Course details
Modelling and Simulation
IMS Acad. year 2008/2009 Winter semester 5 credits
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, numerical methods, Modelica language. Simulation experiment control. Visualization and analysis of simulation results.
Guarantor
Language of instruction
Completion
Time span
- 39 hrs lectures
- 4 hrs exercises
- 2 hrs pc labs
- 7 hrs projects
Department
Lecturer
Instructor
Subject specific learning outcomes and competences
Knowledge of simulation principles. The ability to create simulation models of various types. Basic knowledge of simulation system principles.
Learning objectives
The goal is to introduce students to basic simulation methods and tools for modelling and simulation of continuous, discrete and combined systems.
Recommended prerequisites
- Introduction to Programming Systems (IZP)
- Algorithms (IAL)
- Signals and Systems (ISS)
Prerequisite knowledge and skills
Basic knowledge of numerical mathematics, probability and statistics, and basics of programming.
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 Ross, S.: Simulation, Academic Press, 2002, ISBN 0-12-598053-1
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. System Dymola/Modelica.
- Combined simulation. The role of simulation in digital systems design.
- Special model classes, models of heterogeneous systems.
- Cellular automata and simulation.
- Checking model validity, verification of models. Analysis of simulation results.
- Simulation results visualization. Interactive simulation. 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 numerical exercises
- discrete simulation: using Petri nets, using SIMLIB/C++
- continuous simulation: differential equations, block diagrams, examples of models in SIMLIB/C++
Syllabus of computer exercises
- Introduction to Dymola simulation system, continuous simulation.
Progress assessment
At least half of the points you can get during the semester
Teaching methods and criteria
Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.
Controlled instruction
project, midterm exam
Course inclusion in study plans