Plantwide Control (eBook, ePUB)

Recent Developments and Applications
Redaktion: Rangaiah, Gade Pandu; Kariwala, Vinay

• Format: ePub

Produktbeschreibung

The use of control systems is necessary for safe and optimal operation of industrial processes in the presence of inevitable disturbances and uncertainties. Plant-wide control (PWC) involves the systems and strategies required to control an entire chemical plant consisting of many interacting unit operations. Over the past 30 years, many tools and methodologies have been developed to accommodate increasingly larger and more complex plants. This book provides a state-of-the-art of techniques for the design and evaluation of PWC systems. Various applications taken from chemical, petrochemical, biofuels and mineral processing industries are used to illustrate the use of these approaches. This book contains 20 chapters organized in the following sections: * Overview and Industrial Perspective * Tools and Heuristics * Methodologies * Applications * Emerging Topics With contributions from the leading researchers and industrial practitioners on PWC design, this book is key reading for researchers, postgraduate students, and process control engineers interested in PWC.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 240
• Erscheinungstermin: 9. Januar 2012
• Englisch
• ISBN-13: 9781119940883
• Artikelnr.: 37356728

Autorenporträt

Prof. Gade Pandu Rangaiah is currently Professor and Deputy Head in the Department of Chemical & Biomolecular Engineering at the National University of Singapore. His research interests are in control, modeling and optimization of chemical, petrochemical and related processes. Prof. Rangaiah published nearly 120 papers in international journals and presented around 90 papers in conferences. He received several awards for his teaching including Annual Teaching Excellence Awards from the National University of Singapore for four consecutive years. Prof. Rangaiah edited two books (one on multi-objective optimization and another on global optimization) published by World Scientific. Dr Vinay Kariwala is an Assistant Professor in the School of Chemical and Biomedical Engineering at the Nanyang Technological University, Singapore. He got his Ph.D. degree in Chemical Engineering (Computer Process Control) from the University of Alberta, Canada, in 2004. During 2004-2005, he worked as a postdoctoral fellow at the Norwegian University of Science and Technology, Trondheim, Norway. He has published more than 25 papers in international journals and refereed conference proceedings in the broad areas of plant-wide control and control structure design. Recently, his contributions were recognized with the best reviewer award by Journal of Process Control for the year 2009.

Inhaltsangabe

Preface Section I: Overview and Perspective 1 Introduction 1.1 Background 1
1.2 Plant-Wide Control 2 1.3 Scope and Organization of the Book 4
References 10 2 Industrial Perspective on Plant-Wide Control 2.1
Introduction 1 2.2 Design Environment 3 2.3 Disturbances and Measurement
System Design 6 2.4 Academic Contributions 8 2.5 Conclusions 11 References
12 Section II: Tools and Heuristics 3 Control Degrees of Freedom Analysis
for Plant-Wide Control of Industrial Processes 3.1 Introduction 2 3.2
Control Degrees of Freedom (CDOF) 4 3.3 Computation Methods for Control
Degrees of Freedom (CDOF): A Review 7 3.4 Computation of CDOF Using
Flowsheet-Oriented Method 14 3.4.1 Computation of Restraining Number for
Unit Operations 16 3.5 Application of Flowsheet-Oriented Method to
Distillation Columns and the Concept of Redundant Process Variables 19 3.6
Application of Flowsheet-Oriented Method to Compute CDOF to Complex
Integrated Processes 22 3.7 Conclusions 23 References 24 4 Selection of
Controlled Variables Using Self-Optimizing Control Method 4.1 Introduction
2 4.2 General Principle 4 4.3 Brute-Force Optimization Approach for CV
Selection 8 4.4 Local Methods 11 4.4.1 Minimum Singular Value (MSV) Rule 12
4.4.2 Exact Local Method 14 4.4.3 Optimal Measurement Combination 16
4.4.3.1 Null Space Method 16 4.4.3.2 Explicit Solution 17 4.4.3.3 Toy
Example 19 4.5 Branch and Bound Methods 21 4.6 Constraint Handling 23 4.7
Case Study: Forced Circulation Evaporator 26 4.8 Conclusions and Discussion
32 4.9 Acknowledgements 34 References 34 5 Input-Output Pairing Selection
for Design of Decentralized Controller 5.1 Introduction 2 5.1.1 State of
the Art 3 5.2 Relative Gain Array and Variants 5 Steady-State RGA 6 5.2.2
Niederlinski Index 8 5.2.3 The Dynamic Relative Gain Array 9 5.2.4 The
Effective Relative Gain Array 11 5.2.5 The Block Relative Gain 12 5.2.6
Relative Disturbance Gain Array 14 5.3 µ-Interaction Measure 15 5.4 Pairing
Analysis Based on the Controllability and Observability 17 5.4.1 The
Participation Matrix 17 5.4.2 The Hankel Interaction Index Array 19 5.4.3
The Dynamic Input-Output Pairing Matrix 19 Input-Output Pairing for
Uncertain Multivariable Plants 21 RGA in the Presence of Statistical
Uncertainty 22 RGA in the Presence of Norm-Bounded Uncertainties 23 DIOPM
and the Effect of Uncertainty 26 Input-Output Pairing for Nonlinear
Multivariable Plants 28 5.6.1 Relative Order Matrix 29 5.6.2 The Nonlinear
RGA 30 5.7 Conclusions and Discussion 31 References 33 6 Heuristics for
Plantwide Control 6.1 Introduction 2 6.2 Basics of Heuristic Plantwide
Control 4 6.2.1 Plumbing 5 6.2.2 Recycle 6 6.2.2.1 Effect of Recycle on
Time Constants 6 6.2.2.2 Snowball Effects in Liquid Recycle Systems 7
6.2.2.3 Gas Recycle Systems 8 6.2.3 Fresh Feed Introduction 8 6.2.3.1
Ternary Example 9 6.2.3.2 Control Structures 11 6.2.3.3 Ternary Process
with Altered Volatilities 12 6.2.4 Energy Management and Integration 12
6.2.5 Controller Tuning 13 6.2.5.1 Flow and Pressure Control 13 6.2.5.2
Level Control 14 6.2.5.3 Composition and Temperature Control 16 6.2.5.4
Interacting Control Loops 17 6.2.6 Throughput Handle 18 6.3 Application to
HDA Process 18 6.3.1 Process Description 19 6.3.2 Application of Plantwide
Control Heuristics 20 6.3.2.1 Throughput Handle 20 6.3.2.2 Maximum Gas
Recycle 20 6.3.2.3 Component Balances (Downs Drill) 20 6.3.2.4 Flow Control
in Liquid Recycle Loop 21 6.3.2.5 Product Quality and Constraint Loops 21
6.4 Conclusion 21 7 Throughput Manipulator Location Selection for Economic
Plantwide Control 7.1 Introduction 2 7.2 Throughput Manipulation, Inventory
Regulation and Plantwide Variability Propagation 3 7.3 Quantitative Case
Studies 6 7.3.1 Case Study I: Recycle Process 7 7.3.1.1 Alternative Control
Structures 7 7.3.1.2 Quantitative Back-Off Results 8 7.3.1.3 Salient
Observations 10 7.3.2 Case Study II: Recycle Process with Side Reaction 11
7.3.2.1 Economically Optimal Process Operation 11 7.3.2.2 Self Optimizing
Variables for Unconstrained Degrees of Freedom 14 7.3.2.3 Plantwide Control
System Design 15 7.3.2.4 Dynamic Simulation Results 18 7.4 Discussion 19
7.5 Conclusions 23 7.6 Acknowledgments 23 7.7 Supplementary Information 23
References 24 8 Influence of Process Variability Propagation in Plant-Wide
Control 8.1 Introduction 2 8.2 Theoretical Background 5 8.3 Local Unit
Operation Control 12 8.3.1 Heat Exchanger 12 8.3.2 Extraction Process 13
8.4 Inventory Control 15 8.4.1 Pressure Control in Gas Headers 15 8.4.2
Parallel Unit Operations 17 8.4.3 Liquid Inventory Control 18 Plant-Wide
Control Examples 21 8.5.1 Distillation Column Control 21 8.5.2
Esterification Process 22 8.6 Conclusion 25 References 27 Section III:
Methodologies 9 A Review of Plant-Wide Control Methodologies and
Applications 9.1 Introduction 1 9.2 Review and Approach-Based
Classification of PWC Methodologies 3 9.2.1 Heuristics-Based PWC Methods 4
9.2.2 Mathematical-Based PWC Methods 6 9.2.3 Optimization-Based PWC Methods
8 9.2.4 Mixed PWC Methods 9 9.3 Structure-Based Classification of PWC
Methodologies 12 9.4 Processes Studied in PWC Applications 14 9.5
Comparative Studies on Different Methodologies 16 9.6 Concluding Remarks 18
References 20 10 Integrated Framework of Simulation and Heuristics for
Plant-Wide Control System Design 10.1 Introduction 1 10.2 HDA Process:
Overview and Simulation 2 10.2.1 Process Description 2 10.2.2 Steady-State
and Dynamic Simulation 4 10.3 Integrated Framework Procedure and
Application to HDA Plant 5 10.4 Evaluation of the Control System 17 10.5
Conclusions 18 References 20 11 Economic Plantwide Control Introduction 1
Control Layers and Time Scale Separation 3 Plantwide Control Procedure 7
Degrees of Freedom for Operation 9 11.5 Skogestad's Plantwide Control
Procedure 12 Top-Down Part 12 Discussion 29 Conclusion 30 REFERENCES 30 12
Performance Assessment of Plant-Wide Control Systems 12.1 Introduction 2
12.2 Desirable Qualities of a Good Performance Measure 4 12.3 Performance
Measure Based on Steady State: Steady-State Operating Cost/Profit 5 12.4
Performance Measures Based on Dynamics 6 12.4.1 Process Settling Time Based
on Overall Absolute Component Accumulation 6 12.4.2 Process Settling Time
Based on Plant Production 7 12.4.3 Dynamic Disturbance Sensitivity (DDS) 8
12.4.4 Deviation from the Production Target (DPT) 8 12.4.5 Total Variation
(TV) in Manipulated Variables 10 12.5 Application of the Performance
Measures to the HDA Plant Control Structure 11 12.5.1 Steady-State
Operating Cost 12 12.5.2 Process Settling Time Based on Overall Absolute
Component Accumulation 12 12.5.3 Process Settling Time Based on Plant
Production 13 12.5.4 Dynamic Disturbance Sensitivity (DDS) 14 12.5.5
Deviation from the Production Target (DPT) 15 12.5.6 Total Variation (TV)
in Manipulated Variables 15 12.6 Application of the Performance Measures
for Comparing PWC Systems 15 12.7 Discussion and Recommendations 17 12.7.1
Disturbances and Set-Point Changes 17 12.7.2 Performance Measures 19 12.8
Concluding Remarks 21 References 21 Section IV: Applications Studies 13
Design and Control of a Cooled Ammonia Reactor 13.1 Introduction 2 13.2
Cold-Shot Process 4 13.2.1 Process Flowsheet 4 13.2.2 Equipment Sizes,
Capital and Energy Costs 6 13.3 Cooled-Reactor Process 7 13.3.1 Process
Flowsheet 7 13.3.2 Reaction Kinetics 9 13.3.3 Optimum Economic Design of
the Cooled-Reactor Process 10 13.3.3.1 Effect of Pressure 10 13.3.3.2
Effect of Reactor Size 12 13.3.4 Comparison of Cold-Shot and Cooled-Reactor
Processes 12 13.4 Control 13 13.5 Conclusion 16 13.6 Acknowledgement 16
References 16 14 Design and Plant-Wide Control of a Biodiesel Plant 14.1
Introduction 1 14.2 Steady-State Plant Design and Simulation 4 14.2.1
Process Design 4 14.2.1.1 Feed and Product Specifications 4 14.2.1.2
Reaction Section 5 14.2.1.3 Separation Section 6 14.2.2 Process Flowsheet
and HYSYS Simulation 8 14.3 Optimization of Plant Operation 10 14.4
Application of IFSH to Biodiesel Plant 12 14.5 Validation of the Plant-Wide
Control Structure 18 14.6 Conclusions 20 References 20 15 Plant-Wide
Control of a Reactive Distillation Process 15.1 Introduction 2 15.2 Design
of Ethyl Acetate Reactive-Distillation Process 3 15.2.1 Kinetic and
Thermodynamic Models 3 15.2.2 The Process Flowsheet 4 15.2.3 Comparison of
the Process Using Either Homogeneous or Heterogeneous Catalyst 6 15.3
Control Structure Development of the Two Catalyst Systems 8 15.3.1
Inventory Control Loops 8 15.3.2 Product Quality Control Loops 10 15.3.3
Tuning of the Two Temperature Control Loops 12 Closed-Loop Simulation
Results 13 15.3.5 Summary of PWC Aspects 15 15.4 Conclusions 17 References
17 16 Control System Design of a Crystallizer Train for Para-Xylene
Recovery 16.1 Introduction 3 16.1 Process 5 16.2 Description 5 16.2.1
Para-Xylene Production Process 5 16.2.2 Para-Xylene Recovery Based on
Crystallization Technology 6 16.3 Process Model 8 16.3.1 Crystallizer
(Units 1-5) 8 16.3.2 Cyclone Separator (Units 9, 11) 10 16.3.3 Centrifugal
Separator (Units 8, 10) 11 16.3.4 Overall Process Model 12 16.4 Control
System Design 14 16.4.1 Basic Regulatory Control 14 16.4.2 Steady State
Optimal Operation Policy 15 16.4.2.1 Maximization of Para-Xylene Recovery
15 16.4.2.2 Load Distribution 17 16.4.3 Design of Optimizing Controllers 19
16.4.3.1 Multiloop Controller 20 16.4.3.2 Multivariable Controller 20
16.4.3.3 Simulation 21 16.4.4 Incorporation of Steady State Optimizer 22
16.4.4.1 LP Based Steady State Optimizer 22 16.4.4.2 Simulation 24 16.4.5
Justification of MPC Application 25 16.5 Conclusions 26 16.6 5.A Linear
Steady State Model and Constraints 27 References 29 17 Modeling and Control
of Industrial Off-Gas Systems 17.1 Introduction 3 17.2 Process Description
5 Off-Gas System Model Development 7 17.3.1 Roaster off-Gas Train 8 17.3.2
Furnace Off-Gas Train 12 17.4 Control of Smelter Off-Gas Systems 14 17.4.1
Roaster Off-Gas System 15 17.4.1.1 Degree of Freedom Analysis 15 17.4.1.2
Definition of Optimal Operation 16 17.4.1.3 Optimization 17 17.4.1.4
Production Rate 19 17.4.1.5 Structure of the Regulatory and Supervisory
Control 21 17.4.1.6 Validation of the Proposed Control Structure 22 17.4.2
Furnace Off-Gas System 22 17.4.2.1 Manipulated Variables and Degree of
Freedom Analysis 22 17.4.2.2 Definition of Optimal Operation 23 17.4.2.3
Optimization 24 17.4.2.4 Production Rate 26 17.4.2.5 Structure of the
Regulatory and Supervisory Control Layer 27 17.4.2.6 Validation of the
Proposed Control Structures 28 17.5 Conclusion 28 Notation 29 Subscripts 32
References 33 Section V: Emerging Topics 18 Plant-Wide Control via a
Network of Autonomous Controllers 18.1 Introduction 2 18.2 Process and
Controller Networks 7 18.2.1 Representation of Process Network 7 18.2.2
Representation of Control Network 10 Plant-Wide Stability Analysis Based on
Dissipativity 13 18.4 Controller Network Design 18 18.4.1 Transformation of
the Network Topology 18 Plant-Wide Connective Stability 25 18.4.3
Performance Design 27 18.5 Case Study 31 18.5.1 Process Model 32 18.5.2
Distributed Control System Design 34 18.6 Discussions and Conclusion 35
References 40 19 Co-Ordinated, Distributed Plant-Wide Control 19.1
Introduction 2 Co-Ordination Based Plant-Wide Control 8 19.2.1 Price-Driven
Co-Ordination 11 19.2.1.1 The Price Decomposition Principle 11 19.2.1.2
Algorithm 12 Price-Driven Co-Ordination Procedure: 14 19.2.1.4 Summary 15
19.2.2 Augmented Price-Driven Method 15 19.2.2.1 The Newton Based Price
Update Method as a Negotiation Principle 17 19.2.3 Resource Allocation
Co-Ordination 18 19.2.3.1 Resource Allocation Principle 18 19.2.3.2
Algorithm and Interpretation 18 19.2.4 Prediction-Driven Co-Ordination 21
19.2.4.1 Prediction-Driven Principle 21 19.2.4.2 Algorithm and
Interpretation 23 19.2.4.3 Prediction Driven Co-Ordination Procedure 23
19.2.5 Economic Interpretation 24 19.3 Case Studies 25 19.3.1 A Pulp Mill
Process 25 19.3.1.1 Problem Formulation 25 Plant-Wide Coordination and
Performance Comparison 27 19.3.2 A Forced-Circulation Evaporator System 29
19.3.2.1 Problem Formulation 30 Plant-Wide Co-Ordination and Performance 32
19.4 The Future 34 References 38 20 Determination of Plant-Wide Control
Loop Configuration and Eco-Efficiency 20.1 Introduction 1 20.2 Relative
Gain Array (RGA) and Relative Exergy Gain Array (REA) 4 20.2.1 Relative
Gain Array (RGA) 4 20.2.2 Relative Exergy Array (REA) 6 20.2.2.1 Exergy 6
20.2.2.2 Relative Exergy Array 8 20.3 Exergy Calculation Procedure 10 20.4
Case Study 13 20.4.1 Distillation Column 13 20.4.2 Case Study 2 15 20.5
Summary 19 References