2023
DOI: 10.3390/app13031934
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Dynamic Analysis of Fuzzy Systems

Abstract: In this work, a new methodology for the dynamic analysis of non-linear systems is developed by applying the Mamdani fuzzy model. With this model, parameters such as settling time, peak time and overshoot will be obtained. The dynamic analysis of non-linear fuzzy systems with triangular membership functions is performed, and linguistic variables describing overly complex or ill-defined phenomena are used to fit the model. Scaling factors will simplify the modification of the variables, making them easier to fin… Show more

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“…A graphical representation of the membership functions associated with the output s_OFFSET_M is available in Figure 5. The method chosen for defuzzification in the case of the Mamdani FIS uses the center of gravity technique (i.e., centroid); this method is applied in many other works [20,27,28,41,42]. According to this defuzzification technique, a crisp output Z calculated for continuous values uses the curve of the scaled output membership function µ(x), as expressed in Equation ( 5) [29,43].…”
Section: Mamdanimentioning
confidence: 99%
“…A graphical representation of the membership functions associated with the output s_OFFSET_M is available in Figure 5. The method chosen for defuzzification in the case of the Mamdani FIS uses the center of gravity technique (i.e., centroid); this method is applied in many other works [20,27,28,41,42]. According to this defuzzification technique, a crisp output Z calculated for continuous values uses the curve of the scaled output membership function µ(x), as expressed in Equation ( 5) [29,43].…”
Section: Mamdanimentioning
confidence: 99%