Control by Artificial Intelligence

Course guarantor:

Lecturer:

Tutor:

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:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: