Abstract
It has been demonstrated many times in practice that fuzzy logic controllers have an important role in rule-based expert systems. However, it is essential for a fuzzy logic controller to have an appropriate set of rules to perform at the desired level. The linguistic structure of the fuzzy logic controller allows a tentative linguistic policy to be used as an initial rule base. At the design stage, if one can assemble a reasonably good collection of rules, it may then be possible to tune these rules to improve the controller performance. In this paper, a genetic-algorithm-based method for tuning the rule base of a fuzzy logic controller is presented. The method is used in tuning two PD-like fuzzy logic controllers and the results are discussed.
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