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This book is focused on the development of rigorous, yet practical,
methods for the design of advanced process control systems to
improve process operational safety and cybersecurity for a wide
range of nonlinear process systems. Process Operational Safety and
Cybersecurity develops designs for novel model predictive control
systems accounting for operational safety considerations, presents
theoretical analysis on recursive feasibility and simultaneous
closed-loop stability and safety, and discusses practical
considerations including data-driven modeling of nonlinear
processes, characterization of closed-loop stability regions and
computational efficiency. The text then shifts focus to the design
of integrated detection and model predictive control systems which
improve process cybersecurity by efficiently detecting and
mitigating the impact of intelligent cyber-attacks. The book
explores several key areas relating to operational safety and
cybersecurity including: machine-learning-based modeling of
nonlinear dynamical systems for model predictive control; a
framework for detection and resilient control of sensor
cyber-attacks for nonlinear systems; insight into theoretical and
practical issues associated with the design of control systems for
process operational safety and cybersecurity; and a number of
numerical simulations of chemical process examples and Aspen
simulations of large-scale chemical process networks of industrial
relevance. A basic knowledge of nonlinear system analysis, Lyapunov
stability techniques, dynamic optimization, and machine-learning
techniques will help readers to understand the methodologies
proposed. The book is a valuable resource for academic researchers
and graduate students pursuing research in this area as well as for
process control engineers. Advances in Industrial Control reports
and encourages the transfer of technology in control engineering.
The rapid development of control technology has an impact on all
areas of the control discipline. The series offers an opportunity
for researchers to present an extended exposition of new work in
all aspects of industrial control.
This book is focused on the development of rigorous, yet practical,
methods for the design of advanced process control systems to
improve process operational safety and cybersecurity for a wide
range of nonlinear process systems. Process Operational Safety and
Cybersecurity develops designs for novel model predictive control
systems accounting for operational safety considerations, presents
theoretical analysis on recursive feasibility and simultaneous
closed-loop stability and safety, and discusses practical
considerations including data-driven modeling of nonlinear
processes, characterization of closed-loop stability regions and
computational efficiency. The text then shifts focus to the design
of integrated detection and model predictive control systems which
improve process cybersecurity by efficiently detecting and
mitigating the impact of intelligent cyber-attacks. The book
explores several key areas relating to operational safety and
cybersecurity including: machine-learning-based modeling of
nonlinear dynamical systems for model predictive control; a
framework for detection and resilient control of sensor
cyber-attacks for nonlinear systems; insight into theoretical and
practical issues associated with the design of control systems for
process operational safety and cybersecurity; and a number of
numerical simulations of chemical process examples and Aspen
simulations of large-scale chemical process networks of industrial
relevance. A basic knowledge of nonlinear system analysis, Lyapunov
stability techniques, dynamic optimization, and machine-learning
techniques will help readers to understand the methodologies
proposed. The book is a valuable resource for academic researchers
and graduate students pursuing research in this area as well as for
process control engineers. Advances in Industrial Control reports
and encourages the transfer of technology in control engineering.
The rapid development of control technology has an impact on all
areas of the control discipline. The series offers an opportunity
for researchers to present an extended exposition of new work in
all aspects of industrial control.
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The Semantic Web - Joint International Semantic Technology Conference, JIST 2011, Hangzhou, China, December 4-7, 2011, Proceedings (Paperback, 2012 ed.)
Jeff Z. Pan, Huajun Chen, Hong-Gee Kim, Juanzi Li, Zhe Wu, …
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R1,605
Discovery Miles 16 050
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Ships in 10 - 15 working days
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This book constitutes the refereed post-proceedings of the Joint
International Semantic Technology Conference, JIST 2011, held in
Hangzhou, China, in December 2011. This conference is a joint event
for regional semantic Web related conferences. JIST 2011 brings
together the Asian Semantic Web Conference 2011 and the Chinese
Semantic Web Conference 2011. The 21 revised full papers presented
together with 12 short papers were carefully reviewed and selected
from 82 submissions. The papers cover a wide range of topics in
disciplines related to semantic technology including applications
of the semantic Web, management of semantic Web data, ontology and
reasoning, social semantic Web, and user interfaces to the semantic
Web.
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