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How to control if even experts are not sure : Robust fuzzy control

Author
Kreinovich, Vladik YA.
Published
JAN 1, 1992.
Physical Description
1 electronic document
Additional Creators
Tolbert, Dana, Nguyen, Hung T., and Lea, Robert
Online Version

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Unclassified, Unlimited, Publicly available.
Free-to-read Unrestricted online access
Summary
In real life, the degrees of certainty that correspond to one of the same expert can differ drastically, and fuzzy control algorithms translate these different degrees of uncertainty into different control strategies. In such situations, it is reasonable to choose a fuzzy control methodology that is the least vulnerable to this kind of uncertainty. It is shown that this 'robustness' demand leads to min and max for &- and V-operations, to 1-x for negation, and to centroid as a defuzzification procedure.
Other Subject(s)
Collection
NASA Technical Reports Server (NTRS) Collection.
Note
Document ID: 19930015953.
Accession ID: 93N25142.
NASA-TM-108745.
NAS 1.15:108745.
Terms of Use and Reproduction
No Copyright.
View MARC record | catkey: 15670674