CONTROL AND OPTIMIZATION OF MULTISCALE PROCESS SYSTEMS
Panagiotis D. Christofides
Antonios Armaou
Yiming Lou
Amit Varshney
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Birkhauser
Series: Control Engineering
212 pp., 100 illus., Hardcover
ISBN 978-0-8176-4792-6
http://www.springer.com/birkhauser/engineering/book/978-0-8176-4792-6
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ABOUT THIS BOOK
* First book published on the subject of control and optimization of
multiscale process systems
* Includes new techniques for feedback controller design and
optimization for multiscale process systems not included in other books
* Illustrates the application of controller design and optimization
methods to various complex chemical processes of industrial interest,
including different thin film deposition processes, an ion-sputtering
process, and a catalytic CO oxidation process
* Excellent source of new research topics and references to recent and
significant work in the field
* May be used as a textbook for a graduate-level engineering or
mathematics course on the analysis and control of multiscale systems, or
as a supplementary text for graduate-level courses on advanced process
control
Interest in the control and optimization of multiscale process systems has
been triggered by the need to achieve tight feedback control and optimal
operation of complex processes, such as deposition and sputtering of thin
films in semiconductor manufacturing, which are characterized by highly
coupled macroscopic and microscopic phenomena. Drawing from recent
advances in the dynamics and control of distributed parameter processes
for which continuum laws are applicable as well as stochastic modeling of
phenomena at mesoscopic/microscopic length scales, control and
optimization of multiscale process systems has evolved into a very active
research area of systems and control engineering.
This book—the first of its kind—presents general methods for feedback
controller synthesis and optimization of multiscale systems, illustrating
their application to thin-film growth, sputtering processes, and catalytic
systems of industrial interest. Beginning with an introduction to general
issues on control and optimization of multiscale systems and a review of
previous work in this area, the book discusses detailed modeling
approaches for multiscale processes with emphasis on the theory and
implementation of kinetic Monte Carlo simulation, methods for feedback
control using kinetic Monte Carlo models, stochastic model construction
and parameter estimation, predictive and covariance control using
stochastic partial differential equation models, and both steady-state and
dynamic optimization algorithms that efficiently address coupled
macroscopic and microscopic objectives.
Key features of the work:
* Demonstrates the advantages of the methods presented for control and
optimization through extensive simulations.
* Includes new techniques for feedback controller design and optimization
of multiscale process systems that are not included in other books.
* Illustrates the application of controller design and optimization
methods to complex multiscale processes of industrial interest.
* Contains a rich collection of new research topics and references to
significant recent work.
The book requires basic knowledge of differential equations, probability
theory, and control theory, and is intended for researchers, graduate
students, and process control engineers. Throughout the book, practical
implementation issues are addressed to help researchers and engineers
understand the development and application of the methods presented in
greater depth.
Written for:
researchers and graduate students in systems and control; and process
control engineers
Keywords:
* dynamic optimization
* feedback controllers
* kinetic Monte Carlo methods
* multiscale optimization
* multiscale process systems
* optimization
* stochastic PDEs
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