2008
DOI: 10.1007/978-1-4020-6668-9_13
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An Asymptotic Consistency Criterion for Optimizing Defuzzification in Fuzzy Control

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Cited by 1 publication
(2 citation statements)
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“…Also, in that case we are considering fuzzy real numbers, which means that all theory developed for the treatment of the fuzzy real line can be used. We have included in the bibliography a number of references dealing with the implementation of a structure on the fuzzy real line; especially the work of D. Dubois In [85] and [86] we have been working on two new criteria, only applicable on compact subsets X ⊆ R or subsets thereof, which nevertheless seem to be important. Suppose a controller is given by a rule base consisting of a finite number of fuzzy variables A = {α 1 , ..., α n } ⊆ F(X).…”
Section: Nominal Scale Invariance Criterion (Nsic)mentioning
confidence: 99%
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“…Also, in that case we are considering fuzzy real numbers, which means that all theory developed for the treatment of the fuzzy real line can be used. We have included in the bibliography a number of references dealing with the implementation of a structure on the fuzzy real line; especially the work of D. Dubois In [85] and [86] we have been working on two new criteria, only applicable on compact subsets X ⊆ R or subsets thereof, which nevertheless seem to be important. Suppose a controller is given by a rule base consisting of a finite number of fuzzy variables A = {α 1 , ..., α n } ⊆ F(X).…”
Section: Nominal Scale Invariance Criterion (Nsic)mentioning
confidence: 99%
“…As mentioned in [69], when we consider a single-input, single-output controller, we can control the shape of the surface to a certain extent by manipulating the membership functions. In [85] and [86], we studied the behavior of the identity mapping between two fuzzy antecedent rule bases, and whether or not it yields an identity mapping between the input before fuzzification and the output after defuzzification. We found that this was not the case.…”
Section: The Input-output Mappingmentioning
confidence: 99%