Minimal fuzzy memberships and rules using hierarchical geneticalgorithms
Kit-Sang Tang; Kim-Fung Man; Zhi-Feng Liu; Sam Kwong
Industrial Electronics, IEEE Transactions on
Volume 45, Issue 1, Feb 1998 Page(s):162 - 169
Digital Object Identifier 10.1109/41.661317
Summary:A new scheme to obtain optimal fuzzy subsets and rules is
proposed. The method is derived from the use of genetic algorithms,
where the genes of the chromosome are classified into two different
types. These genes can be arranged in a hierarchical form, where one
type of gene controls the other. The effectiveness of this genetic
formulation enables the fuzzy subsets and rules to be optimally reduced
and, yet, the system performance is well maintained. In this paper, the
details of formulation of the genetic structure are given. The required
procedures for coding the fuzzy membership function and rules into the
chromosome are also described. To justify this approach to fuzzy logic
design, the proposed scheme is applied to control a constant water
pressure pumping system. The obtained results, as well as the associated
final fuzzy subsets, are included in this paper. Because of its
simplicity, the method could lead to a potentially low-cost fuzzy logic
implementation
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