Course detail

Modelling and Simulation

FIT-IMSAcad. year: 2024/2025

Introduction to modelling and simulation concepts. System analysis and classification. Abstract and simulation models. Continuous, discrete, and hybrid models. Using Petri nets in the simulation. Pseudorandom number generation and testing. Queuing systems. Monte Carlo method. Continuous simulation, numerical methods, Modelica language. Simulation experiment control. Visualization and analysis of simulation results.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

Dr. Ing. Petr Peringer

Department

Department of Intelligent Systems (UITS)

Entry knowledge

Basic knowledge of numerical mathematics, probability, statistics, and basics of programming.

Rules for evaluation and completion of the course

Project, midterm exam, final exam (written). Exam prerequisites: At least 10 points you can get during the semester.
Within this course, attendance on the lectures is not monitored. The knowledge of students is examined by the projects and by the final exam. The minimal number of points which can be obtained from the final exam is 30. Otherwise, no points will be assigned to a student.

Aims

The goal is to introduce students to basic simulation methods and tools for modelling and simulation of continuous, discrete and hybrid systems.
Result will be basic knowledge of systems modelling, simulation system implementation principles, and the ability to create simulation models of various types.

Study aids

Not applicable.

Prerequisites and corequisites

Basic literature

Cellier F., Kofman E.: Continuous System Simulation. Springer 2000.
Fishwick P.: Simulation Model Design and Execution, PrenticeHall, 1995, ISBN 0-13-098609-7 Law A., Kelton D.: Simulation Modelling and Analysis, McGraw-Hill, 1991, ISBN 0-07-100803-9 Ross, S.: Simulation, Academic Press, 2002, ISBN 0-12-598053-1

Recommended reading

Fishwick P.: Simulation Model Design and Execution, PrenticeHall, 1995, ISBN 0-13-098609-7 (EN)
Law A., Kelton D.: Simulation Modelling and Analysis, McGraw-Hill, 1991, ISBN 0-07-100803-9
Modelica - A Unified Object-Oriented Language for Systems Modeling -Language Specification, Version 3.4, Modelica Association, 2017
Peringer P.: Modelování a simulace, studijní opora, FIT/ESF, 2006-2012 (CS)
Rábová Z. a kol: Modelování a simulace, VUT Brno, 1992, ISBN 80-214-0480-9 (CS)
Ross, S.: Simulation, Academic Press, 2002, ISBN 0-12-598053-1 (EN)
Soubor materiálů prezentovaných na přednáškách je dostupný na WWW. (CS)
Texts available on course WWW page. (EN)

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme BIT Bachelor's 3 year of study, winter semester, compulsory
  • Programme BIT Bachelor's 3 year of study, winter semester, compulsory

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

Dr. Ing. Petr Peringer
Ing. Martin Hrubý, Ph.D.

Syllabus

  1. Introduction to modelling and simulation. System analysis, classification of systems. Basic introduction to systems theory.
  2. Model classification: conceptual, abstract, and simulation models. Multimodels. Basic methods of model building.
  3. Simulation systems and languages, basic means of model and experiment description. Principles of simulation system implementation.
  4. Generating, transformation, and testing of pseudorandom numbers. Stochastic models, Monte Carlo methods.
  5. Parallel process modelling. Using Petri nets in simulation.
  6. Models o queuing systems. Discrete simulation models.
  7. Time and simulation experiment control, "next-event" algorithm.
  8. Cellular automata and simulation.
  9. Continuous systems modelling. Overview of numerical methods for continuous simulation. Introduction to Modelica.
  10. Combined/hybrid simulation, state events. Modelling of digital systems.
  11. Special model classes, models of heterogeneous systems, model parameters optimization overview.
  12. Analytical solution of queuing system models.
  13. Checking of model validity, verification of models. Analysis of simulation results.

Seminar

4 hod., compulsory

Teacher / Lecturer

Ing. Martin Hrubý, Ph.D.

Syllabus

  1. discrete simulation: using Petri nets
  2. continuous simulation: differential equations, block diagrams, examples of models

Project

9 hod., compulsory

Teacher / Lecturer

Ing. Martin Hrubý, Ph.D.

Syllabus

Individual selection of a suitable problem, its analysis, simulation model creation, experimenting with the model, and analysis of results.

E-learning texts

slajdy IMS
IMS.pdf 1.72 MB

Elearning

eLearning: currently opened course