Fuzzy Control

The course is a substitute for:

Fuzzy Control (X35FZR)

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:

Backgrounds of modelling and control of dynamical systems (Laplace transform, system description, stability, frequency response, design of PID compensator)

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. Driankov D., Hellendoorn H., Reinfrank M. M.: An Introduction to Fuzzy

Control, 1993. Springer Verlag.

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

Prentice Hall.

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

4. 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: