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 for years to come.

This fifth volume in the series is the first comprehensive source on energy systems engineering for the process industries. As such, it combines key contributions from leading research groups to form a single source of vital information otherwise dispersed among specialized journals.
Inspired by the leading authority in the field, the Centre for Process Systems Engineering at Imperial College London, this interdisciplinary work explores new technologies of sustainable energy sources and their optimization as energy sufficient systems. The innovative technologies thus covered are crucial for the continued growth of already established multi-billion-dollar commercial markets: oil and gas, petrochemicals, pharmaceuticals and fine chemicals, food and beverage and consumer goods.
From the contents:
* Polygeneration systems engineering
* Integrated oil & gas optimization
* Technologies for hydrogen production and storage
* Wind farm modeling, control and optimization
* Thermo-economic design
* Energy efficiency and carbon footprint reduction
* Energy systems solutions in the pulp and paper industry
* CO2 capture from natural gas
* Hydrogen infrastructure design and optimization
* Chance-constrained optimization of investment planning problems in the electric power industry
For chemical, process and automation engineers, as well as those working in measurement and control, and for lecturers in these fields, this is the ultimate reference work for years to come.

Optimization, simulation and control play an increasingly important role in science and industry. Because of their numerous applications in various disciplines, research in these areas is accelerating at a rapid pace.

This volume brings together the latest developments in these areas of research as well as presents applications of these results to a wide range of real-world problems. The book is composed of invited contributions by experts from around the world who work to develop and apply new optimization, simulation and control techniques either at a theoretical level or in practice. Some key topics presented include: equilibrium problems, multi-objective optimization, variational inequalities, stochastic processes, numerical analysis, optimization in signal processing, and various other interdisciplinary applications.

This volume can serve as a useful resource for researchers, practitioners, and advanced graduate students of mathematics and engineering working in research areas where results in optimization, simulation and control can be applied.

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.

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.

This volume presents recent exciting developments for the solution of model based predictive control problems by multiparametric programming algorithms and tools, described in volume 1 of this series.

Model based predictive control (MPC) is the advanced control technology of choice in process systems applications, for on-line control and real-time optimization. It relies in the computation of the optimal control input actions by repeteadly solving on-line and open or closed loop optimal control problem at the time instant when a state measurement or estimation becomes available. However, the capabilities of this technology are restricted mainly by the often extensive and computationally demanding on-line calculations, which make MPC mostly suitable for large-scale, expensive and slowly-varying systems. This book describes in detail how these shortcomings can be effcetively overcome by employing the novel multi-parametric programming theory and algorithms of volume 1, for a wide range of MPC problems, including hybrid and robust control.

The book is intended for academics, researchers and control practitioners who are involved on contemporary control studies, the design and implementation of control strategies, and the development of control hardware for embedded systems applications, as well as for educational purposes both in academia and industry.

The Process Systems Engineering (PSE) Series offers an integrated and interdisciplinary approach towards the development of methodologies and tools for modeling, design, control and optimization of enterprise-wide, process, manufacturing, energy and other such complex systems. A key theme is the systematic management ofcomplexity in systems involving uncertainty across different time and length scales. To address this formidable challenge, the multi-disciplinary expertise of mechanical, control, chemical, molecular and biological engineers, operations researchers, mathematical programming specialists and computer scientists is required.

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.

This volume and the preceding Volume 3 present an in depth account of recent novel methodologies and algorithmic developments for the simulation, modeling and optimization of integrated supply chains. Emphasis is placed on strategic and tactical Supply Chain planning for the process industries.
Management of supply chains is a complex task mainly due to the large size of the physical supply network and inherent uncertainties. Depending on the level, one or more of the following decisions are taken:
- Number, size and location of manufacturing sites, warehouses and distribution centres
- Network connectivity
- Production decisions
- Management of inventory levels and replenishment policies
- Transportation decisions
- Sustainability aspects
The book contains high-quality works from leading researchers in the field whose expertise fits within this scope. It is intended for academics, researchers, industry practitioners in supply chain management, who are involved in model-based supply chain activities, across engineering and applied science disciplines, as well as for educational purposes both in academia and industry.
The Process Systems Engineering (PSE) Series offers an integrated and interdisciplinary approach towards the development of methodologies and tools for modelling, design, control and optimisation of enterprise-wide, process, manufacturing, energy and other such complex systems. A key theme is the systematic management of complexity in systems involving uncertainty across different time and length scales. To address this formidable challenge, the multi-disciplinary expertise of mechanical, control, chemical, molecular and biologicalengineers, operations researchers, mathematical programming specialists, and computer scientists is required.

Synthesis and Operability Strategies for Computer-Aided Modular Process intensification presents state-of-the-art methodological developments and real-world applications for computer-aided process modeling, optimization and control, with a particular interest on process intensification systems. Each chapter consists of basic principles, model formulation, solution algorithm, and step-by-step implementation guidance on key procedures. Sections cover an overview on the current status of process intensification technologies, including challenges and opportunities, detail process synthesis, design and optimization, the operation of intensified processes under uncertainty, and the integration of design, operability and control. Advanced operability analysis, inherent safety analysis, and model-based control strategies developed in the community of process systems engineering are also introduced to assess process operational performance at the early design stage.

Optimization, simulation and control play an increasingly important role in science and industry. Because of their numerous applications in various disciplines, research in these areas is accelerating at a rapid pace. This volume brings together the latest developments in these areas of research as well as presents applications of these results to a wide range of real-world problems. The book is composed of invited contributions by experts from around the world who work to develop and apply new optimization, simulation and control techniques either at a theoretical level or in practice. Some key topics presented include: equilibrium problems, multi-objective optimization, variational inequalities, stochastic processes, numerical analysis, optimization in signal processing, and various other interdisciplinary applications. This volume can serve as a useful resource for researchers, practitioners, and advanced graduate students of mathematics and engineering working in research areas where results in optimization, simulation and control can be applied.

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.

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.