450-8707/02 – Non-Conventional Methods of Mechatronical Systems Control (NMŘMS)

Gurantor departmentDepartment of Cybernetics and Biomedical EngineeringCredits4
Subject guarantorIng. Zdeněk Slanina, Ph.D.Subject version guarantorIng. Zdeněk Slanina, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Study languageEnglish
Year of introduction2015/2016Year of cancellation
Intended for the facultiesUSP, FSIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
SLA77 Ing. Zdeněk Slanina, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Part-time Credit and Examination 0+12

Subject aims expressed by acquired skills and competences

To acquaint students with modern and efficient control methods, which use non-numeric descriptions of the control law in the science of artificial intelligence. Students will acquire knowledge of fuzzy set mathematics and fuzzy logic, artificial neural networks and evolutionary algorithms. Acquires skills in the design, debugging and application of fuzzy controllers, neural controllers and special intelligent controllers and advanced optimization using genetic algorithms. For the controller design and simulation is used Matlab-Simulink.

Teaching methods

Project work


The course is based on selected methods of artificial intelligence applied in the synthesis of non-conventional controllers of mechatronic systems. Approaches are used Mamdani and Takagi-Sugeno fuzzy controllers and fuzzy-neural controllers. To adapt and optimize the structure and controller parameters are used genetic algorithms. Computer simulations are carried out in Matlab-Simulink.

Compulsory literature:

GANG,F. Analysis and Synthesis of Fuzzy Control Systems: A Model-Based Approach. CRC Press, 2010. ISBN 9781420092646 MATA,F., MARICHAL,G.N., JIMNEZ,E. Fuzzy Modeling and Control: Theory and Applications. Atlantis Publishing Corporation, 2014 ISBN 9462390819.

Recommended literature:

RUSSEL,S., NORVIG,P.: Artificial Intelligence, Prentice-Hall, Inc., 2003, ISBN 0-13-080302-2

Way of continuous check of knowledge in the course of semester

Credit conditions: Students can reach 40 (21 minimal) points for essays and term labor. Completion of the course: Students must receive credit and pass the final exam. Final exam has two parts - Written exam with a gain of 40 (10 minimal) and points - Oral exam with a gain of 20 (6 minimal) points The completion of this course the student must complete both parts of the final exam.


Other requirements

There are not defined other requirements for student


Subject has no prerequisities.


Subject has no co-requisities.

Subject syllabus:

1. Artificial intelligence principles, non-conventional description of complex systems 2. Principles and approaches of knowledge based non-numerical modelling and control 3. Principles of fuzzy sets and fuzzy linguistic logic 4. Rule based modelling, aproximative reasoning and results interpretation, expert systems 5. Fuzzy logic based controller analysis and synthesis, structures and their properties in comparison with conventional controllers 6. Fuzzy control and its application in mechatronics 7. Artificial neural networks, structures and self-learning principles 8. Neural controller synthesis an their properties discussion 9. Combined fuzzy-neural controllers 10. Evolution and genetic algorithms in tasks of optimization of structures and parameters of conventional controllers 11. Genetic algorithms application issues, advanced genetic algorithms and their properties 12. Structural and parameter optimization of non-conventional controllers using genetic algorithms 13. Computational intelligence, integrated fuzzy-neuro-genetic structures in control 14. Intelligent controllers, their structure and application

Conditions for subject completion

Full-time form (validity from: 2016/2017 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 40  21
        Examination Examination 60 (60) 30
                Písemná zkouška Written examination 40  10
                Ústní zkouška Oral examination 20  6
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2021/2022 (N0714A270004) Mechatronics CMS P English Ostrava 2 Compulsory study plan
2020/2021 (N0714A270004) Mechatronics CMS P English Ostrava 2 Compulsory study plan
2019/2020 (N3943) Mechatronics (3906T006) Mechatronic Systems P English Ostrava 2 Compulsory study plan
2019/2020 (N0714A270004) Mechatronics CMS P English Ostrava 2 Compulsory study plan
2018/2019 (N3943) Mechatronics (3906T006) Mechatronic Systems P English Ostrava 2 Compulsory study plan
2017/2018 (N3943) Mechatronics (3906T006) Mechatronic Systems P English Ostrava 2 Compulsory study plan
2016/2017 (N3943) Mechatronics (3906T006) Mechatronic Systems P English Ostrava 2 Compulsory study plan
2015/2016 (N3943) Mechatronics (3906T006) Mechatronic Systems P English Ostrava 2 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner