A Saturation Based Interpolation Method for Fuzzy Systems
نویسندگان
چکیده
This paper presents an alternative inference-defuzzification algorithm for Takagi-Sugeno fuzzy systems that preserves local-model interpretation and convexity properties. The linear model in the rule consequent is saturated outside the core set of the antecedent membership functions. This allows the interpretation of the consequents of fuzzy rules as a local linearization of the model restricted to the subset where it is valid. The setting has readability advantages over TakagiSugeno frameworks, and it is simpler that other interpolation proposals. Some examples illustrate the approach. Copyright 2005 IFAC
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تاریخ انتشار 2005