fuzzy system

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crisp function interval function fuzzy function Folie 8
• • • • Fuzzy Systems Most common are fuzzy systems defined by means of if-then rules: rule-based fuzzy systems. In the rest of this lecture we will focus on these systems only. Fuzzy systems can serve different purposes, such as – modeling, – data analysis, – prediction or – control. Here, a fuzzy rule-based system is for simplicity called a fuzzy model, model regardless of its eventual purpose. Folie 9
Page 1 and 2: Fakultät ETIT Institut für Automa
Page 3 and 4: 1. • • In the description of th
Page 5 and 6: 3. • • The input, output and st
Page 7: Fuzzy Systems • • • Fuzzy sys
Page 11 and 12: • • • In fuzzy systems, the r
Page 13 and 14: • Mamdani (Linguistic) fuzzy mode
Page 15 and 16: • • • Fuzzy logic operators,
Page 17 and 18: Example Max-min composition X, Y, Z
Page 19 and 20: • • Takagi-Sugeno fuzzy model:
Page 21 and 22: 60 50 40 30 20 10 0 1.2 1 0.8 0.6 0
Page 23 and 24: Example R1: If X is small then Y =
Page 25 and 26: What defines the size of the rule-b
Page 27 and 28: • • • A set of rules in the c
Page 29 and 30: • • • • The antecedent form
Page 31 and 32: Fuzzification • • • The first
Page 33 and 34: Defuzzification • • • The res
Page 35 and 36: Types of defuzzifiers: 2. The Cente
Page 37 and 38: Types of defuzzifiers: There are se
Page 39 and 40: Fuzzy System (Overview) A fuzzy sys
Page 41 and 42: Folie 41

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