Course detail

Simulation Modeling

FSI-VMOAcad. year: 2015/2016

Course is focused on gaining knowledge and skill in area of simulation modeling of continuous and discrete dynamic systems and relevant areas. Practical examples are technically oriented and also include simulation of non-linear and chaotic systems. At the end of course are presented simulations of intelligent systems which have wide use in area of modeling and optimization. In computer exercises is used environment of Matlab/Simulink (and selected toolboxes).

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

prof. RNDr. Ing. Jiří Šťastný, CSc.

Department

Institute of Automation and Computer Science (ÚAI)

Learning outcomes of the course unit

Knowledge of simulation principles. The ability to create simulation models of various types. Basic knowledge about nonlinear, chaotic, fractal and intelligent systems.

Prerequisites

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

Co-requisites

Not applicable.

Planned learning activities and teaching methods

The course is taught through lectures explaining the basic principles and theory of the discipline. Exercises are focused on practical topics presented in lectures.

Assesment methods and criteria linked to learning outcomes

Written and oral exam from course's contents, assessment from projects and written tests.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

The goal of the subject is to acquire practical skill of modeling and simulation of dynamic systems. Nonlinear and chaotic systems are included. The goal of the subject is also to make introduction to intelligent system simulation.

Specification of controlled education, way of implementation and compensation for absences

Attendance at lectures is not inspected. Attendance at exercises is obliged. Knowledge of students is verified by elaborated projects and final exam.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Ross S.: Simulation, 3rd edition, Academic Press, 2002
Zeigler B., Praehofer H., Kim T.: Theory of Modelling and Simulation, 2nd edition, Academic Press, 2000
J. Horák, L. Krlín, A. Raidl: Deterministický chaos a jeho fyzikální aplikace, Academia, Praha, 2003
Kvasnička, V., Pospíchal, J., Tiňo, P: Evolučné algoritmy, STU Bratislava, 2000

Recommended reading

Ross S.: Simulation, 3rd edition, Academic Press, 2002
Zeigler B., Praehofer H., Kim T.: Theory of Modelling and Simulation, 2nd edition, Academic Press, 2000
J. Horák, L. Krlín, A. Raidl: Deterministický chaos a jeho fyzikální aplikace, Academia, Praha, 2003
Kvasnička, V., Pospíchal, J., Tiňo, P: Evolučné algoritmy, STU Bratislava, 2000

Classification of course in study plans

  • Programme M2I-P Master's

    branch M-AIŘ , 2. year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

prof. RNDr. Ing. Jiří Šťastný, CSc.

Syllabus

1. Definition of basic terms and model classification: conceptual, abstract and simulation models. Description of models. Basic methods of modelling.
2. Simulation of dynamic systems I. (continuous systems, synchronization of computation)
3. Simulation of dynamic systems II. (continuous and discretized systems)
4. Simulation of dynamic systems III. (ODE solvers and methods of numerical integration)
5. Generators of pseudo random numbers (implementation of generators, tests)
6. Simulation modelling using cellular automata (model of epidemic)
7. Non-linear and chaotic systems I. (deterministic chaos, examples)
8. Non-linear and chaotic systems II. (attractor, Lyapunov stability)
9. Fractals and chaos I. (IFS, generators, fractal dimensions)
10. Fractals and chaos II. (L-systems, models of natural objects)
11. Intelligent systems I. (swarm systems)
12. Intelligent systems II. (evolutionary systems)
13. Intelligent systems III. (cognitive systems)

Computer-assisted exercise

26 hours, compulsory

Teacher / Lecturer

Ing. Petr Jindra

Syllabus

1. Simulation software I. (Simulink, SimMechanics).
2. Simulation software II. (Stateflow, MapleSim).
3. Technical object simulation I. (a car).
4. Technical object simulation I. (water tanks' system, RLC circuit).
5. Random numbers generators.
6. Midterm test and projects instructions.
7. Non-linear systems (examples, simulation modeling)
8. Deterministic chaos. Butterfly effect.
9. Fractal generating I. (IFS, Mandelbrot).
10. Fractal generating I. (L-systems).
11. Intelligent systems I., ant colony cptimization.
12. Intelligent systems II., metaheuristics in optimization tasks.
13. Intelligent systems III., artificial neural network.