Term: Fall 2007
Course No.: 498-002
Credit Hours: 3
Instructor: Stephane Lafortune
Prerequisites: Junior standing
This course is intended for undergraduate 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 and analysis of discrete event and hybrid systems. Examples from the above areas will be used throughout the course to illustrate the main concepts.
There are no specific course prerequisites; however, the course is aimed at juniors and seniors in EE, CE, CS, or ME. Some basic knowledge of probability (from e.g., Math 425 or EECS 401 or IOE 265 or Stat 412) is recommended for the last part of the course.
Finite-state automata models of discrete event systems: notions of deadlock and livelock, product and parallel composition, observers, diagnosers.
Petri net models of discrete event systems: reachability analysis with coverability tree, structural analysis with invariants.
Timed automata models of discrete event systems: parallel composition, reachability analysis by untiming.
Hybrid automata models of hybrid systems: basic notions.
Stochastic models of discrete event systems: stochastic automata, Markov chains, introduction of queueing models.
Introduction to discrete event simulation.
Textbook:"Introduction to Discrete Event Systems - Second Edition"by C. Cassandras and S. Lafortune, Springer, 2007
Grading:Homework assignments, two exams, and a project.
Several software tools will be used in the course: UMDES, DESUMA, Matlab with Stateflow and SimEvents. [Full Story]