White Box and Black Box Models; -- 3.2.2 Linear and Non-linear Models; -- 3.2.3 Static and Dynamic Models; -- 3.2.4 Distributed and Lumped Parameter Models; -- 3.2.5 Continuous and Discrete Models; -- 3.3 Empirical (linear) Dynamic Models; -- 3.4 Model Structure Considerations; -- 3.4.1 Parametric Models; -- 3.4.2 Non-parametric Models; -- 3.5 Model Identification; -- 3.5.1 Introduction; -- 3.5.2 Identification of Parametric Models; -- 3.5.3 Identification of Non-parametric Models; -- References; -- 4 Identification Examples; -- 4.1 SISO Furnace Parametric Model Identification; -- 4.2 MISO Parametric Model Identification; -- 4.3 MISO Non-parametric Identification of a Non-integrating Process; -- 4.4 MIMO Identification of an Integrating and Non-integrating Process; -- 4.5 Design of Plant Experiments; -- 4.5.1 Nature of Input Sequence; -- 4.5.2 PRBS Type Input; -- 4.5.3 Step Type Input; -- 4.5.4 Type of Experiment; -- 4.6 Data File Layout; -- 4.7 Conversion of Model Structures; -- 4.8 Example and Comparison of Open and Closed Loop Identification; -- References; -- 5 Linear Multivariable Control; -- 5.1 Interaction in Multivariable Systems; -- 5.1.1 The Relative Gain Array; -- 5.1.2 Properties of the Relative Gain Array; -- 5.1.3 Some Examples; -- 5.1.4 The Dynamic Relative Gain Array; -- 5.2 Dynamic Matrix Control; -- 5.2.1 Introduction; -- 5.2.2 Basic 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
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