Modelling and Simulation

• 39 hrs lectures
• 4 hrs exercises
• 9 hrs projects

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

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

• Algorithms (IAL)
• Signals and Systems (ISS)
• Introduction to Programming Systems (IZP)

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

• 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

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

1. discrete simulation: using Petri nets, using SIMLIB/C++
2. continuous simulation: differential equations, block diagrams, examples of models in Dymola

At least half of the points you can get during the semester

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.