Students will be able to design and implement intelligent control algorithms based on the fuzzy sets theory.

1. explain notion of fuzzy sets
2. explain functioning principles of fuzzy controller
3. explain methods for fuzzy controller preset
4. explain notion of fuzzy controller stability
5. compute fuzzy controller parameters
6. apply fuzzy controller and self-learning fuzzy controller

problem solving exercises are part of lectures, with active participation of students

Design and simulation of fuzzy controller (Matlab); design of fuzzy controller on PLC; design of fuzzy controller on PIC and PC

1. Basics of the fuzzy sets; Fuzzy operators and fuzzy norms
2. Linquistic variables; Fuzzy propositions and fuzzy relations; Fuzzy rules; Fuzzy implication; Fuzzy inference engines
3. Fuzzy controller structure; Fuzzy rule table; Distribution of the fuzzy membership functions; Fuzzyfication and defuzzyfication
4. Initial setting of the fuzzy controller - emulation of the standard control algorithms
5. Design, simulation and practical implementation of the basic fuzzy controller
6. Lyapunov stability of fuzzy control systems
7. Fuzzy controller design based on phase plane isoclines
8. midterm exam
9. Fuzzy numbers; fuzzy controller design based on fuzzy numbers
10. Design, simulation and practical implementation of fuzzy controller based on fuzzy numbers
11. Basic principles of adaptive control systems
12. Reference model based fuzzy adaptive control
13. Basics of the control system sensitivity theory; self-learning fuzzy controller based on sensitivity functions
14. Design and implementation of self-learning fuzzy controller
15. final exam