Caccavale / Iamarino / Pierri Control and Monitoring of Chemical Batch Reactors

1. Auflage 2010
ISBN: 978-0-85729-195-0
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 186 Seiten

Reihe: Advances in Industrial Control

The Chemical Batch Reactor is aimed at tackling the above problems from a blending of academic and industrial perspectives. Advanced solutions (i.e., those based on recent research results) to the four fundamental problems of modeling, identification, control and fault diagnosis for batch processes are developed in detail in four distinct chapters. In each chapter, a general overview of foundational concepts is also given, together with a review of recent and classical literature on the various subjects.To provide a unitary treatment of the different topics and give a firm link to the underlying practical applications, a single case study is developed as the book progresses; a batch process of industrial interest, i.e., the phenol-formaldehyde reaction for the production of phenolic resins, is adopted to test the various techniques developed. In this way, a roadmap of the solutions to fundamental problems, ranging from the early stages of the production process to the complete design of control and diagnosis systems, is provided for both industrial practitioners and academic researchers.

Autoren/Hrsg.

Caccavale, Fabrizio

Iamarino, Mario

Pierri, Francesco

Tufano, Vincenzo

Inhaltsverzeichnis

1;Series Editors' Foreword;9
2;Preface;11
3;Acknowledgements;13
4;Contents;14
5;Introduction;17
5.1;Overview of the Main Topics;17
5.2;The Batch Reactor;18
5.2.1;The Case Study;19
5.3;Identification of Mathematical Models;20
5.4;Thermal Stability;20
5.5;Control of Batch Reactors;21
5.6;Fault Diagnosis for Chemical Batch Reactors;22
5.7;Applications to Non-ideal Reactors;23
5.8;Suggested Reading Paths;23
6;The Chemical Batch Reactor;24
6.1;Ideal Chemical Reactors;25
6.2;The Rate of Chemical Reactions;27
6.3;The Ideal Batch Reactor;30
6.3.1;Conservation of Mass;31
6.3.2;Conservation of Energy;35
6.4;Introducing the Case Study;37
6.4.1;Components;39
6.4.2;Reactions;40
6.5;A General Model for a Network of Nonchain Reactions;42
6.6;Measuring the Reactor Status;46
6.6.1;Measurements Quality;47
6.6.2;Online Measurements;47
6.6.3;Offline Measurements;50
6.7;Manipulating the Reactor Status;50
6.8;Conclusions;52
6.9;References;52
7;Identification of Kinetic Parameters;54
7.1;Bayesian Approach and Popper's Falsificationism;56
7.2;Experimental Data and Mathematical Models;58
7.3;Maximum Likelihood and Least Squares Criteria;60
7.4;Optimization for Models Linear in the Parameters;63
7.5;Optimization for Models Nonlinear in the Parameters;65
7.5.1;Steepest Descent Algorithm;65
7.5.2;Newton-Raphson Algorithm;66
7.5.3;Levenberg-Marquardt Algorithm;67
7.6;Implicit Models;68
7.7;Statistical Analysis of the Results;69
7.8;Case Study: Identification of Reduced Kinetic Models;71
7.8.1;Reduced Models;71
7.8.2;Generation of Data for Identification;73
7.8.3;Estimating the Kinetic Parameters;74
7.8.4;Estimating the Heats of Reaction;76
7.8.5;Validation of the Reduced Models;77
7.9;Conclusions;80
7.10;References;81
8;Thermal Stability;83
8.1;Runaway in Chemical Batch Reactors;84
8.2;Dimensionless Mathematical Model;85
8.3;Adiabatic Reactor;88
8.4;Isoperibolic Reactor;89
8.4.1;The Semenov Theory;90
8.4.2;Geometry-based Runaway Criteria;93
8.4.3;Sensitivity-based Runaway Criteria;96
8.5;Operation Limited by the Maximum Allowable Temperature;98
8.6;Case Study: Runaway Boundaries;99
8.7;Conclusions;101
8.8;References;101
9;Model-based Control;103
9.1;Control Strategies for Batch Reactors;105
9.2;PID Regulator;106
9.3;Model Predictive Control ;107
9.4;Feedback Linearization;109
9.4.1;Input-Output Linearization;109
9.4.2;Generic Model Control;110
9.5;State-Space Model for Control Design;111
9.6;Estimation of the Heat Released by Reaction;113
9.6.1;Model-Based Nonlinear Observer;114
9.6.2;Model-Free Approaches;116
9.6.2.1;Approach Based on Universal Interpolators;116
9.6.2.2;A Classical Model-Free Approach;118
9.7;Adaptive Two-Loop Control Scheme;118
9.8;Case Study: Temperature Control;122
9.8.1;Simulation Model;123
9.8.2;Design of the Controller-Observer Scheme;124
9.8.3;Discussion of Results;125
9.8.4;Comparison with the PID Controller;127
9.9;Conclusions;130
9.10;References;131
10;Fault Diagnosis;135
10.1;Fault Diagnosis Strategies for Batch Reactors;136
10.1.1;Model-Free Approaches;137
10.1.2;Model-Based Approaches;138
10.2;Basic Principles of Model-Based Fault Diagnosis;139
10.2.1;Residual Generation;141
10.2.2;Decision Making System and Fault Isolation;142
10.3;Fault Diagnosis for Chemical Batch Reactors;143
10.3.1;Fault Characterization;143
10.3.2;Architecture of the Fault Diagnosis Scheme;145
10.4;Sensor Fault Diagnosis;147
10.4.1;Residuals Generation and Fault Isolation;149
10.4.2;Determination of the Healthy Signal;150
10.4.2.1;Voter procedure;150
10.5;Actuator and Process Fault Diagnosis;152
10.5.1;Fault Detection;152
10.5.2;Fault Isolation and Identification;154
10.6;Decoupling Sensor Faults from Process and Actuator Faults;157
10.7;Case Study: Fault Diagnosis;157
10.7.1;Simulation Results: Sensor Faults;158
10.7.2;Simulation Results: Process and Actuator Faults;162
10.7.3;Simulation Results: Sensor and Actuator Faults;166
10.8;Conclusions;169
10.9;References;169
11;Applications to Nonideal Reactors;173
11.1;Nonideal Batch Reactors;174
11.2;Nonideal Mixing;175
11.3;Multiphase Batch Reactors;179
11.4;Scaling-up the Information;180
11.4.1;Basic Ideas of Scale-up;180
11.4.2;The Scale-up of Real Batch Reactors;182
11.5;Suggestions and Conclusions;183
11.6;References;184
12;Appendix A Proofs;185
12.1;Proof of Theorem 5.1;185
12.2;Proof of Theorem 5.2;187
12.3;Proof of Theorem 5.3;188
12.4;Proof of Theorem 5.4;189
12.5;Proof of Theorem 6.1;190
12.6;Proof of Theorem 6.2;192
12.7;References;194
13;Index;195