352-0505/02 – Modelling and Simulation (MaS)
| Gurantor department | Department of Control Systems and Instrumentation | Credits | 5 |
| Subject guarantor | prof. Ing. Petr Noskievič, CSc. | Subject version guarantor | prof. Ing. Petr Noskievič, CSc. |
| Study level | undergraduate or graduate | | |
| | Study language | English |
| Year of introduction | 2004/2005 | Year of cancellation | 2019/2020 |
| Intended for the faculties | USP, FS | Intended for study types | Follow-up Master, Master |
Subject aims expressed by acquired skills and competences
The goal of this subject to obtain the knowledge from the modelling of the basic dynamic systems and creation of the simulation models. The next goal is to be able to realize the simulation model in the simulation programme and to simulate the responses of the systems. The subject is focused ability to use the basic methods of the mathematical physical modelling, realization and use of the simulation models.
Teaching methods
Lectures
Tutorials
Experimental work in labs
Project work
Summary
Dynamic systems, state space models, linearization. System sensitivity.
Differential equation of higher order. Function approximation. Methods of
numerical solution of differential equations, Runge-Kutta methods.
Predictor-corrector methods. Stiff systems. Stability of the numerical solution.
Stability regions. Model order reduction methods. Simulation of the discrete
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
Active work at the excercises.
3 Projects - max.3 x 10 points,
1 test - max.10 points,
1 task in english - max 5 points.
E-learning
Other requirements
Active work at the excercises.
3 Projects - max.3 x 10 points,
1 test - max.10 points,
1 task in english - max 5 points.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Fundamentals of the dynamic system analysis, comparison of the analytical and experimental methods of the identification.
2. Linear and nonlinear systems. Linearization of models.
3. Time varying systems, time invariant systems, systems with time delay, equilibrium, stability of the equilibrium.
4. Programming of the models in the form of differential equations and transfer functions.
5. Realization of the mathematical models using the simulation programmes. Classification of the simulation programmes.
6. Numerical methods used for the modelling of the static characteristics.
7. Numerical methods for integration and derivative computation.
8. Numerical methods for solution of the differential equations.
9. State space models – numerical solution. Transition matrix.
10. Stability of the methods for the numerical solution of the differential equations.
11. A-stabil, AD-stabil methods of the numerical solution of the differential equations.
12. Discrete event systems. Structure, description, modelling and simulation.
13. Random number generation, Monte Carlo methods for discrete event system modelling.
14. Simulation programmes. Case study.
Conditions for subject completion
Conditions for completion are defined only for particular subject version and form of study
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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