Fall 1999
General Course Information
Motivation
- Current real world systems are becoming increasingly complex.
- Typical examples: large networks of computers, flexible
manufacturing systems, vehicular traffic systems, supervisory control
systems.
- Need new paradigms for design, modeling, analysis, control, and
optimization of such systems.
- Current viewpoint: discrete event systems.
- Bring together techniques from control theory, communication
networks, computer science, and operations research for solving engineering
problems.
- Underlying goal: provide broad background in useful techniques
and tools for dealing with discrete event systems.
Objectives
To provide students with a broad background in
useful techniques and tools relevant to the design, modeling, analysis,
control, and optimization of discrete event systems; to
introduce students to current research topics in discrete
event systems and to prepare students to undertake such research; to
promote an awareness of the need for new paradigms for approaching
problems involving increasingly complex man-made systems; to bring
together techniques from control theory, communication networks,
computer science, and operations research for solving engineering
problems.
Brief Course Description
- Models and tools for the design and analysis of discrete event systems.
- Topics
include deterministic and stochastic models of discrete event
systems, supervisory control, simulation, gradient
estimation, stochastic optimization methods, and hybrid systems.
- Application examples in communication/computer networks, real-time
computer systems, and manufacturing systems are provided.
References
- Class notes.
- C.G. Cassandras,
Discrete Event Systems: Modeling and Performance Analysis,
Richard D. Irwin, Inc., and Aksen Associates, Inc., 1993.
- Y.C. Ho and X.R. Cao, Perturbation Analysis of Discrete Event
Systems, Kluwer, 1991.
- P. Glasserman, Gradient Estimation via Perturbation Analysis,
Kluwer, 1991.
- Papers in the literature.
Prerequisites
- EE 580 and EE 302, or equivalent.
- Basic state space systems in discrete time (desirable but not required).
- An appreciation of rigor.
Contact information
Professor Edwin K. P. Chong
Course web page:
Professor Edwin K. P. Chong,
echong@ecn.purdue.edu
This document was last modified
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