• Understanding of fuzzy approach to modeling, identification and control of process and systems. • Introduction to analysis and synthesis various fuzzy control algorithms. • Analysis, design, simulation and experimental realization of fuzzy control systems using Matlab/Simulink software.

Knowledge and understanding of: • Fuzzy identification of systems. • Analysis and design of ndirect and direct adaptive fuzzy controllers. • Analysis and design of fuzzy sliding mode controllers. • Analysis and design of fuzzy supervisory controllers. • Stability of fuzzy systems. • Simulation and practical realization of fuzzy control systems using PC and programing software Matlab/Simulink with various automatic control plants.

Relation to identification, estimation, and prediction. Batch least squares and recursive least squares methods. Gradient methods. Clustering methods. Fuzzy control as sliding control: analysis and design. Design of the direct and indirect adaptive fuzzy controller. Stability and convergence analysis. Fuzzy supervisory control. Fuzzy gain scheduling. Stability of fuzzy systems: direct and indirect Lyapunov’s method.

PA: Fuzzy identification. Analysis and synthesis of various fuzzy control algorithms based on sliding mode control, tracking control, adaptive control and supervisory control. PL: Matlab, Simulink, Fuzzy and Identification toolbox. Design and simulation conventional and nonconventional fuzzy control algorithms using Matlab. Practice and experiments: realization of fuzzy control systems of various automatic control plants using PC and programming software Matlab/Simulink.

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: 65

New material: 35
Elaboration and examples (recapitulation): 15

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

Review and grading of calculation tasks: 0
Review and grading of lab reports: 0
Review and grading of seminar papers: 15
Review and grading of the project: 0
Test: 0
Test: 0
Final exam: 0

Activity during lectures: 0
Test/test: 0
Laboratory practice: 10
Calculation tasks: 0
Seminar paper: 40
Project: 0
Final exam: 50
Requirement for taking the exam (required number of points): 0

K. M. Passino, S. Yurkovich, "Fuzzy Control", Addison-Wesley, 1998.; D. Driankov, H. Hellendoorn and M. Reinfrank, "An Introduction to Fuzzy Control" , Springer Verlag, 1996.