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Reactor network synthesis with guaranteed robust performance / Titelei/Inhaltsverzeichnis
Reactor network synthesis with guaranteed robust performance / Titelei/Inhaltsverzeichnis
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Chapter
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I–XIV
Titelei/Inhaltsverzeichnis
I–XIV
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1–16
1 Introduction
1–16
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1.1 Reactor network synthesis
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1.1.1 Motivation
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1.1.2 Task
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1.1.3 Methods
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1.2 Design of decentralized control systems
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1.2.1 Tasks
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1.2.2 Methods
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1.3 Simultaneous process and control system design
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1.3.1 Motivation
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1.3.2 Methods
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1.4 Content and goals of this work
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1.4.1 Overview
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1.4.2 New features of this work
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17–29
2 Some Preliminaries
17–29
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2.1 Dynamic systems
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2.2 Eigenvalue and spectral abscissa functions
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2.3 Lyapunov stability
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2.4 Dynamic response
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2.5 Extension to differential-algebraic systems
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30–46
3 Open-loop reactor network synthesis
30–46
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3.1 Structuredmodeling of reactor networks
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3.1.1 A structured representation of reactor network models
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3.1.2 Models of Subsystem 1 to N
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3.1.3 Models of subsystems N + 1 and N +2
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3.1.4 Modeling flow connections
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3.1.5 A dynamicmodel of the network
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3.1.6 Idle reactors in open-loop reactor networks
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3.2 Problemformulation
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3.2.1 Eigenvalue constraint for open-loop reactor network synthesis
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3.2.2 Continuity analysis of the proposed eigenvalue constraint
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3.2.3 A direct problemformulation
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3.2.4 Problemreformulation
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3.3 Summary
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47–59
4 Simultaneous design of reactor network and its decentralized control system
47–59
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4.1 Modeling of reactor networks with decentralized control structure
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4.1.1 A closed-loop reactor networkmodel
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4.1.2 Complementarity constraints for control structure selection
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4.1.3 Idle reactors and controllers
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4.1.4 Structural constraints
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4.1.5 Structural properties of the closed-loop model
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4.2 Problemformulation
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4.2.1 Eigenvalue constraint for simultaneous reactor network and control systemsynthesis
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4.2.2 Problemformulation
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4.3 Summary
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60–106
5 Solution methods
60–106
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5.1 Discrete-continuous optimization
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5.1.1 Mixed-integer nonlinear program
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5.1.2 General concepts to solveMINLP
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5.1.3 Solutionmethods for convexMINLP
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5.1.4 Solution methods for non-convex MINLP
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5.1.5 Generalized disjunctive programming
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5.2 Mathematical programs with complementarity constraints
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5.2.1 MPCC versus NLP
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5.2.2 Solutionmethods forMPCC
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5.2.3 Relationship toMINLP
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5.3 Semi-infinite programming
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5.3.1 Local solutionmethods for SIP
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5.3.2 Global solutionmethods for SIP
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5.3.3 A robust design method: Normal vector approach
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5.4 Eigenvalue optimization
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5.4.1 Relation to semi-definite programming
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5.4.2 Solution methods for EVO: Non-smooth optimization
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5.4.3 Solution methods for EVO: Smoothing techniques
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5.5 Challenges of solving the derived reactor network synthesis problem
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5.6 A proposed two-step hybrid solution method
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5.6.1 Step 1: Mixed-integer problem without uncertainty
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5.6.2 Step 2: Robust optimization problem
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5.7 Implementation
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107–132
6 Case study of allyl chloride production
107–132
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6.1 Open-loop reactor network design with robust stability
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6.1.1 Problemsetting
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6.1.2 Design results
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6.2 Simultaneous reactor network and control system design for fast response
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6.2.1 Closed-loop reactor networkmodeling
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6.2.2 Problemsetting
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6.2.3 Results and discussion
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6.2.4 Comparison with established sequential design
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6.3 Computational experience
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133–140
7 Summary and outlook
133–140
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7.1 Contributions and summary of this work
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7.2 Future research directions
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7.2.1 Extensions regarding to the guaranteed robust dynamic properties
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7.2.2 Extensions regarding optimization methods
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7.2.3 Extension to control structure selection for linear system
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7.2.4 Other possible extensions and improvements
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141–157
Appendices
141–157
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A Extension of the reactor network model to PFR
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B Proof of Proposition 3.2.1
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C Proof of Proposition 3.2.2
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D Parametric optimization problems
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E Proof of Theorem 5.3.10
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158–176
Bibliography
158–176
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Reactor network synthesis with guaranteed robust performance , page I - XIV
Titelei/Inhaltsverzeichnis
Autoren
Xiao Zhao
DOI
doi.org/10.51202/9783186952035-I
ISBN print: 978-3-18-395203-8
ISBN online: 978-3-18-695203-5
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doi.org/10.51202/9783186952035-I
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