Introduction to Discrete Event Systems

This book is a comprehensive introduction to 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 queuing theory, amd more.

Introduction to Discrete Event Systems is a comprehensive introduction to 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 queuing theory, discrete-event simulation, and concurrent estimation techniques. This edition includes new material pertaining to the diagnosis of discrete event systems, decentralized supervisory control, and interval-based timed automata and hybrid automata models.

This textbook is valuable 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, operations research, and industrial engineering.

Includes numerous detailed examples and student exercises Second edition incorporates essential elements of Hybrid System modeling, thus contributing to bridging the existing gap between time-driven and event-driven systems Includes supplementary material: sn.pub/extras

Autorentext

Christos G. Cassandras is Professor of Manufacturing Engineering and Professor of Electrical and Computer Engineering at Boston University. He received degrees from Yale University (B.S., 1977), Stanford University (M.S.E.E., 1978), and Harvard University (S.M., 1979; Ph.D., 1982). In 1982-84 he was with ITP Boston, Inc. where he worked on the design of automated manufacturing systems. In 1984-1996 he was a faculty member at the Department of Electrical and Computer Engineering, University of Massachusetts/Amherst. He specializes in the areas of discrete event and hybrid systems, stochastic optimization, and computer simulation, with applications to computer and sensor networks, manufacturing systems, and transportation systems. He has published over 200 refereed papers in these areas, and two textbooks. He has guest-edited several technical journal issues and serves on several journal Editorial Boards. Dr. Cassandras is currently Editor-in-Chief of the IEEE Transactions on Automatic Control and has served as Editor for Technical Notes and Correspondence and Associate Editor. He is a member of the IEEE CSS Board of Governors, chaired the CSS Technical Committee on Control Theory, and served as Chair of several conferences. He has been a plenary speaker at various international conferences, including the American Control Conference in 2001 and the IEEE Conference on Decision and Control in 2002. He is the recipient of several awards, including the 1999 Harold Chestnut Prize (IFAC Best Control Engineering Textbook) for Discrete Event Systems: Modeling and Performance Analysis, and a 1991 Lilly Fellowship. He is a member of Phi Beta Kappa and Tau Beta Pi. He is also a Fellow of the IEEE.

Stéphane Lafortune is Professor of Electrical Engineering and Computer Science at the University of Michigan, Ann Arbor. He received degrees from Ecole Polytechnique de Montréal (B.Eng., 1980), McGill University (M.Eng., 1982), and the University of California atBerkeley (Ph.D., 1986). He joined the University of Michigan in 1986. He specializes in the areas of discrete event systems, fault diagnosis, supervisory control, and optimization, with applications to communication networks and transportation systems. He has published over 130 refereed papers in these areas, and one textbook. Dr. Lafortune is currently Department Editor of the Journal of Discrete Event Dynamic Systems: Theory and Applications. He served as Associate Editor and Associate-Editor-at-Large of the IEEE Transactions on Automatic Control in the period 1993-1999. He was a plenary speaker at various international meetings, including the 1996 International Workshop on Discrete Event Systems (WODES'96). He is the recipient of several awards, including the 1994 and 2001 George S. Axelby Outstanding Paper Awards from the IEEE Control Systems Society. He is a Fellow of the IEEE.

Klappentext

Introduction to Discrete Event Systems is a comprehensive introduction to 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.

Distinctive features of the second edition include:

• more detailed treatment of equivalence of automata, event diagnosis, and decentralized event diagnosis

• expanded treatment of centralized and decentralized control of partially-observed systems

• new sections on timed automata with guards (in the Alur-Dill formalism) and hybrid automata

• an introduction to hybrid systems

• updated coverage of discrete event simulation, including new software tools available

• recent developments in sensitivity analysis for discrete event systems as well as hybrid systems

  This textbook is valuable 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, operations research, and industrial engineering.

  Inhalt
  Systems and Models.- Languages and Automata.- Supervisory Control.- Petri Nets.- Timed and Hybrid Models.- Stochastic Timed Automata.- Markov Chains.- to Queueing Theory.- Controlled Markov Chains.- to Discrete-Event Simulation.- Sensitivity Analysis and Concurrent Estimation.