Quantitative Measure for Discrete Event Supervisory Control Hardcover - 2004

First line

Discrete-event dynamic behavior of a physical plant is often modelled as a deterministic finite-state automaton (DFSA) that can be represented by a regular language [7] [9].

From the rear cover

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.