Control and Monitoring of Chemical Batch Reactors

Series Editors' Foreword

Preface

Acknowledgements

Contents

Introduction

Overview of the Main Topics

The Batch Reactor

The Case Study

Identification of Mathematical Models

Thermal Stability

Control of Batch Reactors

Fault Diagnosis for Chemical Batch Reactors

Applications to Non-ideal Reactors

Suggested Reading Paths

The Chemical Batch Reactor

Ideal Chemical Reactors

The Rate of Chemical Reactions

The Ideal Batch Reactor

Conservation of Mass

Conservation of Energy

Introducing the Case Study

Components

Reactions

A General Model for a Network of Nonchain Reactions

Measuring the Reactor Status

Measurements Quality

Online Measurements

Offline Measurements

Manipulating the Reactor Status

Conclusions

References

Identification of Kinetic Parameters

Bayesian Approach and Popper's Falsificationism

Experimental Data and Mathematical Models

Maximum Likelihood and Least Squares Criteria

Optimization for Models Linear in the Parameters

Optimization for Models Nonlinear in the Parameters

Steepest Descent Algorithm

Newton-Raphson Algorithm

Levenberg-Marquardt Algorithm

Implicit Models

Statistical Analysis of the Results

Case Study: Identification of Reduced Kinetic Models

Reduced Models

Generation of Data for Identification

Estimating the Kinetic Parameters

Estimating the Heats of Reaction

Validation of the Reduced Models

Conclusions

References

Thermal Stability

Runaway in Chemical Batch Reactors

Dimensionless Mathematical Model

Adiabatic Reactor

Isoperibolic Reactor

The Semenov Theory

Geometry-based Runaway Criteria

Sensitivity-based Runaway Criteria

Operation Limited by the Maximum Allowable Temperature

Case Study: Runaway Boundaries

Conclusions

References

Model-based Control

Control Strategies for Batch Reactors

PID Regulator

Model Predictive Control

Feedback Linearization

Input-Output Linearization

Generic Model Control

State-Space Model for Control Design

Estimation of the Heat Released by Reaction

Model-Based Nonlinear Observer

Model-Free Approaches

Approach Based on Universal Interpolators

A Classical Model-Free Approach

Adaptive Two-Loop Control Scheme

Case Study: Temperature Control

Simulation Model

Design of the Controller-Observer Scheme

Discussion of Results

Comparison with the PID Controller

Conclusions

References

Fault Diagnosis

Fault Diagnosis Strategies for Batch Reactors

Model-Free Approaches

Model-Based Approaches

Basic Principles of Model-Based Fault Diagnosis

Residual Generation

Decision Making System and Fault Isolation

Fault Diagnosis for Chemical Batch Reactors

Fault Characterization

Architecture of the Fault Diagnosis Scheme

Sensor Fault Diagnosis

Residuals Generation and Fault Isolation

Determination of the Healthy Signal

Voter procedure

Actuator and Process Fault Diagnosis

Fault Detection

Fault Isolation and Identification

Decoupling Sensor Faults from Process and Actuator Faults

Case Study: Fault Diagnosis

Simulation Results: Sensor Faults

Simulation Results: Process and Actuator Faults

Simulation Results: Sensor and Actuator Faults

Conclusions

References

Applications to Nonideal Reactors

Nonideal Batch Reactors

Nonideal Mixing

Multiphase Batch Reactors

Scaling-up the Information

Basic Ideas of Scale-up

The Scale-up of Real Batch Reactors

Suggestions and Conclusions

References

Appendix A Proofs

Proof of Theorem 5.1

Proof of Theorem 5.2

Proof of Theorem 5.3

Proof of Theorem 5.4

Proof of Theorem 6.1

Proof of Theorem 6.2

References

Index