Multi-Parametric Programming

Multi-Parametric Programming
Author: Efstratios N. Pistikopoulos
Publisher: Wiley-VCH
Total Pages: 336
Release: 2007-04-09
Genre: Business & Economics
ISBN:

This first book to cover all aspects of multi-parametric programming and its applications in process systems engineering includes theoretical developments and algorithms in multi-parametric programming with applications from the manufacturing sector and energy and environment analysis. The volume thus reflects the importance of fundamental research in multi-parametric programming applications, developing mechanisms for the transfer of the new technology to industrial problems. Since the topic applies to a wide range of process systems, as well as due to the interdisciplinary expertise required to solve the challenge, this reference will find a broad readership. Inspired by the leading authority in the field, the Centre for Process Systems Engineering at Imperial College London.

Explicit Nonlinear Model Predictive Control

Explicit Nonlinear Model Predictive Control
Author: Alexandra Grancharova
Publisher: Springer
Total Pages: 241
Release: 2012-03-22
Genre: Technology & Engineering
ISBN: 3642287808

Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an explicit state feedback law avoids the need for executing a numerical optimization algorithm in real time. The benefits of an explicit solution, in addition to the efficient on-line computations, include also verifiability of the implementation and the possibility to design embedded control systems with low software and hardware complexity. This book considers the multi-parametric Nonlinear Programming (mp-NLP) approaches to explicit approximate NMPC of constrained nonlinear systems, developed by the authors, as well as their applications to various NMPC problem formulations and several case studies. The following types of nonlinear systems are considered, resulting in different NMPC problem formulations: ؠ Nonlinear systems described by first-principles models and nonlinear systems described by black-box models; - Nonlinear systems with continuous control inputs and nonlinear systems with quantized control inputs; - Nonlinear systems without uncertainty and nonlinear systems with uncertainties (polyhedral description of uncertainty and stochastic description of uncertainty); - Nonlinear systems, consisting of interconnected nonlinear sub-systems. The proposed mp-NLP approaches are illustrated with applications to several case studies, which are taken from diverse areas such as automotive mechatronics, compressor control, combustion plant control, reactor control, pH maintaining system control, cart and spring system control, and diving computers.

Uncertainty-aware Integration of Control with Process Operations and Multi-parametric Programming Under Global Uncertainty

Uncertainty-aware Integration of Control with Process Operations and Multi-parametric Programming Under Global Uncertainty
Author: Vassilis M. Charitopoulos
Publisher: Springer Nature
Total Pages: 285
Release: 2020-02-05
Genre: Science
ISBN: 3030381374

This book introduces models and methodologies that can be employed towards making the Industry 4.0 vision a reality within the process industries, and at the same time investigates the impact of uncertainties in such highly integrated settings. Advances in computing power along with the widespread availability of data have led process industries to consider a new paradigm for automated and more efficient operations. The book presents a theoretically proven optimal solution to multi-parametric linear and mixed-integer linear programs and efficient solutions to problems such as process scheduling and design under global uncertainty. It also proposes a systematic framework for the uncertainty-aware integration of planning, scheduling and control, based on the judicious coupling of reactive and proactive methods. Using these developments, the book demonstrates how the integration of different decision-making layers and their simultaneous optimisation can enhance industrial process operations and their economic resilience in the face of uncertainty.

Multi-level Mixed-Integer Optimization

Multi-level Mixed-Integer Optimization
Author: Styliani Avraamidou
Publisher: Walter de Gruyter GmbH & Co KG
Total Pages: 154
Release: 2022-06-06
Genre: Technology & Engineering
ISBN: 3110760312

This book provides the fundamental underlying mathematical theory, numerical algorithms and effi cient computational tools for the solution of multi-level mixedinteger optimization problems. It can enable a vast array of decision makers and engineers (e.g. process engineers, bioengineers, chemical and civil engineers, and economists) to model, formulate and solve hierarchical decision making problems. The book gives detailed insights on multi-level optimization by comprehensive explanations, step-by-step numerical examples and case studies, plots, and diagrams.

Predictive Control for Linear and Hybrid Systems

Predictive Control for Linear and Hybrid Systems
Author: Francesco Borrelli
Publisher: Cambridge University Press
Total Pages: 447
Release: 2017-06-22
Genre: Mathematics
ISBN: 1107016886

With a simple approach that includes real-time applications and algorithms, this book covers the theory of model predictive control (MPC).

Parameterized Algorithms

Parameterized Algorithms
Author: Marek Cygan
Publisher: Springer
Total Pages: 618
Release: 2015-07-20
Genre: Computers
ISBN: 3319212753

This comprehensive textbook presents a clean and coherent account of most fundamental tools and techniques in Parameterized Algorithms and is a self-contained guide to the area. The book covers many of the recent developments of the field, including application of important separators, branching based on linear programming, Cut & Count to obtain faster algorithms on tree decompositions, algorithms based on representative families of matroids, and use of the Strong Exponential Time Hypothesis. A number of older results are revisited and explained in a modern and didactic way. The book provides a toolbox of algorithmic techniques. Part I is an overview of basic techniques, each chapter discussing a certain algorithmic paradigm. The material covered in this part can be used for an introductory course on fixed-parameter tractability. Part II discusses more advanced and specialized algorithmic ideas, bringing the reader to the cutting edge of current research. Part III presents complexity results and lower bounds, giving negative evidence by way of W[1]-hardness, the Exponential Time Hypothesis, and kernelization lower bounds. All the results and concepts are introduced at a level accessible to graduate students and advanced undergraduate students. Every chapter is accompanied by exercises, many with hints, while the bibliographic notes point to original publications and related work.

Multi-parametric Optimization and Control

Multi-parametric Optimization and Control
Author: Efstratios N. Pistikopoulos
Publisher: John Wiley & Sons
Total Pages: 320
Release: 2020-11-02
Genre: Mathematics
ISBN: 1119265150

Recent developments in multi-parametric optimization and control Multi-Parametric Optimization and Control provides comprehensive coverage of recent methodological developments for optimal model-based control through parametric optimization. It also shares real-world research applications to support deeper understanding of the material. 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.

Gröbner Bases and Applications

Gröbner Bases and Applications
Author: Bruno Buchberger
Publisher: Cambridge University Press
Total Pages: 566
Release: 1998-02-26
Genre: Mathematics
ISBN: 9780521632980

Comprehensive account of theory and applications of Gröbner bases, co-edited by the subject's inventor.

Fuzzy Linear Programming: Solution Techniques and Applications

Fuzzy Linear Programming: Solution Techniques and Applications
Author: Seyed Hadi Nasseri
Publisher: Springer
Total Pages: 246
Release: 2019-05-29
Genre: Technology & Engineering
ISBN: 3030174212

This book presents the necessary and essential backgrounds of fuzzy set theory and linear programming, particularly a broad range of common Fuzzy Linear Programming (FLP) models and related, convenient solution techniques. These models and methods belong to three common classes of fuzzy linear programming, namely: (i) FLP problems in which all coefficients are fuzzy numbers, (ii) FLP problems in which the right-hand-side vectors and the decision variables are fuzzy numbers, and (iii) FLP problems in which the cost coefficients, the right-hand-side vectors and the decision variables are fuzzy numbers. The book essentially generalizes the well-known solution algorithms used in linear programming to the fuzzy environment. Accordingly, it can be used not only as a textbook, teaching material or reference book for undergraduate and graduate students in courses on applied mathematics, computer science, management science, industrial engineering, artificial intelligence, fuzzy information processes, and operations research, but can also serve as a reference book for researchers in these fields, especially those engaged in optimization and soft computing. For textbook purposes, it also includes simple and illustrative examples to help readers who are new to the field.

Dynamic Process Modeling

Dynamic Process Modeling
Author:
Publisher: John Wiley & Sons
Total Pages: 628
Release: 2013-10-02
Genre: Technology & Engineering
ISBN: 3527631348

Inspired by the leading authority in the field, the Centre for Process Systems Engineering at Imperial College London, this book includes theoretical developments, algorithms, methodologies and tools in process systems engineering and applications from the chemical, energy, molecular, biomedical and other areas. It spans a whole range of length scales seen in manufacturing industries, from molecular and nanoscale phenomena to enterprise-wide optimization and control. As such, this will appeal to a broad readership, since the topic applies not only to all technical processes but also due to the interdisciplinary expertise required to solve the challenge. The ultimate reference work for years to come.