Fundamentals of Intelligent Control Systems

Course Description

Basic properties of the Intelligent control systems. Basics of the fuzzy sets theory. Fuzzy sets in the control. Standard fuzzy controller. Hybrid fuzzy controller. Fuzzy numbers. Lyapunov stability in fuzzy systems. Fuzzy phase plane. Adaptive and selflearning fuzzy controllers. Industrial applications of the intelligent control systems. Student work on the practical design and implementation of the intelligent control algorithms.

General Competencies

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

Learning Outcomes

  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

Forms of Teaching


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

Laboratory Work

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

Grading Method

Continuous Assessment Exam
Type Threshold Percent of Grade Threshold Percent of Grade
Laboratory Exercises 0 % 12 % 0 % 12 %
Homeworks 0 % 21 % 0 % 21 %
Mid Term Exam: Written 0 % 30 % 0 %
Final Exam: Written 0 % 27 %
Final Exam: Oral 10 %
Exam: Written 50 % 47 %
Exam: Oral 20 %

Week by Week Schedule

  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

Study Programmes

University undergraduate
Control Engineering and Automation (module)
Elective Courses (6. semester)


Zdenko Kovačić, Stjepan Bogdan (2005.), Fuzzy controller design: theory and applications, CRC Press
D. Driankov, H. Hellendoorn, M. Reinfrank (1993.), An Introduction to Fuzzy Control, Springer-Verlag

Laboratory exercises

Grading System

ID 34341
  Summer semester
L0 English Level
L1 e-Learning
30 Lecturers
0 Exercises
15 Laboratory exercises


90 Excellent
75 Very Good
60 Good
50 Acceptable