• Automatic Control, Semester 3, position 1

• Understanding of fuzzy approach to modeling phenomenon, process and systems. • Introduction to basic of fuzzy set theory and fuzzy control theory. • Introduce students to the fundamental principles of artificial neural networks. • Analysis, design, simulation and practical realization of fuzzy control systems using Matlab/Simulink programming software.

On successful completion of the course the students should be able to: • Understand fuzzy set, fuzzy logic and fuzzy control theory. • Design of fuzzy controllers and fuzzy systems. • Realize of various fuzzy control algorithms. • Perform simulation and practically implement various fuzzy control systems using PC and programing software Matlab/Simulink.

Fuzzy set theory. Fuzzy relations, operations on fuzzy sets. Fuzzy logic: linguistic variables, fuzzy rules, approximate reasoning. Fuzzy systems: fuzzy rule base, fuzzy inference engine, fuzzifier, defuzzifier, mathematical representations of fuzzy systems. Fuzzy control: theoretical and practical approach. Design and analysis of fuzzy controllers, fuzzy PID controllers. Mamdani and Takagi-Sugeno fuzzy systems. Fuzzy systems as universal approximators. Fuzzy tuning of classical conventional controllers. Nonconventional fuzzy control algorithms. Application of fuzzy control.

PA: Practical work includes computational exercises that follow the content of course. PL: Practice and experiments: simulation and experimental application of fuzzy algorithms as well as their practical realization using Matlab/Simulink for control different plants within a modular educational real-time control system (inverted pendulum, , heat flow experiment, DC servo motor).

Defined by curriculum of the study programme.

• Modular educational real time control system with various control plants (DC servo motor, inverted pendulum, double inverted pendulum, heat flow experiment, coupled water tanks experiment), with acquisition hardware and software. • PC and PC Embedded controllers, Siemens Simatic PLC, National Instruments controllers, • Installation for control system testing and acquisition of electrical variables, • Intelligent Control Systems Laboratory, Control Systems Laboratory.

Total assigned hours: 75

New material: 20
Elaboration and examples (recapitulation): 10

Auditory exercises: 5
Laboratory exercises: 20
Calculation tasks: 0
Seminar paper: 0
Project: 5
Consultations: 0
Discussion/workshop: 0
Research study work: 0

Review and grading of calculation tasks: 0
Review and grading of lab reports: 2
Review and grading of seminar papers: 0
Review and grading of the project: 4
Test: 4
Test: 0
Final exam: 5

Activity during lectures: 5
Test/test: 50
Laboratory practice: 5
Calculation tasks: 0
Seminar paper: 0
Project: 0
Final exam: 40
Requirement for taking the exam (required number of points): 30

D. Driankov, H. Hellendoorn and M. Reinfrank, "An Introduction to Fuzzy Control" , Springer Verlag, 1996.; K. M. Passino, S. Yurkovich, "Fuzzy Control", Addison-Wesley, 1998; Radiša Jovanović, Fuzzy logic, modelling and control, Faculty of Mechanical Engineering, Belgrade, ISBN 978-86-6060-059-4, 2020 (in Serbian). ; Radiša Jovanović, Mаtlab and Simulink in Automatic Control, Faculty of Mechanical Engineering, Belgrade, ISBN 978-86-7083-896-3, 2021 (in Serbian).