Uncertainty Aware Integration Of Control With Process Operations And Multi Parametric Programming Under Global Uncertainty
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Uncertainty-aware Integration of Control with Process Operations and Multi-parametric Programming Under Global Uncertainty by Vassilis M. Charitopoulos Pdf
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.
13th International Symposium on Process SystemsEngineering – PSE 2018, July 1-5 2018 by Mario R. Eden,Gavin Towler,Maria Ierapetritou Pdf
Process Systems Engineering brings together the international community of researchers and engineers interested in computing-based methods in process engineering. This conference highlights the contributions of the PSE community towards the sustainability of modern society and is based on the 13th International Symposium on Process Systems Engineering PSE 2018 event held San Diego, CA, July 1-5 2018. The book contains contributions from academia and industry, establishing the core products of PSE, defining the new and changing scope of our results, and future challenges. Plenary and keynote lectures discuss real-world challenges (globalization, energy, environment and health) and contribute to discussions on the widening scope of PSE versus the consolidation of the core topics of PSE. Highlights how the Process Systems Engineering community contributes to the sustainability of modern society Establishes the core products of Process Systems Engineering Defines the future challenges of Process Systems Engineering
Integrated Process Design and Operational Optimization Via Multiparametric Programming by Baris Burnak,Nikolaos A Diangelakis,Efstratios N Pistikopoulos Pdf
This book presents a comprehensive optimization-based theory and framework that exploits the synergistic interactions and tradeoffs between process design and operational decisions that span different time scales. Conventional methods in the process industry often isolate decision making mechanisms with a hierarchical information flow to achieve tractable problems, risking suboptimal, even infeasible operations. In this book, foundations of a systematic model-based strategy for simultaneous process design, scheduling, and control optimization is detailed to achieve reduced cost and improved energy consumption in process systems. The material covered in this book is well suited for the use of industrial practitioners, academics, and researchers. In Chapter 1, a historical perspective on the milestones in model-based design optimization techniques is presented along with an overview of the state-of-the-art mathematical tools to solve the resulting complex problems. Chapters 2 and 3 discuss two fundamental concepts that are essential for the reader. These concepts are (i) mixed integer dynamic optimization problems and two algorithms to solve this class of optimization problems, and (ii) developing a model based multiparametric programming model predictive control. These tools are used to systematically evaluate the tradeoffs between different time-scale decisions based on a single high-fidelity model, as demonstrated on (i) design and control, (ii) scheduling and control, and (iii) design, scheduling, and control problems. We present illustrative examples on chemical processing units, including continuous stirred tank reactors, distillation columns, and combined heat and power regeneration units, along with discussions of other relevant work in the literature for each class of problems.
Fifth International Conference on Foundations of Computer-Aided Process Design by Michael F. Malone,James A. Trainham,Brice Carnahan Pdf
Looks at challenges for the future, including the broader challenge of extending design to include creating new value for a company, and a discussion of how emerging technologies, particularly increased computer speeds, may impact future design.
Process Systems Engineering 2003 by Bingzhen Chen,Art Westerberg Pdf
Contains proceedings from the 8th International Symposium on Process Systems Engineering (PSE), which brought together the global community of process systems engineering researchers and practitioners involved in the creation and application of computing based methodologies for planning, design, operation, control, and maintenance of chemical processes. Contains proceeding from the 8th International Symposium on Process Systems EngineeringConference theme for PSE 2003 is 'supporting business decision making'
Author : American Institute of Chemical Engineers Publisher : Unknown Page : 532 pages File Size : 52,6 Mb Release : 2000 Category : Chemical engineering ISBN : UOM:39015049138020
The 7th International Conference on Information Science, Communication and Computing by Xuesong Qiu,Yang Xiao,Zhiqiang Wu,Yudong Zhang,Yuan Tian,Bo Liu Pdf
This conference proceedings is a collection of the accepted papers of ISCC2023 - the 7th International Conference on Information Science, Communication and Computing held in Chongqing, China, 2-5 June 2023. The topics focus on intelligent information science and technology, artificial intelligence and intelligent systems, cloud computing and big data, smart computing and communication technology, wireless network, and cyber security. Each part can be used as an excellent reference by industry practitioners, university faculties, research fellows, and undergraduate and graduate students who need to build a knowledge base of the latest advances and state of the practice in the topics covered by this conference proceedings. This will enable them to build, maintain and manage systems of high reliability and complexity. We would like to thank the authors for their hard work and dedication, and the reviewers for ensuring that only the highest quality papers were selected.
Decision Making Under Uncertainty by Mykel J. Kochenderfer Pdf
An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.
Mastering Uncertainty in Mechanical Engineering by Peter F. Pelz,Peter Groche,Marc E. Pfetsch,Maximilian Schaeffner Pdf
This open access book reports on innovative methods, technologies and strategies for mastering uncertainty in technical systems. Despite the fact that current research on uncertainty is mainly focusing on uncertainty quantification and analysis, this book gives emphasis to innovative ways to master uncertainty in engineering design, production and product usage alike. It gathers authoritative contributions by more than 30 scientists reporting on years of research in the areas of engineering, applied mathematics and law, thus offering a timely, comprehensive and multidisciplinary account of theories and methods for quantifying data, model and structural uncertainty, and of fundamental strategies for mastering uncertainty. It covers key concepts such as robustness, flexibility and resilience in detail. All the described methods, technologies and strategies have been validated with the help of three technical systems, i.e. the Modular Active Spring-Damper System, the Active Air Spring and the 3D Servo Press, which have been in turn developed and tested during more than ten years of cooperative research. Overall, this book offers a timely, practice-oriented reference guide to graduate students, researchers and professionals dealing with uncertainty in the broad field of mechanical engineering.
Chemical Production Scheduling by Christos T. Maravelias Pdf
Understand common scheduling as well as other advanced operational problems with this valuable reference from a recognized leader in the field. Beginning with basic principles and an overview of linear and mixed-integer programming, this unified treatment introduces the fundamental ideas underpinning most modeling approaches, and will allow you to easily develop your own models. With more than 150 figures, the basic concepts and ideas behind the development of different approaches are clearly illustrated. Addresses a wide range of problems arising in diverse industrial sectors, from oil and gas to fine chemicals, and from commodity chemicals to food manufacturing. A perfect resource for engineering and computer science students, researchers working in the area, and industrial practitioners.
Multi-parametric Optimization and Control by Efstratios N. Pistikopoulos,Nikolaos A. Diangelakis,Richard Oberdieck Pdf
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.
Handbook of Uncertainty Quantification by Roger Ghanem,David Higdon,Howman Owhadi Pdf
The topic of Uncertainty Quantification (UQ) has witnessed massive developments in response to the promise of achieving risk mitigation through scientific prediction. It has led to the integration of ideas from mathematics, statistics and engineering being used to lend credence to predictive assessments of risk but also to design actions (by engineers, scientists and investors) that are consistent with risk aversion. The objective of this Handbook is to facilitate the dissemination of the forefront of UQ ideas to their audiences. We recognize that these audiences are varied, with interests ranging from theory to application, and from research to development and even execution.
The Uncertainty Analysis of Model Results by Eduard Hofer Pdf
This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decision-makers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results.
Multi-Parametric Model-Based Control by Anonim Pdf
This volume covers theoretical advances and developments, computational challenges and tools as well as applications in the area of multi-parametric model based control. Part I is concerned with the presentation of algorithms for parametric model based control focusing on: - novel frameworks for the derivation of explicit optimal control policies for continuous time-linear dynamic systems - new theoretical developments on hybrid model based control - methods for obtaining the explicit robust model-based tracking control - theoretical frameworks for parametric dynamic optimization and - recent developments for continuous-time systems Part II presents a series of application in the following areas: - the incorporation of advanced model based controllers in a simultaneous process design and control framework for complex separation systems - the development of advanced model based control techniques for regulating the blood glucose for patients with Type 1 diabetes - the design of model predictive and parametric controllers for anesthesia. - the development of optimal control policies in a pilot plant exothermic reactor The volume is intended for academics and researchers that carry out model based control research, industrial practitioners involved in the control of new and existing processes and products, policy makers, as well as for educational purposes both in academia and industry.
Sun Tracking and Solar Renewable Energy Harvesting by Gerro Prinsloo,Robert Dobson Pdf
Free to download eBook on Practical Solar Tracking Design, Solar Tracking, Sun Tracking, Sun Tracker, Solar Tracker, Follow Sun, Sun Position calculation (Azimuth, Elevation, Zenith), Sun following, Sunrise, Sunset, Moon-phase, Moonrise, Moonset calculators. In harnessing power from the sun through a solar tracker or solar tracking system, renewable energy system developers require automatic solar tracking software and solar position algorithms. On-axis sun tracking system such as the altitude-azimuth dual axis or multi-axis solar tracker systems use a sun tracking algorithm or ray tracing sensors or software to ensure the sun's passage through the sky is traced with high precision in automated solar tracker applications, right through summer solstice, solar equinox and winter solstice. Eco Friendly and Environmentally Sustainable Micro Combined Solar Heat and Power (m-CHP, m-CCHP, m-CHCP) with Microgrid Storage and Layered Smartgrid Control towards Supplying Off-Grid Rural Villages in developing BRICS countries such as Africa, India, China and Brazil. Off-grid rural villages and isolated islands areas require mCHP and trigeneration solar power plants and associated isolated smart microgrid solutions to serve the community energy needs. This article describes the development progress for such a system, also referred to as solar polygeneration. The system includes a sun tracker mechanism wherin a parabolic dish or lenses are guided by a light sensitive mechanique in a way that the solar receiver is always at right angle to the solar radiation. Solar thermal energy is then either converted into electrical energy through a free piston Stirling, or stored in a thermal storage container. The project includes the thermodynamic modeling of the plant in Matlab Simulink as well as the development of an intelligent control approach that includes smart microgrid distribution and optimization. The book includes aspects in the simulation and optimization of stand-alone hybrid renewable energy systems and co-generation in isolated or islanded microgrids. It focusses on the stepwise development of a hybrid solar driven micro combined cooling heating and power (mCCHP) compact trigeneration polygeneration and thermal energy storage (TES) system with intelligent weather prediction, weak-ahead scheduling (time horizon), and look-ahead dispatch on integrated smart microgrid distribution principles. The solar harvesting and solar thermodynamic system includes an automatic sun tracking platform based on a PLC controlled mechatronic sun tracking system that follows the sun progressing across the sky. An intelligent energy management and adaptive learning control optimization approach is proposed for autonomous off-grid remote power applications, both for thermodynamic optimization and smart micro-grid optimization for distributed energy resources (DER). The correct resolution of this load-following multi objective optimization problem is a complex task because of the high number and multi-dimensional variables, the cross-correlation and interdependency between the energy streams as well as the non-linearity in the performance of some of the system components. Exergy-based control approaches for smartgrid topologies are considered in terms of the intelligence behind the safe and reliable operation of a microgrid in an automated system that can manage energy flow in electrical as well as thermal energy systems. The standalone micro-grid solution would be suitable for a rural village, intelligent building, district energy system, campus power, shopping mall centre, isolated network, eco estate or remote island application setting where self-generation and decentralized energy system concepts play a role. Discrete digital simulation models for the thermodynamic and active demand side management systems with digital smartgrid control unit to optimize the system energy management is currently under development. Parametric simulation models for this trigeneration system (polygeneration, poligeneration, quadgeneration) are developed on the Matlab Simulink and TrnSys platforms. In terms of model predictive coding strategies, the automation controller will perform multi-objective cost optimization for energy management on a microgrid level by managing the generation and storage of electrical, heat and cooling energies in layers. Each layer has its own set of smart microgrid priorities associated with user demand side cycle predictions. Mixed Integer Linear Programming and Neural network algorithms are being modeled to perform Multi Objective Control optimization as potential optimization and adaptive learning techniques.