SYLLABUS

University: Technical University of Košice

Faculty: Faculty of Electrical Engineering and Informatics

Department: Department of Cybernetics and Artificial Intelligence

Course Number: 26000781

Course Name: Fuzzy Systems

Type, scope and method of learning activities:
Course Type: Lecture, Numerical exercises, Laboratory exercise
Recommended scope of the course content (in hours):
Full-time study (hours per week): 2,1,1
Part-time study (hours per semester): ST 26,13,13
Study Method: Attendance

Number of credits: 6

Recommended semester of study: ST

Recommended semester

Study programme

Study grade

Study Method

2.rok ST

Intelligent Systems (IS_Bc_D_sk)

Bachelor

Attendance

Level of study:

Prerequisites:

Course completion requirements:
Assessment and completion of the course: Credit test and examination
Continuous assessment: Student passes the continuous assessment and receives credits when he or she meets the requirement to obtain at least 21% out of 40%.
consecutive tests, projects
Final assessment: Student passes the final assessment and passes the examination when he or she meets the requirement to obtain at least 31% out of 60%.
final test nad oral examination
Overall assessment: Overall assessment is the sum of the assessments obtained by students in the assessment period. The overall result is determined in accordance with the internal regulations of the Technical University in Košice. (Study Regulations, the internal regulation principles of doctoral studies)

Learning outcomes:
A graduate gains knowledge about utilization of means based on the fuzzy sets theory in the area of dynamic systems models design, control and parameter optimization of fuzzy systems as well as their use in systems for decision support. From this reason the graduate obtains necessary knowledge about fuzzy systems and related methods for modelling, simulation, control and decision making, together with knowledge about evaluation of typical experiments in such a measure that he/she will be able to utilize gained knowledge in real tasks of various projects with help of efficient information processing, analysis of a given task and programming techniques based on the fuzzy sets theory.

Brief course content:
• Description and utilization of uncertainty in control.
• Detailed description of several types of fuzzy controllers (Mamdani, TSK, adaptive, sliding mode control).
• Approaches of knowledge base design.
• Fuzzy systems for decision making support.
• Other type of fuzzy systems as extensions of conventional control and decision making means (fuzzy cognitive maps, fuzzy clustering, etc.).
• Type-2 fuzzy systems.
• Hardware and software support of fuzzy systems.
• Fuzzy programming and its types.
• Fuzzy data, their analysis, similarity of data.
• General theory of uncertainty – overview of various uncertainty types and relations among them.

Recommended Reference Sources:
• Jura, P.: Základy fuzzy logiky pro řízení a modelování (učebnica); VUT Brno, 2003.
• Vaščák, J.: Fuzzy logika v regulácii (učebný text); Technická Univerzita Košice, 2008.
• Cherkassky, V. – Mulier, F.: Learning from Data – Concepts, Theory and Methods; John Wiley a Sons, 1998.

Recommended optional program components:

Languages required for the course completion: Slovak

Notes:

Course assessment:
Total number of students assessed: 33

27%

24%

45%

Teacher:
prof. Ing. Peter Sinčák, CSc.

Last modified: 31.08.2017

Approved by: person(s) responsible for the study program