Introduction to discrete event systems
著者
書誌事項
Introduction to discrete event systems
Springer, c2021
3rd ed
大学図書館所蔵 全1件
注記
Includes bibliographical references and index
内容説明・目次
内容説明
This unique textbook comprehensively introduces the field of discrete event systems, offering a breadth of coverage that makes the material accessible to readers of varied backgrounds. The book emphasizes a unified modeling framework that transcends specific application areas, linking the following topics in a coherent manner: language and automata theory, supervisory control, Petri net theory, Markov chains and queueing theory, discrete-event simulation, and concurrent estimation techniques.
Topics and features:
detailed treatment of automata and language theory in the context of discrete event systems, including application to state estimation and diagnosis
comprehensive coverage of centralized and decentralized supervisory control of partially-observed systems
timed models, including timed automata and hybrid automata
stochastic models for discrete event systems and controlled Markov chains
discrete event simulation
an introduction to stochastic hybrid systems
sensitivity analysis and optimization of discrete event and hybrid systems
new in the third edition: opacity properties, enhanced coverage of supervisory control, overview of latest software tools
This proven textbook is essential to advanced-level students and researchers in a variety of disciplines where the study of discrete event systems is relevant: control, communications, computer engineering, computer science, manufacturing engineering, transportation networks, operations research, and industrial engineering.
Christos G. Cassandras is Distinguished Professor of Engineering, Professor of Systems Engineering, and Professor of Electrical and Computer Engineering at Boston University.
Stephane Lafortune is Professor of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor.
目次
Preface-Third Edition.- Preface- Second Edition.- Preface.- Systems and Models.- Languages and Automata.- Supervisory Control.- Petri Nets.- Timed and Hybrid Models.- Stochastic Timed Automata.- Markov Chains.- Introduction to Queuing Theory.- Controlled Markov Chains.- Introduction to Discrete-Event Simulation.- Sensitivity Analysis and Concurrent Estimation.- Review of Probability Theory.- IPA Estimator.- Index.- About the Authors.
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