Učni načrt predmeta

Predmet:
Modeliranje dinamičnih sistemov
Course:
Modelling of Dynamic Systems
Študijski program in stopnja /
Study programme and level
Študijska smer /
Study field
Letnik /
Academic year
Semester /
Semester
Informacijske in komunikacijske tehnologije, 3. stopnja Inteligentni sistemi in robotika 1 1
Information and communication technologies, 3rd cycle Intelligent Systems and Robotics 1 1
Vrsta predmeta / Course type
Izbirni / Elective
Univerzitetna koda predmeta / University course code:
IKT3-624
Predavanja
Lectures
Seminar
Seminar
Vaje
Tutorial
Klinične vaje
work
Druge oblike
študija
Samost. delo
Individ. work
ECTS
15 15 15 105 5

*Navedena porazdelitev ur velja, če je vpisanih vsaj 15 študentov. Drugače se obseg izvedbe kontaktnih ur sorazmerno zmanjša in prenese v samostojno delo. / This distribution of hours is valid if at least 15 students are enrolled. Otherwise the contact hours are linearly reduced and transfered to individual work.

Nosilec predmeta / Course leader:
doc. dr. Damir Vrančić
Sodelavci / Lecturers:
Jeziki / Languages:
Predavanja / Lectures:
Slovenščina, angleščina / Slovene, English
Vaje / Tutorial:
Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:
Prerequisites:

Zaključen študij druge stopnje s področja informacijskih ali komunikacijskih tehnologij ali zaključen študij druge stopnje na drugih področjih z znanjem osnov s področja predmeta. Potrebna so tudi osnovna znanja matematike, računalništva in informatike.

Completed second-cycle studies in information or communication technologies or completed second-cycle studies in other fields with knowledge of fundamentals in the field of this course. Basic knowledge of mathematics, computer science and informatics is also requested.

Vsebina:
Content (Syllabus outline):

1. Uvod
- Uvod v sisteme
- Lastnosti dinamičnih sistemov
- Pristopi k modeliranju dinamičnih sistemov
- Faze procesa sinteze modela dinamičnega sistema

2. Dinamični sistemi
- Tipologija dinamičnih sistemov
- Linearni dinamični sistemi
- Nelinearni dinamični sistemi
- Stohastični dinamični sistemi

3. Simulacija dinamičnih sistemov
- Osnove numerične integracije
- Simulacija dinamičnih sistemov
- Orodja za simulacijo dinamičnih sistemov

4. Modeliranje dinamičnih sistemov
- Metode modeliranja dinamičnih sistemov
- Linearne metode identifikacije
- Nelinearne metode identifikacije
- Optimizacija modela dinamičnega sistema
- Validacija modelov
- Primeri modeliranja iz prakse

1. Introduction
- Introduction to systems
- Properties of dynamic systems
- Approaches to modelling dynamic systems
- Phases of process model dynamic system synthesis

2. Dynamic systems
- Typology of dynamical systems
- Linear dynamic systems
- Nonlinear dynamic systems
- Stohastic dynamic systems

3. Simulation of dynamic systems
- Basics of numeric integration
- Simulation of dynamic systems
- Tools for simulation of dynamic systems

4. Modelling of dynamic systems
- Methods of dynamic systems modelling
- Linear identification methods
- Nonlinear identification methods
- Optimisation of dynamic system model
- Models validation
- Examples of modelling in practice

Temeljna literatura in viri / Readings:

Knjige/Books:
S. Strmčnik and Đ. Juričić (Eds.) (2013). Case studies in Control - Putting Theory to Work. Springer.
E. Cumberbatch and A. Fitt (2001). Mathematical Modelling: Case Studies from Industry. University
Press, Cambridge.
Hangos, K.M. and I.T. Cameron (2001). Process Modelling and Model Analysis. Academic Press, London.
J. Kocijan (2016). Modelling and control of dynamic systems using Gaussian process models. Springer.
E. Zauderer (2006). Partial Differential Equations of Applied Mathematics. Willey&Sons, New Jersey.
A. M. Law, W. D. Kelton (2000). Simulation modeling and analysis, McGraw-Hill.

Cilji in kompetence:
Objectives and competences:

Cilji predmeta so:
- seznanjanje z lastnostmi dinamičnih sistemov
- usposobljenost za modeliranje linearnih in nelinearnih dinamičnih sistemov in validacijo modelov
- kompetentnost za delo s simulacijskimi orodji

Pridobljene kompetence:
- poznavanje osnovnih konceptov dinamičnih sistemov
- poznavanje metod za modeliranje dinamičnih sistemov iz podatkov
- sposobnost uporabe identifikacijskih in optimizacijskih algoritmov
- zmožnost uporabe simulacijskih orodij

Course objectives:
- understanding dynamic system characteristics
- qualification for modeling linear and nonlinear dynamic systems and validation of models - competence for work with simulation tools

Competences:
- knowledge of basic concepts of dynamic systems
- knowledge of methods for modeling dynamic systems from data
- ability to use the identification and optimization algorithms
- the ability to use simulation tools

Predvideni študijski rezultati:
Intendeded learning outcomes:

Študenti bodo z uspešno opravljenimi obveznostmi tega predmeta pridobili:
- osnovno znanje o dinamičnih sistemih
- znanja o modeliranju dinamičnih sistemov
- znanja o nekaterih identifikacijskih in optimizacijskih algoritmih
- razumevanje pravilnega vrednotenja modela
- razumevanje konceptov regulacije
- sposobnost uporabe identifikacijskih in optimizacijskih algoritmov
- zmožnost uporabe simulacijskih orodij

Students successfully completing this course will acquire:
- basic knowledge about dynamic systems
- knowledge about dynamic systems modelling
- knowledge about some identification and optimisation algorithms
- ability for their selection and proper use
- understanding the proper evaluation of the model
- understanding control concepts
- ability to use the identification and optimization algorithms
- ability to use simulation tools

Metode poučevanja in učenja:
Learning and teaching methods:

Interaktivno delo s študentom v okviru predavanj in seminarske naloge z vključevanjem metod komparativne analize, sinteze in prepoznavanja struktur in vzorcev znanja ter usmerjanega reševanja realnih problemov.

Interactive work with a student in the frame of lectures and seminar work, including methods of comparative analysis, synthesis and recognition of knowledge structures and patterns, and supervised solving of real problems.

Načini ocenjevanja:
Delež v % / Weight in %
Assesment:
Seminarska naloga s predstavitvijo in zagovorom rešitve izbranega primera iz študentovega raziskovalnega dela
50 %
Seminar work with presentation and defence of the proposed solving of the selected problem from student’s research work
S pisnim delom izpita se preverjajo teoretična in praktična znanja o senzorjih v procesnem vodenju
50 %
Written exam, which assesses knowledge of the theory and the implementation of concepts of sensors in process control
Reference nosilca / Lecturer's references:
1. HUBA, Mikuláš, BISTÁK, Pavol, VRANČIĆ, Damir. Series PIDA controller design for IPDT processes. Applied sciences. Feb. 2023, vol. 13, iss. 4, [article no.] 2040, str. 1-26, ilustr. ISSN 2076-3417
2. HUBA, Mikuláš, BISTÁK, Pavol, VRANČIĆ, Damir. Robust stability analysis of filtered PI and PID controllers for IPDT processes. Mathematics. Jan. 2023, vol. 11, iss. 1, [article no.] 30, str. 1-24, ilustr. ISSN 2227-7390
3. VRANČIĆ, Damir, MOURA OLIVEIRA, Paulo, BISTÁK, Pavol, HUBA, Mikuláš. Model-free VRFT-based tuning method for PID controllers. Mathematics. Feb. 2023, vol. 11, iss. 3, [article no.] 715, str. 1-29
4. HUBA, Mikuláš, BISTÁK, Pavol, VRANČIĆ, Damir. Parametrization and optimal tuning of constrained series PIDA controller for IPDT models. Mathematics. Oct. 2023, vol. 11, iss. 20, [article no.] 4229, str. 1-32, ilustr. ISSN 2227-7390
5. HUBA, Mikuláš, VRANČIĆ, Damir. Tuning of PID control for the double integrator plus dead time model by modified real dominant pole and performance portrait methods. Mathematics. 2022, vol. 10, iss. 6, str. 971-1-971-25, ilustr. ISSN 2227-7390