Course details
Modelling and Simulation
IMS Acad. year 2012/2013 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
- 9 hrs projects
Department
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. Multimodels. Basic methods 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, "next-event" algorithm.
- Continuous systems modelling. Overview of numerical methods used for continuous simulation.
- Introduction to Dymola simulation system.
- Combined/hybrid simulation. Modelling of digital systems.
- Special model classes, models of heterogeneous systems.
- Cellular automata and simulation.
- Checking model validity, verification of models. Analysis of simulation results. Visualization of simulation results. Model optimization.
- Generating, transformation, and testing of pseudorandom numbers. Stochastic models, Monte Carlo methods.
- Basic 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 Dymola
Progress assessment
At least 10 points you can get during the semester
Controlled instruction
Within this course, attadance 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.
Course inclusion in study plans