Fuzzy Control

Lecturer:

Tutor:

Supervisor:

Department of Control Engineering

Synopsis:

The scope of the course is to present the basic principles, methods and algorithms in fuzzy logic modelling and control of dynamical systems. The lectures are focusing on basics of fuzzy logics and general design of fuzzy logic systems and structure and learning algorithms of the most used neural and fuzzy neural networks.The obtained knowledge is then applicated on problem solving in modelling and control of dynamical systems. The students will verify the algorithms on modelling and control of models of dynamical physical systems in the laboratory of control theory or on another experimental data.

Requirements:

Elaboration of both essays and presentation of achieved results.

Syllabus of lectures:

1. Introduction to fuzzy logic, advantages and disadvantages of fuzzy systems

2. Linguistic and Takagi-Sugeno fuzzy models

3. Fuzzy sets, operations, relations

4. Fuzzification and defuzzification.

5. Fuzzy rules, aggregation, inference mechanisms

6. Neural networks, architecture

7. Neural networks learning algorithms

8. Fuzzy neural networks in modelling

9. Knowledge-based and data-driven model building, cluster analysis

10. Fuzzy control, controllers' structure

11. Stability of fuzzy systems

12. Fuzzy neural networks in control

13. Implementation of fuzzy systems on PLCs

14. Examples of applications of fuzzy systems in modelling and control

Syllabus of tutorials:

1. Recapitulation of relevant mathematical apparatus

2. Fuzzy Logic Toolbox for Matlab

3. Neural Network Toolbox for Matlab

4. Essay I - fuzzy neural modelling

5. Study of literature relevant to essay I

6. Elaboration of essay I

7. Elaboration of essay I

8. Essay II - fuzzy neural control

9. Study of literature relevant to essay II

10. Elaboration of essay II

11. Elaboration of essay II

12. Elaboration of essay II

13. Presentation of results

14. Presentation of results

Study Objective:

Study materials:

1. Vysoký P.: Fuzzy Control, 1997. Scriptum CTU. (in Czech)

2. Driankov D., Hellendoorn H., Reinfrank M. M.: An Introduction to Fuzzy Control, 1993. Springer Verlag.

3. Jang J.S.R., Sun C.T., Mizutani E.: Neuro-fuzzy and Soft Computing, 1997. Prentice Hall.

4. Fuzzy Logic Toolbox for Matlab, User's Guide.

5. Neural Network Toolbox for Matlab, User's Guide.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

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• Economics and Management in Electrical Engineering- structured studies (elective specialized course)
• Electronics - Electronic Applications- structured studies (elective specialized course)
• Electronics - Electronics and Photonics- structured studies (elective specialized course)
• Cybernetics and Measurements - Artificial Intelligence- structured studies (elective specialized course)
• Cybernetics and Measurements - Measurement and Instrumentation Systems- structured studies (elective specialized course)
• Cybernetics and Measurements - Aeronautical Engineering and Control Systems- structured studies (elective specialized course)
• Heavy-current Engineering - Electric Drives- structured studies (elective specialized course)
• Heavy-current Engineering - Electrical Engineering Applications- structured studies (elective specialized course)
• Telecommunications and Radio-engineering - Opto-electric Systems- structured studies (elective specialized course)
• Telecommunications and Radio-engineering - Radio Communications, Navigation and Radar Systems- struc (elective specialized course)
• Telecommunications and Radio-engineering - Multimedia, Sound and Television Technology- structured s (elective specialized course)
• Telecommunications and Radio-engineering - Telecommunications- structured studies (elective specialized course)