The module introduces the basic techniques involved in the modeling, analysis and supervisory control of discrete event systems. Both logic models (such as Automata) and timed models (such as Markov chains) will be looked at in a deterministic and non-deterministic set-up.

On successfully completing this module you shall be able to: 1. Assess the the suitabillity of a system for modeling in a discrete-event set-up; 2. Create a discrete-event model and assess its structural properties; 3. Design algorithms for the qualitative and quantitative analysis of Discrete Event Systems; 4. Design a supervisory controller and an observer automaton; 5. Simulate a discrete event system; 6. Assess the performance of the system in a deterministic and stochastic set-up.

Finite state Automata: deterministic and non-deterministic; Supervisory Control; Petri Nets; Timed Automata: stochastic and deterministic; Markov Chains.