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This edited volume provides insights into and tools for the
modeling, analysis, optimization, and control of large-scale
networks in the life sciences and in engineering. Large-scale
systems are often the result of networked interactions between a
large number of subsystems, and their analysis and control are
becoming increasingly important. The chapters of this book present
the basic concepts and theoretical foundations of network theory
and discuss its applications in different scientific areas such as
biochemical reactions, chemical production processes, systems
biology, electrical circuits, and mobile agents. The aim is to
identify common concepts, to understand the underlying mathematical
ideas, and to inspire discussions across the borders of the various
disciplines. The book originates from the interdisciplinary summer
school "Large Scale Networks in Engineering and Life Sciences"
hosted by the International Max Planck Research School Magdeburg,
September 26-30, 2011, and will therefore be of interest to
mathematicians, engineers, physicists, biologists, chemists, and
anyone involved in the network sciences. In particular, due to
their introductory nature the chapters can serve individually or as
a whole as the basis of graduate courses and seminars, future
summer schools, or as reference material for practitioners in the
network sciences.
Thepastthree decadeshaveseenrapiddevelopmentin the areaofmodelpred-
tive control with respect to both theoretical and application
aspects. Over these 30 years, model predictive control for linear
systems has been widely applied, especially in the area of process
control. However, today's applications often require driving the
process over a wide region and close to the boundaries of -
erability, while satisfying constraints and achieving near-optimal
performance. Consequently, the application of linear control
methods does not always lead to satisfactory performance, and here
nonlinear methods must be employed. This is one of the reasons why
nonlinear model predictive control (NMPC) has - joyed signi?cant
attention over the past years,with a number of recent advances on
both the theoretical and application frontier. Additionally, the
widespread availability and steadily increasing power of today's
computers, as well as the development of specially tailored
numerical solution methods for NMPC, bring
thepracticalapplicabilityofNMPCwithinreachevenforveryfastsystems.This
has led to a series of new, exciting developments, along with new
challenges in the area of NMPC.
This edited volume provides insights into and tools for the
modeling, analysis, optimization, and control of large-scale
networks in the life sciences and in engineering. Large-scale
systems are often the result of networked interactions between a
large number of subsystems, and their analysis and control are
becoming increasingly important. The chapters of this book present
the basic concepts and theoretical foundations of network theory
and discuss its applications in different scientific areas such as
biochemical reactions, chemical production processes, systems
biology, electrical circuits, and mobile agents. The aim is to
identify common concepts, to understand the underlying mathematical
ideas, and to inspire discussions across the borders of the various
disciplines. The book originates from the interdisciplinary summer
school "Large Scale Networks in Engineering and Life Sciences"
hosted by the International Max Planck Research School Magdeburg,
September 26-30, 2011, and will therefore be of interest to
mathematicians, engineers, physicists, biologists, chemists, and
anyone involved in the network sciences. In particular, due to
their introductory nature the chapters can serve individually or as
a whole as the basis of graduate courses and seminars, future
summer schools, or as reference material for practitioners in the
network sciences.
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