Distributed Model Predictive Control for Plant-Wide Systems

Name: Distributed Model Predictive Control for Plant-Wide Systems
Brand: Wiley
Price: 118.99 EUR
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Shaoyuan Li Yi Zheng(Author)

Wiley (Publisher)

1st Edition

Published on 24. July 2015

328 pages

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978-1-118-92158-6 (ISBN)

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Content

Cover
Title Page
Copyright
Contents
Preface
About the Authors
Acknowledgement
List of Figures
List of Tables
Chapter 1 Introduction
1.1 Plant-Wide System
1.2 Control System Structure of the Plant-Wide System
1.2.1 Centralized Control
1.2.2 Decentralized Control and Hierarchical Coordinated Decentralized Control
1.2.3 Distributed Control
1.3 Predictive Control
1.3.1 What is Predictive Control
1.3.2 Advantage of Predictive Control
1.4 Distributed Predictive Control
1.4.1 Why Distributed Predictive Control
1.4.2 What is Distributed Predictive Control
1.4.3 Advantage of Distributed Predictive Control
1.4.4 Classification of DMPC
1.5 About this Book
Part I Foundation
Chapter 2 Model Predictive Control
2.1 Introduction
2.2 Dynamic Matrix Control
2.2.1 Step Response Model
2.2.2 Prediction
2.2.3 Optimization
2.2.4 Feedback Correction
2.2.5 DMC with Constraint
2.3 Predictive Control with the State Space Model
2.3.1 System Model
2.3.2 Performance Index
2.3.3 Prediction
2.3.4 Closed-Loop Solution
2.3.5 State Space MPC with Constraint
2.4 Dual Mode Predictive Control
2.4.1 Invariant Region
2.4.2 MPC Formulation
2.4.3 Algorithms
2.4.4 Feasibility and Stability
2.5 Conclusion
Chapter 3 Control Structure of Distributed MPC
3.1 Introduction
3.2 Centralized MPC
3.3 Single-Layer Distributed MPC
3.4 Hierarchical Distributed MPC
3.5 Example of the Hierarchical DMPC Structure
3.6 Conclusion
Chapter 4 Structure Model and System Decomposition
4.1 Introduction
4.2 System Mathematic Model
4.3 Structure Model and Structure Controllability
4.3.1 Structure Model
4.3.2 Function of the Structure Model in System Decomposition
4.3.3 Input-Output Accessibility
4.3.4 General Rank of the Structure Matrix
4.3.5 Structure Controllability
4.4 Related Gain Array Decomposition
4.4.1 RGA Definition
4.4.2 RGA Interpretation
4.4.3 Pairing Rules
4.5 Conclusion
Part II Unconstrained Distributed Predictive Control
Chapter 5 Local Cost Optimization-based Distributed Model Predictive Control
5.1 Introduction
5.2 Local Cost Optimization-based Distributed Predictive Contro
5.2.1 Problem Description
5.2.2 DMPC Formulation
5.2.3 Closed-loop Solution
5.2.4 Stability Analysis
5.2.5 Simulation Results
5.3 Distributed MPC Strategy Based on Nash Optimality
5.3.1 Formulation
5.3.2 Algorithm
5.3.3 Computational Convergence for Linear Systems
5.3.4 Nominal Stability of Distributed Model Predictive Control System
5.3.5 Performance Analysis with Single-step Horizon Control Under Communication Failure
5.3.6 Simulation Results
5.4 Conclusion
Appendix
Appendix A. QP problem transformation
Appendix B. Proof of Theorem 5.1
Chapter 6 Cooperative Distributed Predictive Control
6.1 Introduction
6.2 Noniterative Cooperative DMPC
6.2.1 System Description
6.2.2 Formulation
6.2.3 Closed-Form Solution
6.2.4 Stability and Performance Analysis
6.2.5 Example
6.3 Distributed Predictive Control based on Pareto Optimality
6.3.1 Formulation
6.3.2 Algorithm
6.3.3 The DMPC Algorithm Based on Plant-Wide Optimality
6.3.4 The Convergence Analysis of the Algorithm
6.4 Simulation
6.5 Conclusions
Chapter 7 Networked Distributed Predictive Control with Information Structure Constraints
7.1 Introduction
7.2 Noniterative Networked DMPC
7.2.1 Problem Description
7.2.2 DMPC Formulation
7.2.3 Closed-Form Solution
7.2.4 Stability Analysis
7.2.5 Analysis of Performance
7.2.6 Numerical Validation
7.3 Networked DMPC with Iterative Algorithm
7.3.1 Problem Description
7.3.2 DMPC Formulation
7.3.3 Networked MPC Algorithm
7.3.4 Convergence and Optimality Analysis for Networked
7.3.5 Nominal Stability Analysis for Distributed Control Systems
7.3.6 Simulation Study
7.4 Conclusion
Appendix
Appendix A. Proof of Lemma 7.1
Appendix B. Proof of Lemma 7.2
Appendix C. Proof of Lemma 7.3
Appendix D. Proof of Theorem 7.1
Appendix E. Proof of Theorem 7.2
Appendix F. Derivation of the QP problem (7.52)
Part III Constraint Distributed Predictive Control
Chapter 8 Local Cost Optimization Based Distributed Predictive Control with Constraints
8.1 Introduction
8.2 Problem Description
8.3 Stabilizing Dual Mode Noncooperative DMPC with Input Constraints
8.3.1 Formulation
8.3.2 Algorithm Design for Resolving Each Subsystem-based Predictive Control
8.4 Analysis
8.4.1 Recursive Feasibility of Each Subsystem-based Predictive Control
8.4.2 Stability Analysis of Entire Closed-loop System
8.5 Example
8.5.1 The System
8.5.2 Performance Comparison with the Centralized MPC
8.6 Conclusion
Chapter 9 Cooperative Distributed Predictive Control with Constraints
9.1 Introduction
9.2 System Description
9.3 Stabilizing Cooperative DMPC with Input Constraints
9.3.1 Formulation
9.3.2 Constraint C-DMPC Algorithm
9.4 Analysis
9.4.1 Feasibility
9.4.2 Stability
9.5 Simulation
9.6 Conclusion
Chapter 10 Networked Distributed Predictive Control with Inputs and Information Structure Constraints
10.1 Introduction
10.2 Problem Description
10.3 Constrained N-DMPC
10.3.1 Formulation
10.3.2 Algorithm Design for Resolving Each Subsystem-based Predictive Control
10.4 Analysis
10.4.1 Feasibility
10.4.2 Stability
10.5 Formulations Under Other Coordination Strategies
10.5.1 Local Cost Optimization Based DMPC
10.5.2 Cooperative DMPC
10.6 Simulation Results
10.6.1 The System
10.6.2 Performance of Closed-loop System under the N-DMPC
10.6.3 Performance Comparison with the Centralized MPC and the Local Cost Optimization based MPC
10.7 Conclusions
Part IV Application
Chapter 11 Hot-Rolled Strip Laminar Cooling Process with Distributed Predictive Control
11.1 Introduction
11.2 Laminar Cooling of Hot-rolled Strip
11.2.1 Description
11.2.2 Thermodynamic Model
11.2.3 Problem Statement
11.3 Control Strategy of HSLC
11.3.1 State Space Model of Subsystems
11.3.2 Design of Extended Kalman Filter
11.3.3 Predictor
11.3.4 Local MPC Formulation
11.3.5 Iterative Algorithm
11.4 Numerical Experiment
11.4.1 Validation of Designed Model
11.4.2 Convergence of EKF
11.4.3 Performance of DMPC Comparing with Centralized MPC
11.4.4 Advantages of the Proposed DMPC Framework Comparing with the Existing Method
11.5 Experimental Results
11.6 Conclusion
Chapter 12 High-Speed Train Control with Distributed Predictive Control
12.1 Introduction
12.2 System Description
12.3 N-DMPC for High-Speed Trains
12.3.1 Three Types of Force
12.3.2 The Force Analysis of EMUs
12.3.3 Model of CRH2
12.3.4 Performance Index
12.3.5 Optimization Problem
12.4 Simulation Results
12.4.1 Parameters of CRH2
12.4.2 Simulation Matrix
12.4.3 Results and Some Comments
12.5 Conclusion
Chapter 13 Operation Optimization of Multitype Cooling Source System Based on DMPC
13.1 Introduction
13.2 Structure of Joint Cooling System
13.3 Control Strategy of Joint Cooling System
13.3.1 Economic Optimization Strategy
13.3.2 Design of Distributed Model Predictive Control in Multitype Cold Source System
13.4 Results and Analysis of Simulation
13.5 Conclusion
References
Index
EULA

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Distributed Model Predictive Control for Plant-Wide Systems

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