Course detail
Discrete Event Systems
FEKT-LSDUAcad. year: 2018/2019
Discrete event systems and their typical examples, modelling, Basic modeling concepts. Petri nets, definitions, types, purpose, autonomous PN, colored PN. Sequence systems. Markov chains and processes, queueing systems.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Learning outcomes of the course unit
- analyse behaviour of discrete event systems
- design models for simple discrete event systems
- write discrete event systems model in different representations
- compute basic statistics for queing systems
- analyse simple Markov networks
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Examination. Max. 70 points.
Conditions for awarding the course-unit credit:
1. Active participation in exercises
2. Minimum of 10 points awarded for home-works
Course curriculum
Automata, basic concepts
Automata and language relation
Petri nets
Timed systems
Hybrid systems
Stochastic timed systems
Discrete event systems control
Discrete time Markov chains
Continuous time Markov processes
Queuing theory
Markov chains control
Discrete event systems simulation
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Recommended reading
Classification of course in study plans
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
Automata, basic concepts
Automata and language relation
Petri nets
Timed systems
Hybrid systems
Stochastic timed systems
Discrete event systems control
Discrete time Markov chains
Continuous time Markov processes
Queuing theory
Markov chains control
Discrete event systems simulation
Exercise in computer lab
Teacher / Lecturer
Syllabus
Automata, basic concepts
Automata and language relation
Petri nets
Timed systems
Hybrid systems
Stochastic timed systems
Discrete event systems control
Discrete time Markov chains
Continuous time Markov processes
Queuing theory
Markov chains control
Discrete event systems simulation