Abstract-In fuzzy rule-based models acquired from numerical data, redundancy may be present in the form of similar fuzzy sets that represent compatible concepts. This results in an unnecessarily complex and less transparent linguistic description of the system. By using a measure of similarity, a rule base simplification method is proposed that reduces the number of fuzzy sets in the model. Similar fuzzy sets are merged to create a common fuzzy set to replace them in the rule base. If the redundancy in the model is high, merging similar fuzzy sets might result in equal rules that also can be merged, thereby reducing the number of rules as well. The simplified rule base is computationally more efficient and linguistically more tractable. The approach has been successfully applied to fuzzy models of real world systems.

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A new method of designing a controller, based on a vague kind of information and using fuzzy set theory, shows promising results in a case study.Seminary--In many cases a human operator is far more successful in controlling a complex industrial process than a controller designed by modern control techniques. The method of expressing the strategy of a human operator using fuzzy set theory has already been proposed elsewhere. In this study this method is applied to the control of a warm water plant. Fuzzy algorithms based on linguistic rules describing the operator's control strategy are applied to control this plant. Several types of such algorithms are implemented and compared.

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elIn fuzzy rule based models, redundancy may be present in the form of similarfuzzy sets, especially i f the models are acquired from data by using techniques like fuzzy clustering or gradient learning. The result is an unnecessarily complex and a less effective linguistic description of the system. An automated method is proposed that reduces the number of fuzzy sets in the model using a similarity measure. A comprehensive linguistic description is obtained by linguistic approximation. A numerical example demonstrates the approach.