Electrical Engineering and Computer Science

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Term: Winter, 2010
Course No.: 498-001
Credit Hours: 3
Instructor: Stephane Lafortune
Prerequisites: Senior or Graduate standing in EE, CS, CE, ME, or AERO

Course Description:
This course is intended for engineering and computer science seniors and graduate students who want to learn about dynamic systems with discrete state spaces and event-driven transitions. Discrete Event Systems, as they are called, arise in the modeling of technological systems such as automated manufacturing systems, communication networks, software systems, process control systems, and transportation systems. In embedded and networked systems, discrete event dynamics are coupled with continuous dynamics, giving rise to what are called Hybrid Systems. This course will introduce students to the modeling, analysis, and control of discrete event systems. The modeling of hybrid systems will also be introduced. Examples from the above areas will be used throughout the course to illustrate the main concepts.

This course is offered in place of EECS 661, the graduate-level course on Discrete Event Systems that is normally offered in the fall of even years. EECS 661 will not be offered in Fall 2010; the next expected offering of EECS 661 is Fall 2012. Graduate students who intended to take 661 in Fall 2010 should take 498-W10 instead; it will count for graduate credit. 498-W10 is also open to undergraduate seniors. The class material will be adjusted accordingly.

There are no specific course prerequisites other than senior or graduate standing.

For planning purposes, please contact the instructor if you plan to enroll.

Textbook:"Introduction to Discrete Event Systems - Second Edition" by C. Cassandras and S. Lafortune, Springer, 2007

Grading: Homework assignments, two exams, and a short project.

Syllabus: Most of Chapters 2, 4, and 5; part of Chapter 3 of textbook.

Areas of Interest:

  • Finite-state automata models of discrete event systems: notions of deadlock and livelock, product and parallel composition, observer and diagnoser automata.
  • Petri net models of discrete event systems: reachability analysis with coverability tree, structural analysis with invariants.
  • Supervisory control of discrete event systems modeled by automata: controllability and observability, nonblocking control.
  • Control of Petri nets by place invariants.
  • Timed automata models of discrete event systems: parallel composition, reachability analysis by untiming.
  • Hybrid automata models of hybrid systems: basic notions.

The software tool DESUMA will be used in the course.