Course detail
Discrete Event Systems
FEKT-MPC-SDUAcad. year: 2024/2025
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
Czech
Number of ECTS credits
6
Mode of study
Not applicable.
Guarantor
Entry knowledge
The subject knowledge on the Bachelor´s degree level is requested. Basic knowledge of systems modeling (BPC-MOD).
Rules for evaluation and completion of the course
Lesson. project/tests Max. 30 points.
Examination. Max. 70 points.
Conditions for awarding the course-unit credit:
1. Active participation in exercises
2. Minimum of 10 points awarded for projects and tests
The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.
Examination. Max. 70 points.
Conditions for awarding the course-unit credit:
1. Active participation in exercises
2. Minimum of 10 points awarded for projects and tests
The content and forms of instruction in the evaluated course are specified by a regulation issued by the lecturer responsible for the course and updated for every academic year.
Aims
This subject presents the field of systems with discrete character from its essence (contrary to discrete control of continuous systems). This is the question of systems of piece production, of bulk service, traffic systems etc. The subject is interested in modeling, control and optimization of behavior of discrete events. It deals in details with the formulation of the tasks of operations scheduling in computer, traffic and especially in production systems. It gives the overview of using the Witness simulation system - one of the top solutions in the field of discrete event system simulation.
Student can:
- 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
Student can:
- 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
Study aids
Not applicable.
Prerequisites and corequisites
Not applicable.
Basic literature
Václavek, P.: Systémy diskrétních událostí, příklady. ET VUT FEKT, Brno, 2008. (CS)
Recommended reading
Cassandras, C.G., Lafortune, S.: Introduction to Discrete Event Systems, Springer, 2007 (EN)
Elearning
eLearning: currently opened course
Classification of course in study plans
- Programme MPC-KAM Master's 2 year of study, winter semester, compulsory-optional
Type of course unit
Lecture
26 hod., optionally
Teacher / Lecturer
Syllabus
Descrete event systems and models
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
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
26 hod., compulsory
Teacher / Lecturer
Syllabus
Descrete event systems and models
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
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
Elearning
eLearning: currently opened course