IEEE CONTROL SYSTEMS SOCIETY TECHNICAL COMMITTEE
ON DISCRETE EVENT SYSTEMS

    Ryan J. Leduc
    Chair, IEEE CSS Technical Committee on DES
    Dept. of Computing and Software
    McMaster University
    1280 Main Street West
    Hamilton, Ontario
    Canada L8S 4K1

    Phone: (905) 525-9140 Ext. 27962
    Fax: (905) 524-0340
    e-mail: leduc@mcmaster.ca
    WWW: http://www.cas.mcmaster.ca/~leduc/

DESTC Web Page: http://www.cas.mcmaster.ca/destc/

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Contents:

1. Editorial

2. Announcements
 2.1 CFP: Track on Hybrid and Discrete Event Systems at IEEE CASE 2008

3. Books
 3.1 Stochastic Learning and Optimization - A Sensitivity-Based
     Approach", by Xi-Ren Cao
 3.2 Introduction to Discrete Event Systems - Second Edition", by C.
     Cassandras and S. Lafortune

4. Conferences
 4.1 10th International Conference on Control, Automation, Robotics and
     Vision, Hanoi, Vietnam, December 17 - 20, 2008

5. Journals
 5.1 Selections from IEEE Transactions on Automatic Control, Volume: 52
     Issue: 12, December 2007

Welcome to the newsletter of the IEEE Control Systems Technical Committee on Discrete Event Systems!

See http://www.cas.mcmaster.ca/destc/ for information on the DESTC.

Personal note from the editor:

Welcome to the February newsletter,

Ryan

Contributed by: Olaf Stursberg <stursberg@tum.de>

CFP: TRACK ON HYBRID AND DISCRETE EVENT SYSTEMS AT IEEE CASE 2008

The 4th annual IEEE Conference on Automation Science and Engineering
(IEEE CASE) will be held from August 23 to 26, 2008 in Washington DC,
U.S.A.	CASE is an offspring of the IEEE Transactions of Automation
Science and Engineering, http://www.ieee.org/t-ase. High quality CASE
papers will be recommended for publication in this flagship automation
journal.

For a broad range of automated applications, which includes
manufacturing and processing plants, robotics, automotive systems,
transportation, and energy distribution networks, design techniques
based on hybrid and discrete event models have emerged to be
particularly useful. Open problems and current trends like the scalable
design of complex control systems, the growing importance of (wireless)
communication and network aspects in automation, and the consideration
of flexible structures and intelligent components continue to fuel
intensive research activities and interest in the analysis, control,
optimization, and implementation of hybrid, discrete event, and
embedded control systems. We invite you to submit your papers regarding
relevant advances and developments to the

   Track on "Hybrid and Discrete Event Systems"

at IEEE CASE. This track aims at bringing together a multidisciplinary
group of researchers at the leading-edge, focusing on areas which
comprise but are not limited to: 

- Control and planning of discrete-event systems
- Control over communication networks
- Queueing  systems and logistic processes
- Design methods for hybrid control
- Automata and Petri nets
- Discrete event modeling and supervisory control
- Model abstraction and reduction for complex hybrid systems
- Analysis, verification, fault diagnosis, and controller
reconfiguration
- Distributed and agent-based control of switched and hybrid systems
- Machine learning for heterogenous models

Paper Submission:

Authors should submit full papers electronically in double column PDF
format. All papers will be peer-reviewed, and the selected ones will be
published in the CD-ROM Proceedings to be indexed by the Elsevier
database Engineering Index (EI) and Compendex. Six pages are allowed
per paper, and detailed instructions for paper preparation and
submission will be available on the conference web site:
http://www.ieee-case.org.

Important Dates: 

- February 29, 2008: Submission of full papers (firm deadline)
- May 30, 2008: Paper acceptance notification to authors
- June 27, 2008: Final papers submission due

Track Chairs:

Prof. Olaf Stursberg
(Technical University of Munich, stursberg@tum.de)
Prof. Dimitrios Hristu-Varsakelis
(University of Macedonia, dcv@uom.gr)

Contributed by: Xi-Ren Cao <eecao@ust.hk>

STOCHASTIC LEARNING AND OPTIMIZATION - A SENSITIVITY-BASED APPROACH

Xi-Ren Cao
Springer, 2007
ISBN ISBN-13: 978-0-387-36787-3
http://www.amazon.com/Stochastic-Learning-Optimization-Sensitivity-Based-International/dp/038736787X

Stochastic learning and optimization is a multidisciplinary subject 
that has wide applications in modern engineering, social, and financial

problems, including those in Internet and wireless communications, 
manufacturing, robotics, logistics, biomedical systems, and investment 
science. This book is unique in the following aspects.

1. (Four areas in one book) This book covers various disciplines in 
stochastic learning and optimization, including perturbation analysis 
(PA) of discrete-event dynamic systems, Markov decision processes 
(MDPs), reinforcement learning (RL), and adaptive control, within a 
unified framework and using a sensitivity-based view.
2. (A simple approach to MDPs) This book introduces MDP theory through 
a simple approach based on performance difference formulas. This 
approach leads to results for the n-bias optimality with long-run 
average-cost criteria and Blackwell's optimality without discounting 
and Laurent series expansion. This simple approach applies to various 
performance criteria, including long-run avegare and discounted, in the
same way.
3. (Event-based optimization) This book introduces the recently 
developed event-based optimization approach, which opens up a research 
direction in overcoming or alleviating the difficulties due to the 
curse of dimensionality issue by utilizing the system's special 
features.
4. (New topics) This book also introduces other recently developed 
results: PA of Markov systems, reinforcement learning of performance 
gradients, and sample-path-based optimization with gradient estimation 
or policy iteration.
5. (Sample-path construction) This book emphasizes physical 
interpretations based on the sample-path construction.

The book provides a comprehensive overview of the area of stochastic 
learning and optimization and an introduction to the newly developed 
topics in the area; it can be used as a textbook for graduate students 
who wish to gain a quick understanding of this interdisciplinary area 
that contains various disciplines; it is also a good reference book for

researchers in different engineering fields for tools that may help in 
solving their design and optimization problems.

TABLE OF CONTENTS


Table of Contents
Preface 
    1 Introduction . . . . . . . . . . .  1

Part I Four Disciplines in Learning and Optimization
    2 Perturbation Analysis . . . . . . . . . . . . . . . . . . 51
    3 Learning and Optimization with Perturbation Analysis . . 147
    4 Markov Decision Processes . . . . . . . . . . . . . . .  183
    5 Sample-Path-Based Policy Iteration . . . . . . . . . . . 253
    6 Reinforcement Learning . . . . . . . . . .  . . . . . .. 289
    7 Adaptive Control Problems as MDPs . . . . . . . . . . .. 341

Part II The Event-Based Optimization - A New Approach
    8 Event-Based Optimization of Markov Systems . . . . . . . 387
    9 Constructing Sensitivity Formulas . . . . . . . . .. . . 455

Part III Appendices: Mathematical Background
   A Probability and Markov Processes . . . . . . . . . . . .  491
   B Stochastic Matrices . . . . . . . . . . . . .  . . . . .  507
   C Queueing Theory . . . . . . . . . . . . . . .. . . . . .  519

http://www.amazon.com/Stochastic-Learning-Optimization-Sensitivity-Base
d-International/dp/038736787X

or

http://www.ee.ust.hk/~eecao/

Contributed by: C. Cassandras and S. Lafortune <cgc@bu.edu,stephane@umich.edu>

INTRODUCTION TO DISCRETE EVENT SYSTEMS - SECOND EDITION

C. Cassandras and S. Lafortune
Springer, 2007
ISBN 978-0-387-33332-8
http://www.springer.com/engineering/book/978-0-387-33332-8

The second edition of the popular textbook "Introduction to Discrete Event
Systems" by Christos Cassandras and Stephane Lafortune was published in
December 2007 by Springer. The first edition of this textbook was published
in 1999 (Kluwer) and sold over 1600 copies worldwide. 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.

"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. 
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.

For further information, including the complete Table of Contents, please
refer to:
http://www.springer.com/engineering/book/978-0-387-33332-8
The sale price is US$89.95 or 74,95 Euros.

TABLE OF CONTENTS

The chapter titles are:
        Chapter 1 - Systems and Models
        Chapter 2 - Languages and Automata
        Chapter 3 - Supervisory Control
        Chapter 4 - Petri Nets
        Chapter 5 - Timed and Hybrid Models
        Chapter 6 - Stochastic Timed Automata
        Chapter 7 - Markov Chains
        Chapter 8 - Introduction to Queueing Theory
        Chapter 9 - Controlled Markov Chains
        Chapter 10 - Introduction to Discrete-Event Simulation
        Chapter 11 - Sensitivity and Analysis and Concurrent Estimation

Contributed by: Ryan Leduc <leduc aT mcmaster dOt ca>

10TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND
VISION
Hanoi, Vietnam
December 17 - 20, 2008

The 10th International Conference on Control, Automation, Robotics and
Vision, ICARCV 2008, will be held in Hanoi from 17 - 20 December 2008.
The conference is co-organised by the Nanyang Technological University
of Singapore and Vietnamese Academy of Science and Technology. The
technical sponsors are IEEE Control Systems Society, IEEE Computational
Intelligence Society, IEEE Robotics and Automation Society and IEEE
Systems, Man and Cybernetics Society.

ICARCV focuses on both theory and applications mainly covering the
topics of control, automation, robotics and vision. In addition to the
technical sessions, there will be invited sessions and keynote
addresses.

The Proceedings of ICARCV are indexed by ISI Proceedings, EI Compendex
and included in the IEEE Xplore.

The topics of interest include, but are not limited to:

Control: Adaptive control; Robust control; Process control; Complex
systems; Co-operative control; Identification and estimation; Nonlinear
systems; Intelligent systems; Discrete event systems; Hybrid systems;
Networked control systems; Sensor network systems; Delay systems;
Neural networks; Fuzzy systems; Control of biological systems;
Precision motion control; Control applications; Control engineering
education.

Automation: Man-machine interactions; Process automation; Intelligent
automation; Factory modeling and simulation; Home, laboratory and
service automation; Network-based systems; Planning, scheduling and
coordination; Nano-scale automation and assembly; Instrumentation
systems; Biomedical instrumentation and applications.

Robotics: Modeling and identification; Robot control; Mobile robotics;
Mobile sensor networks; Perception systems; Micro robots and
micro-manipulation; Visual servoing; Search, rescue and field robotics;
Robot sensing and data fusion; Localization, navigation and mapping;
Dexterous manipulation; Medical robots and bio-robotics; Human centered
systems; Space and underwater robots; Tele-robotics; Mechanism design
and applications.

Vision: Image/video analysis; Feature extraction, grouping and
segmentation; Scene analysis; Pattern recognition; Learning in vision;
Human-computer interaction; Tracking and surveillance; Biometrics;
Biomedical Image analysis; Activity/behaviour recognition;
Applications.

Best Paper Award:
Selection of the best paper will be made at the Conference based on
both the technical content and presentation. The winner will be chosen
by the Technical Program Committee in consultation with the
International Advisory Committee.

Paper Submission:
Papers must be written in English and should describe original work in
detail.

Please download the template from the conference website and submit the
full papers online http://www.icarcv.org/ by 1 April, 2008. Upon
acceptance, authors will be required to register and present their
papers.

Invited Sessions:
Invited sessions are to provide a forum for focused discussions on new
topics, or innovative applications of established approaches. The
Technical Program Committee is soliciting proposals for invited
sessions focusing on topics of ICARCV 2008. Prospective organisers
should submit proposals to Invited Session Chairman, Li, Zhengguo via
ezgli@ntu.edu.sg or Co-Chairmen Meng, Max Q.-H. via
max@ee.cuhk.edu.hk and Cao, Tien Huynh via lena_capit@yahoo.com. The
deadline for submitting the proposals is 1 March, 2008 and the
procedures in Organising invited sessions can be found in
www.icarcv.org/2008/InvProcedure.asp

Important Dates:

Deadline for Full Paper submission : 1 April 2008
Deadline for Invited Session proposals : 1 March 2008
Notification of Acceptance : 1 July 2008
Deadline for Final Manuscript Submission : 1 September 2008
Deadline for Authors' Registration : 1 September 2008

For further information, please send an email to
secretariat@icarcv.org.

web site: click here

Contributed by: Ryan Leduc <leduc aT mcmaster dOt ca>

SELECTIONS FROM IEEE TRANSACTIONS ON AUTOMATIC CONTROL
VOLUME: 52 ISSUE: 12
DECEMBER, 2007

1) Hierarchical Supervisory Control Based on Discrete Event Systems
With Flexible Marking

da Cunha, A. E. C.; Cury, J. E. R.

Abstract:

This paper proposes a two-level hierarchical supervisory control scheme
for a discrete event system (DES), where the low-level is represented
in the standard Ramadge-Wonham framework and the high level is
represented by a DES with flexible marking (DESFM). As shown, the
flexibility in the definition of marking provided by a DESFM simplifies
the modeling of the high-level marking behavior. This approach, when
compared with other approaches, requires less events and states to
model the high-level, while guaranteeing hierarchical consistency.

2) Invariance Principles for Hybrid Systems With Connections to
Detectability and Asymptotic Stability

Sanfelice, R. G.; Goebel, R.; Teel, A. R.

Abstract:

This paper shows several versions of the (LaSalle's) invariance
principle for general hybrid systems. The broad framework allows for
nonuniqueness of solutions, Zeno behaviors, and does not insist on
continuous dependence of solutions on initial conditions. Instead, only
a mild structural property involving graphical convergence of solutions
is posed. The general invariance results are then specified to hybrid
systems given by set-valued data. Further results involving invariance
as well as observability, detectability, and asymptotic stability are
given.

3) Detectability of Discrete Event Systems

Shu, S.; Lin, F.; Ying, H

Abstract:

In this note, we investigate the detectability problem in discrete
event systems. We assume that we do not know initially which state the
system is in. The problem is to determine the current and subsequent
states of the system based on a sequence of observations. The
observation includes partial event observation and/or partial state
observation, which leads to four possible cases. We further define four
types of detectabilities: strong detectability, (weak) detectability,
strong periodic detectability, and (weak) periodic detectability. We
derive necessary and sufficient conditions for these detectabilities.
These conditions can be checked by constructing an observer, which
models the estimation of states under different observations. The
theory developed in this note can be used in feedback control and
diagnosis. If the system is detectable, then the observer can be used
as a diagnoser to diagnose the failure states of the system.

web site: click here