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Quantitative Measure for Discrete Event Supervisory Control


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ISBN 10: 1441918515 / ISBN 13: 9781441918512
Published by Springer, 2011
Condition: Good Soft cover
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Bibliographic Details

Title: Quantitative Measure for Discrete Event ...

Publisher: Springer

Publication Date: 2011

Binding: Paperback

Book Condition:Good

Edition: 2005.

About this title


Supervisory Control Theory (SCT) provides a tool to model and control human-engineered complex systems, such as computer networks, World Wide Web, identification and spread of malicious executables, and command, control, communication, and information systems. Although there are some excellent monographs and books on SCT to control and diagnose discrete-event systems, there is a need for a research monograph that provides a coherent quantitative treatment of SCT theory for decision and control of complex systems. This new monograph will assimilate many new concepts that have been recently reported or are in the process of being reported in open literature. The major objectives here are to present a) a quantitative approach, supported by a formal theory, for discrete-event decision and control of human-engineered complex systems; and b) a set of applications to emerging technological areas such as control of software systems, malicious executables, and complex engineering systems. The monograph will provide the necessary background materials in automata theory and languages for supervisory control. It will introduce a new paradigm of language measure to quantitatively compare the performance of different automata models of a physical system. A novel feature of this approach is to generate discrete-event robust optimal decision and control algorithms for both military and commercial systems.

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Never before has there been a quantitative approach designed to optimize supervisory decision and control for discrete event systems. The text pioneers a formal system for supervision of human-engineered complex systems, to compare different supervisory models, thereby maximizing potential for achieving high performance. It offers exciting implications for both military and commercial engineering systems. 

Quantitative Measure for Discrete Event Supervisory Control presents a novel method for discrete-event decision and control of complex systems, and provides applications for burgeoning technological needs in engineering (i.e., multi-agent human and robotic systems, aircraft, and electric power generation systems), as well as control of software systems and malicious executables. Using Supervisory Control Theory (SCT), a tool to model and control human engineered complex systems, this text initiates new concepts in quantitative treatment of SCT, as a much needed augmentation to existing research on the diagnosis and control of SCT. This survey is the first comprehensive treatment of a language-theoretic quantitative approach to discrete event supervisory decision and control.

· Summarizes fundamental materials in supervisory decision and control before integrating new method to quantitatively measure performance

· Presents formal theory to support the quantitative approach, thus outlining an effective model for discrete event decision and control of human-engineered complex systems

· Outlines diverse and practical implications for the materials in the commercial and military Command, Control, Computer, Communication, Intelligence, Surveillance, and Reconnaissance (C4ISR) systems

· Illuminates significant mathematical foundations and proofs for reader understanding of quantification processes, while avoiding nonessential mathematical details and applications

· Develops and describes methods that have been successfully classroom-tested in Pennsylvania State University and Louisiana Tech University

Compiling some of the leading research in the field, this self-contained volume contains essential techniques and advanced applications for researchers or graduate students in computer engineering, computer science, and applied mathematics. Additionally, the book may be an important resource for students in other disciplines, such as the biological sciences, management sciences, social sciences, and economics.

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