Course unit code:
Course unit title:
Intelligent Control
Mode of completion and Number of ECTS credits:
Exm (3 credits)
Course supervisor:
prof. Ing. Michal Kvasnica, PhD.
Name of lecturer(s):
R. Kohút, M. Kvasnica, M. Wadinger (2022/2023 – Winter)
R. Kohút, M. Kvasnica (2021/2022 – Winter)
R. Kohút, M. Kvasnica (2020/2021 – Winter)
A. Mészáros, A. Vasičkaninová (2019/2020 – Winter)
A. Mészáros (2018/2019 – Winter)
A. Mészáros (2017/2018 – Winter)
A. Mészáros (2015/2016 – Winter)
Learning outcomes of the course unit:
Students know to apply artificial intelligence methods (methods of patterns recognition, problem solving, expert systems, fuzzy logic, fuzzy modeling and control, artificial neural networks, evolutionary algorithms) to solve problems in the identification, modeling and control of technological processes.
Prerequisites for registration:
Course contents:
Introduction to problems of artificial intelligence
Recognition methods (statistical and structural)
Problem solving
Expert Systems (diagnostic and planning)
Fuzzy logic, fuzzy identification, fuzzy modelling and control
Neural networks in identification and management
Neuro - fuzzy control
Evolutionary algorithms in intelligent control
Recommended or required reading:
  • NÁVRAT, P. Umelá inteligencia. Bratislava: STU, 2002.
  • NÁVRAT, P. – BIELIKOVÁ, M. – BEŇUŠKOVÁ, Ľ. – KAPUSTÍK, I. – UNGER, M. Umelá inteligencia. Bratislava : STU v Bratislave, 2007. 393 s. ISBN 978-80-227-2629-0.
  • WARWICK, K. Neural networks for control and systems. London : Peter Peregrinus, 1992. 260 s. ISBN 0-86341-279-3.
  • TSOUKALAS, L H. – UHRING, R E. Fuzzy and neural approaches in engineering. New York : John Wiley & Sons, 1997. 587 s. ISBN 0-471-16003-2.
  • ZHANG, H. – LIU, D. Fuzzy Modeling and Fuzzy Control. Boston : Birkhäuser, 2006. 416 s. ISBN 978-0-8176-4491-8.
Planned learning activities and teaching methods:
lecture, exercise
Assesment methods and criteria:
Language of instruction:
Slovak, English
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