Fuzzy Modelling and Control

B232 - Summer 23/24
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B171 - Winter 17/18 B191 - Winter 19/20

Fuzzy Modelling and Control - XP35FMD

Student survey results
Credits 4
Semesters Summer
Completion Exam
Language of teaching undefined
Extent of teaching 2P+2C
Annotation
The goal of the subject is to introduce the up-to-date trends and results in the area of modelling and control of nonlinear systems based on fuzzy logic and neural networks. This includes especially analysis and synthesis of Takagi-Sugeno fuzzy systems, utilization of fuzzy systems and neural networks in control of nonlinear systems by approximation of unknown functions appearing in the description of the system, and design of adaptive fuzzy systems both direct and indirect.
Study targets
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Course outlines
Introduction of fuzzy logic, history of utilization of fuzzy logic in modeling and control of nonlinear systems
Terminology and principles of fuzzy logic - fuzzy set, fuzzy operations and relation, linguistic variable, approximate reasoning, fuzzy rule base, inference mechanisms
Neural networks - types and properties, learning algorithms
Fuzzy modeling - design of fuzzy systems using gradient methods, least squares algorithms, fuzzy clustering (recursive and non-recursive algorithms fuzzy c-means, Gustafson-Kessel a Gath-Geva)
Analysis and synthesis of Takagi-Sugeno fuzzy systems using different Lyapunov function candidates
Control of nonlinear fuzzy systems using fuzzy logic and neural networks - sliding mode control, backstepping
Design of direct and indirect adaptive fuzzy controllers
Exercises outlines
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Literature
Li-Xin Wang: A Course in Fuzzy Systems and Control, Prentice Hall, 1997
Vybrané články z časopisů IEEE Transactions on Fuzzy Control, IEEE Transactions on Systems, Man and Cybernetics, Fuzzy Sets and Systems
Requirements
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