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Process Systems Engineering, 5. Process Dynamics, Control, Monitoring, and Identification

  1. Krist V. Gernaey1,
  2. Jarka Glassey2,
  3. Sigurd Skogestad3,
  4. Stefan Krämer4,
  5. Andreas Weiß4,
  6. Sebastian Engell5,
  7. Efstratios N. Pistikopoulos6,
  8. David B. Cameron7

Published Online: 15 OCT 2012

DOI: 10.1002/14356007.o22_o09

Ullmann's Encyclopedia of Industrial Chemistry

Ullmann's Encyclopedia of Industrial Chemistry

How to Cite

Gernaey, K. V., Glassey, J., Skogestad, S., Krämer, S., Weiß, A., Engell, S., Pistikopoulos, E. N. and Cameron, D. B. 2012. Process Systems Engineering, 5. Process Dynamics, Control, Monitoring, and Identification. Ullmann's Encyclopedia of Industrial Chemistry. .

Author Information

  1. 1

    Technical University of Denmark, Department of Chemical and Biochemical Engineering, Lyngby, Denmark

  2. 2

    Newcastle University, Faculty of Science, Agriculture and Engineering, Newcastle upon Tyne, United Kingdom

  3. 3

    Norwegian University of Science and Technology, Department of Chemical Engineering, Trondheim, Norway

  4. 4

    INEOS, Köln, Germany

  5. 5

    Technical University of Dortmund, Department of Chemical Engineering, Dortmund, Germany

  6. 6

    Imperial College London, Department of Chemical Engineering, London, United Kingdom

  7. 7

    IBM Global Business Services, Kolbotn, Norway

  1. The topic Process Systems Engineering was coordinated by Rafiqul Gani, Krist Gernaey, and Gurkan Sin.

Publication History

  1. Published Online: 15 OCT 2012

Abstract

The article contains sections titled:

1.

Introduction

2.

Process Monitoring

2.1.

Introduction

2.2.

Critical Process Parameter Measurement

2.3.

Monitoring Tools

2.3.1.

Data Compression Methods for Multivariate Statistical Process Control (MSPC)

2.3.2.

Multiway MSPC

2.4.

Seed Quality Monitoring Case Study

2.5.

Alternative Methods

2.6.

RBF-Based Monitoring Case Study

3.

Plantwide Control

3.1.

Introduction

3.2.

Previous Work

3.3.

Degrees of Freedom for Operation

3.4.

Skogestad's Plantwide Control Procedure

3.5.

Comparison of the Procedures of Luyben and Skogestad

3.6.

Conclusion

4.

Process Control of Batch Processes

4.1.

Introduction

4.2.

Batch Process Management

4.2.1.

Recipe-Driven Operation Based on ANSI/ISA-88 (IEC 61512-1)

4.2.2.

Recipes

4.2.3.

Control Hierarchy

4.2.4.

Sequential and Logic Control

4.2.5.

Regulatory Control

4.2.6.

Planning and Scheduling in Multipurpose and Multiproduct Plants

4.3.

Quality Control and Batch-Process Monitoring

4.3.1.

Measurement and Control of Quality Parameters

4.3.2.

Inferential Measurements

4.3.3.

State Estimation

4.3.4.

Calorimetry

4.3.5.

Detection of Abnormal Situations and Statistical Process Control

4.4.

Optimal Operation of Single-Batch Processes

4.4.1.

Trajectory Optimization

4.4.2.

Implementation of the Optimized Trajectories

4.4.3.

On-line Optimization

4.4.4.

Optimal Control Along Constraints

4.4.5.

Golden Batch Approach

4.5.

Batch-to-Batch Control

4.5.1.

General

4.5.2.

Iterative Batch-to-Batch Optimization

4.6.

Summary

5.

Model Predictive Control: Multiparametric Programming

5.1.

Introduction

5.2.

Multiparametric Programming Theory

5.2.1.

Multiparametric Nonlinear Programming

5.2.2.

Bilevel/Multilevel, Hierarchical Programming

5.2.3.

Constrained Dynamic Programming

5.2.4.

Global Optimization of Multiparametric Mixed-Integer Linear Programming

5.3.

Explicit/Multiparametric MPC Theory

5.3.1.

Explicit Control and Model Order Reduction

5.3.2.

Robust Explicit MPC

5.4.

MPC-on-a-Chip–Applications

5.5.

A Framework for Multiparametric Programming and Explicit MPC

5.6.

Concluding Remarks and Future Outlook

6.

On-Line Applications of Dynamic Process Simulators

6.1.

Introduction and Historical Background

6.1.1.

Dynamic Simulation

6.1.2.

Historical Perspective: From Design and Training to Full Lifecycle Operations

6.2.

Architecture for On-Line Simulation

6.3.

Challenges in the Use of Dynamic Process Models for On-Line and Real-Time Applications

6.3.1.

Data Security and Corporate Information Policy

6.3.2.

Data Communications and Quality

6.3.3.

Synchronization

6.3.4.

Model Quality

6.3.5.

Thermodynamics

6.4.

Pipeline Management and Leak-Detection

6.5.

Management of Multiphase and Subsea Oil Production

6.6.

The On-Line Facility Simulator

6.7.

Conclusion and Future Directions

7.

Acknowledgments