Course detail
Simulation of Dynamic Systems
FSI-FSI Acad. year: 2025/2026 Winter semester
Modeling and Simulation is a discipline for developing a level of understanding of the interaction of the parts of a system, and of the system as a whole. The course is focused to continues, discrete and hybrid simulation. Modeling and Simulating by means of finite automata, cellular automata and Petri nets. Modeling and simulating complex reactive systems. Random Number Generation and Monte Carlo Methods. Design of simulation experiments, HIL simulation, visualization and verification.
Language of instruction
Czech
Number of ECTS credits
5
Supervisor
Department
Entry knowledge
Fundamentals of mathematics, including differential and integral calculus of functions in one and more variables and solution of system differential equations. Fundamentals of physics, mechanics, electrical engineering and automatic control, knowledge of programming techniques in environment C/C++ and Matlab.
Rules for evaluation and completion of the course
Course-unit credit is conditional on completing of computer projects. Exam has a written and an oral part and tests students’ knowledge of the subject-matter covered in the course.
Attendance at seminars is checked by means of projects.
Aims
The aim of the course is to make students familiar with the methods and selected software supporting the computer simulation.
Students will be able to use software methods and applications for simulation.
The study programmes with the given course
Programme N-AIŘ-P: Applied Computer Science and Control, Master's, compulsory
Programme B-STR-P: Engineering, Bachelor's
specialization AIŘ: Applied Computer Science and Control, compulsory
Type of course unit
Lecture
26 hours, optionally
Syllabus
P1: Tools for computer simulation.
P2: Basics of system theory. Classification of models.
P3: Formal systems.
P4: Petri's nets and finite automaton. Modeling of parallel processes.
P5: Cellular automatons and their use for simulation.
P6: Agent based modeling.
P7: Modeling and simulation of continuous systems I (description, types and solution).
P8: Modeling and simulation of continuous systems II (ODE solvers, error and stability).
P9: Modeling and simulation of continuous and discrete systems.
P10: Modeling and simulation of event driven systems.
P11: Modeling and simulation of stochastic systems. Method Monte Carlo.
P12-13: Modern trends in simulation (HIL simulation, dSpace tools for simulations in automobiles and aeronautics).
Computer-assisted exercise
26 hours, compulsory
Syllabus
Computer labs (exercises) are consistent with the content of lectures. The aim of the labs is to introduce students to practical part of the course above all using Matlab/Simulink system.
The labs are divided into nine parts (modeling and simulation):
a) Mechanical systems
b) Electromechanical systems
c) Logical and electronic systems
d) Fluid systems
e) Stochastic systems (pseudorandom number generators)
f) Cellular automata. Agent based systems.
g) Event driven systems.
h) Petri nets.
i) Fuzzy models.