Inteligent Control Systems

Course title: Inteligent Control Systems

Code: 3ФЕИТ01Л006

Number of credits (ECTS): 6

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

Prerequisite for enrollment of the subject: None

Course Goals (acquired competencies): Students completing this course will obtain a basic understanding of fuzzy logic systems and artificial neural networks, and will know how these techniques are applied to engineering problems, including control systems. Students will understand the advantages and disadvantages of these methods relative to other control methods. Students will be aware of current research trends and issues. Students will be able to design control systems using fuzzy logic and artificial neural networks.

Total available number of classes: 180

Course Syllabus: Introduction to intelligent techniques in control systems: fuzzy logic; neural networks; techniques based on evolution (genetic algorithms); hybrid fuzzy neural systems. Mathematical basis of fuzzy logic. Fuzzy logic and approximate reasoning. Fuzzy inference system. Fuzzification and defuzzification. Mathematical representation of fuzzy logic systems: Mamdani, Takagi-Sugeno and other types of fuzzy models. Fuzzy logic control. Derivative based optimization and their application in fuzzy-neural systems. Derivative free optimization (genetic algorithms) and their applications in fuzzy-neural systems. Adaptive neural networks. Supervised learning neural networks. Identification with fuzzy-neural systems. Fuzzy-neural control systems. Advanced applications of fuzzy-neural systems.

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