Discrete event systems comprise of discrete state spaces and event

Discrete-Event Systems control theory provides automated control solutions
for systems that are characterized by asynchronous and instantaneous
changes of state; for example, a cluster of machines that each may be “idle”,
“busy”, or “broken”. Goals expressed in the language of this theory permit
the automatic generation of control solutions which guarantee that illegal
behaviour will never occur (within the assumptions of the framework).
Despite intensive research on and expansion of the theoretical aspects of
this field, a limited amount of research has been reported on its
implementation and integration into existing systems.
This thesis focuses on identifying classes of systems upon which the theory
may be applied and isolates and examines the implementation issues that
arise. Methodology for the implementation of the theory is provided and
supported by concrete examples. A software suite with an emphasis on
human-computer interaction was developed to facilitate the application of
the theory. The work described herein constitutes some of the first steps in
making the use of Discrete-Event Systems control theory accessible outside
of the academic realm.
Abstract
The problem of controlling sensory perception for use in discrete event feedback
control systems is addressed in this thesis. The sensory perception controller (SPC) is
formulated as a sequential Markov decision problem. The SPC has two main
objectives; 1) to collect perceptual information to identify discrete events with high
levels of confidence and 2) to keep the sensing costs low. Several event recognition
techniques are available where each of the event recognisers produces confidence
levels of recognised events.
For a discrete event control system running in normal operation, the confidence
levels are typically large and only a few event recognisers are needed. Then, as the
event recognition becomes harder, the confidence levels will decrease and additional
event recognisers are utilised by the SPC. The final product is an intelligent
architecture with the ability to actively control the use of sensory input and
perception to achieve high performance discrete event recognition.
The discrete event control framework is chosen for several reasons. First, the theory
of discrete event systems is applicable to a wide range of systems. In particular,
manufacturing, robotics, communication networks, transportation systems and
logistic systems all fall within the class of discrete event systems. Second, the
dynamics of the sensing signals used by the event recognisers are often strong and
contain a large amount of information at the occurrence of discrete events. Third,
because of the discrete nature of events, feedback information is not required

continuously. Hence, valuable processing time is available between events. Fourth,
the discrete events are a natural common representational format for the sensors. A
common sensor format aids the decision process when dealing with different sensor
types. Fifth, the sensing aspect of discrete event systems has often been neglected in
the literature. In this thesis we present a unique approach to on-line discrete event
identification. The thesis contains both theoretical results and demonstrated real-world
applications. The main theoretical contributions of the thesis are 1) the
development of a sensory perception controller for the dynamic real-time selection
of event recognisers. The proposed solution solves the Markov decision process
using stochastic dynamic programming (SDP). SDP guarantees cost-efficiency of the
real-time SPC by solving a sequential constrained optimisation problem. 2) A
sensitivity analysis method for the sensory perception controller has been developed
by exploring the relationship between
Markov decision theory and linear programming. The sensitivity analysis aids in the
robust tuning of the SPC by finding low sensitivity areas for the controller
parameters. Two real-world applications are presented. First, several event
recognition techniques have been developed for a robotic assembly task. Robotic
assembly fits particularly well in the discrete event framework, where discrete
events correspond to changes in contact states between the workpiece and the
environment. Force measurements in particular contain a significant amount of
information when the contact state changes. Second, the sensory perception control
theory and the sensitivity analysis have been demonstrated for a mobile navigation
problem. The cost-efficient use of sensory perception reduces the need for mobile
robots to carry heavy computational resources.
Abstract
We introduce an extension of the classic Discrete Event System Specification (DEVS) formalism that
includes stochastic features. Based on the use of the probability spaces theory we define the
stochastic DEVS (STDEVS) specification, which provides a formal framework for modeling and
simulation of general non-deterministic discrete event systems. The main theoretical properties of the
STDEVS framework are treated, including a new definition of legitimacy of models in the stochastic
context and a proof of STDEVS closure under coupling. We also illustrate the new
stochastic modeling capabilities introduced by STDEVS and their relation with those found in classic
DEVS. Practical simulation examples are given involving performance analysis of computer systems
and hybrid modeling of networked control systems, applications where the modeling of stochastic
components is vital.
Discrete Event Systems comprise of discrete state spaces and event–driven transitions, and
arise across various domains including computer and communication networks, automated

manufacturing systems, air traffic control systems etc. This project will cover the fundamental
concepts in modeling and analysis of Stochastic Discrete Event Systems, with an emphasis on
understanding computer and communication networks.
Abstract
Implementation of complex discrete event manufacturing systems can be considerably
simplified by use of general reusable software modules, representing the physical
components. At the same time, construction of the control system can be facilitated by
use of formal methods for automatic generation of the control laws. These two aspects
can be joined into a general concept with object oriented modeling and control law
synthesis as foundations. The goal is to allow an operator to specify the product routes
through the system, for each type of product; irrespective of any other type of product
that may be simultaneously present within the production system. Control laws
guaranteeing production according to those product specifications can then be
synthesized, given the model of the system. We will describe such an object-oriented
modeling approach to discrete event manufacturing systems. Based on the supervisory
control theory, using interleaved product routes as specification, it is shown how control
laws can be synthesized. An added complexity is that such a specification becomes
nondeterministic in the sense that the same string of events can lead to different system
states. We have shown that the supervisory control theory can indeed be used with
nondeterministic specifications, but also that the notion of controllability is not strong
enough to guarantee an implementable supervisor.
2)
We propose a logical framework for the control theory of reactive systems modeled by
discrete event systems. The logic is the conjunctive nu-calculus, an expressive fragment
of the powerful mu-calculus. Conjunctive nu-calculus possesses an alternative
presentation based on modal specifications, with simple graphical representations. We
exploit modal specification to specify and to solve the basic centralized control problem:
our class of control objectives strictly subsumes the class of regular languages, normally
used in the classic control theory of discrete-event systems, but the existence of
maximally permissive solutions is however preserved.
Examples of DES are
 Traffic Control Systems
 Automated Manufacturing Systems
 Computer and Communication Networks
 Embedded and Networked Systems and
 Software Systems.

C.1 Software for control of discrete-event systems
TCT The model used in this program package is a deterministic finite generator. The
functions of this program package are supervisory control synthesis as developed by W.M.
Wonham (University of Toronto, Toronto, Canada) and co-workers.
The programs were written by several co-workers of Wonham of which the current addresses are
not known to the author of these notes. The program package is available at
...
C.2 Software for analysis and for verification of discreteevent systems.
COSPAN The model used is deterministic finite generators with infinite-string languages. The
function is primarily verification. The author of the program is Dr. R.P.
Kurshan. For information on the program see the book [21]. The program was developed
at Bell Laboratories which is currently part of the company Lucent Technologies.
Concurrency workbench
97C.3 Software for timed discrete-event systems
KRONOS
UPPAAL
TTCT The model used is that of a timed discrete-event system according to the model
developed by W.M. Wonham and B.A. Brandin, see [5]. The main function of the program
package is supervisory control for timed discrete-event systems. At the moment the software
is intended to be used in educational environments.
The source code of the software is available under General Public License in binary
versions for the operating systems Intel-linux/libc5, Intel-linux/libc6, Dos/Wingx/WinNT
in a DOS-box, and Solaris 2.5. A manual is available.
The software has been developed by Christian Meder based on the publications cited
above. The program package is available to the general public at the ftp site
ftp://pc5.isr.unistuttgart.de/ttct. Christian Meder can be contacted at the email address
meder@isr.unistuttgart.de.
C.4 Software for hybrid systems
HYTECH

SHIFT
C.5 Examples and bench marks
The following list of examples and addresses provides information on examples of discreteevent
systems, timed discrete-event system, and hybrid systems, often in the form of input
for a program package, with which the user can test computer programs.
Examples of supervisory control http://www.control.toronto.edu/projects/train/testbed.html.

Discrete event systems comprise of discrete state spaces and event

More Related Content

What's hot (15)

Viewers also liked (20)

Similar to Discrete event systems comprise of discrete state spaces and event (20)

More from Nitish Nagar (19)

Recently uploaded (20)

Discrete event systems comprise of discrete state spaces and event