Efstratios N. Pistikopoulos - Multi-parametric Optimization and Control
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- Название:Multi-parametric Optimization and Control
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Multi-parametric Optimization and Control: краткое содержание, описание и аннотация
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ecent developments in multi-parametric optimization and control
Multi-Parametric Optimization and Control Researchers and practitioners can use the book as reference. It is also suitable as a primary or a supplementary textbook. Each chapter looks at the theories related to a topic along with a relevant case study. Topic complexity increases gradually as readers progress through the chapters. The first part of the book presents an overview of the state-of-the-art multi-parametric optimization theory and algorithms in multi-parametric programming. The second examines the connection between multi-parametric programming and model-predictive control—from the linear quadratic regulator over hybrid systems to periodic systems and robust control.
The third part of the book addresses multi-parametric optimization in process systems engineering. A step-by-step procedure is introduced for embedding the programming within the system engineering, which leads the reader into the topic of the PAROC framework and software platform. PAROC is an integrated framework and platform for the optimization and advanced model-based control of process systems.
Uses case studies to illustrate real-world applications for a better understanding of the concepts presented Covers the fundamentals of optimization and model predictive control Provides information on key topics, such as the basic sensitivity theorem, linear programming, quadratic programming, mixed-integer linear programming, optimal control of continuous systems, and multi-parametric optimal control An appendix summarizes the history of multi-parametric optimization algorithms. It also covers the use of the parametric optimization toolbox (POP), which is comprehensive software for efficiently solving multi-parametric programming problems.
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6 Chapter 6Figure 6.1 The interpretation of mp‐MIQP problems as a combination of severa...Figure 6.2 The schematic representation of the example of a comparison proce...Figure 6.3 The detection of the intersection between two critical regions, 
Figure 6.4 The difference in the partitioning of a critical region due to co...Figure 6.5 The schematic representation of the envelopes of solutions. In (a...Figure 6.6 The solution of problem (6.9). In (a) the partitioning of the par...
7 Chapter 7Figure 7.1 The general framework for the solution of mp‐MIQP problems.Figure 7.2 A schematic representation of the global optimization approach fo...Figure 7.3 A schematic example of a branch‐and‐bound tree.Figure 7.4 A schematic perspective on the different comparison procedures, w...
8 Chapter 8Figure 8.1 The problem statistics of the test sets 
“POP_mpLP1” and 
“POP_...Figure 8.2 The problem statistics of the test sets 
“POP_mpMILP1” and 
“PO...Figure 8.3 The structure of the graphical user interface (GUI) of POP.Figure 8.4 The performance of the geometrical, combinatorial, and connected‐...Figure 8.5 The analysis of the computational effort spent on different aspec...Figure 8.6 The analysis of the computational effort spent on different aspec...Figure 8.7 The performance of the decomposition algorithm for the different ...Figure 8.8 The analysis of the computational effort spent on different compa...Figure 8.9 The analysis of the computational effort spent on different compa...
9 Chapter 10Figure 10.1 The concept of the receding horizon. A set of 
manipulated inpu...Figure 10.2 The solution of the mp‐MPC example problem. (a) The partitioning...
10 Chapter 11Figure 11.1 The solution of the mp‐MPC example problem. Left: (a) The partit...Figure 11.2 Comparison of the feasible regions between (a) the hybrid mp‐MPC...Figure 11.3 The solution of the mp‐MPC with disturbance example problem. (a)...Figure 11.4 The solution of the mp‐MPC with disturbance example problem. (a)...Figure 11.5 Indicative snapshots of the solution of the explicit reference t...Figure 11.6 Indicative snapshots of the solution of the explicit reference t...
11 Chapter 12Figure 12.1 A step‐by‐step outline of the PAROC framework.Figure 12.2 An outline of the model approximation procedure typically used w...Figure 12.3 Software interactions for the implementation of the closed‐loop ...Figure 12.4 Software interactions for the implementation of the closed‐loop ...Figure 12.5 Graphical representation of the binary distillation column examp...Figure 12.6 Critical regions for the solution of the mp‐MHE problem of the b...Figure 12.7 Critical regions for the solution of the mp‐MPC problem of the b...Figure 12.8 Closed loop validation results. Both the mp‐MHE and mp‐MPC schem...Figure 12.9 Step response (a) and impulse response (b) of the tank approxima...Figure 12.10 Closed‐loop validation results for liquid volume set‐point trac...
Guide
1 Cover Page
2 Wiley Series in
3 Title Page
4 Copyright
5 Dedication
6 Table of Contents
7 Part 1 Multi‐parametric Optimization
8 Part II Multi‐parametric Model Predictive Control
9 Begin Reading
10 A Appendix for the mp‐MPC Chapter 10
11 Appendix for the mp‐MPC Chapter 11
12 Index
13 WILEY END USER LICENSE AGREEMENT
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