Course details

Modelling and Simulation

MSI Acad. year 2004/2005 Winter semester 6 credits

Current academic year

Introduction to modelling and simulation concepts. System analysis and classification. Abstract and simulation models. Continuous, discrete, and combined models. Heterogeneous models. Using Petri nets and finite automata in simulation. Pseudorandom number generation and testing. Queuing systems. Monte Carlo method. Continuous simulation. Simulation experiment control. Visualization and analysis of simulation results.

Guarantor

Rábová Zdeňka, doc. Ing., CSc.

Language of instruction

Czech

Completion

Credit+Examination

Time span

  • 39 hrs lectures
  • 6 hrs exercises
  • 2 hrs pc labs
  • 16 hrs projects

Department

Department of Intelligent Systems (UITS)

Subject specific learning outcomes and competences

Knowledge of simulation principles. The ability to create simulation model of various types. Basic knowledge of simulation system principles.

Ability to create, verify, and validate simulation models.

Learning objectives

The goal is to introduce students to basic simulation methods and tools for modelling and simulation of continuous, discrete and combined systems.

Prerequisite knowledge and skills

There are no prerequisites

Study literature

  • Rábová Z. a kol: Modelování a simulace, VUT Brno, 2002, ISBN 80-214-0480-9
  • Soubor materiálů prezentovaných na přednáškách je dostupný na WWW.

Fundamental literature

  • 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
  • Rábová Z. a kol: Modelování a simulace, VUT Brno, 1992

Syllabus of lectures

  • Introduction to modelling and simulation. System analysis, clasification of systems. System theory basics, its relation to simulation.
  • Model classification: conceptual, abstract, and simulation models. Heterogeneous models. Methodology of model building.
  • Simulation systems and languages, means for model and experiment description. Principles of simulation system design.
  • Parallel process modelling. Using Petri nets and finite automata in simulation.
  • Models o queuing systems. Discrete simulation models. Model time, simulation experiment control.
  • Continuous systems modelling. Overview of numerical methods used for continuous simulation.
  • Combined simulation. The role of simulation in digital systems design.
  • Special model classes, models of heterogeneous systems.
  • Checking model validity, verification of models. Analysis of simulation results.
  • Simulation results visualization. Interactive simulation, virtual reality.
  • Design and control of simulation experiments. Model optimization.
  • Generating, transformation, and testing of pseudorandom numbers. Stochastic models, Monte Carlo method.
  • Overview of commonly used simulation systems.

Syllabus of computer exercises

  • Modelling of continuous systems in object-oriented environment
  • Modelling of discrete systems
  • Petri nets in simulation
  • PNtalk system
  • Graphical support for simulation

Progress assessment

Výuka není kontrolována.

Controlled instruction

There are no checked study.

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