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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2024/2025
NOTICE: Study plans for the following academic year are available.

Control by Artificial Intelligence

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Code Completion Credits Range
W31OZ008 ZK 26P+52C
Course guarantor:
Ivo Bukovský, Michael Valášek
Lecturer:
Václav Bauma, Ivo Bukovský, Zbyněk Šika, Michael Valášek
Tutor:
Václav Bauma, Ivo Bukovský, Zbyněk Šika, Michael Valášek
Supervisor:
Department of Mechanics, Biomechanics and Mechatronics
Synopsis:

The student will be acquainted with the methods of control of mechanical systems by means of artificial intelligence.

Artificial intelligence. History, definition.

Control by rule-based system. Production system, state space search.

Lyapunov stability.

Fuzzy sets, language variables, solution of the principle of extensionality.

Fuzzy control.

Neuron and its model, types of neural networks and their learning.

Linear and nonlinear neuron.

Generalization of learning.

Functions with radial base

Control by neural network.

LOLIMOT

Genetic algorithms

Requirements:
Syllabus of lectures:
Syllabus of tutorials:
Study Objective:
Study materials:

Kevin Warwick: Artificial Intelligence: The Basics, Springer 2011

Kosko, B.: Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence, Prentice Hall 1994

Aggarwal, C.C.: Neural Networks and Deep Learning, Springer 2018

Štefan, M.; Šika, Z.; Valášek, M.; Bauma, V.: Neuro-Fuzzy Identification of Nonlinear Dynamic MIMO Systems

Inženýrská mechanika. 2006, 13(3), pp. 223-238.

odkaz: https://moodle-vyuka.cvut.cz/

Note:
Time-table for winter semester 2024/2025:
Time-table is not available yet
Time-table for summer semester 2024/2025:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2025-03-19
For updated information see http://bilakniha.cvut.cz/en/predmet6688806.html