Course title: Fuzzy logic control

Code: FEIT01L013

Number of credits (ECTS): 6

Weekly number of classes: 2+2+1+0

Prerequisite for enrollment of the subject: None

Course goals/Competences: The basic goal of the course is gaining knowledge for one of the nonconventional systems control methods. After passing the course the student will be eligible to analyze and design of nonconventional fuzzy logic controllers for control of objects and processes.

Total available number of classes: 180

Curriculum: Why fuzzy logic? What are fuzzy logic systems? Where and how to use fuzzy logic systems? Mathematical preliminaries of fuzzy logic systems. Fuzzy logic and approximate reasoning (linguistic variables, linguistic values and rules). Fuzzy sets and fuzzy rule base. Fuzzification. Fuzzy inference engine. Defuzzification. Mathematical representation of fuzzy systems. Takagi-Sugeno (T-S) fuzzy systems. Fuzzy logic control of linear systems: stable controllers and optimal and robust controllers. Fuzzy logic control of nonlinear systems: parameterized fuzzy logic controller (P, PD, PI, PID). Multilevel control including fuzzy logic systems. Stable fuzzy control using nonfuzzy supervisor. Fuzzy logic control of systems with fuzzy models: T-S fuzzy logic systems. Dynamics of fuzzy model in feedback control loop. Stability analysis. Design of stable fuzzy logic controller. Basics of neural networks. Implementing neural networks in control systems.

Literature: