Abstract
This paper proposes an eclectic approach for the efficient computation of fuzzy rules based on fuzzy logic and signal processing techniques. The rules {R r} of the MISO zero-order Takagi-Sugeno fuzzy system considered, are given in the form of R r: If X I is A rl and ... and X N is A rN then z is c r, where Xj are fuzzified input variables, A rj are standard fuzzy sets which belong to the corresponding partition of unity {A rj} and c r is a nonfuzzy singleton term of output variable z. A relevant feature of this approach is a quantitative, signal processing based, transformation of uncertainty (imprecision) of each input X j into an additional uncertainty (vagueness) on the corresponding fuzzy partition {A rj}. This transformation greatly simplifies the involved matching computation. Moreover, this fuzzification transformation gives a new set of linguistic terms {A rj’} which is also a partition the unity.
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Fernández, F., Gutiérrez, J. (1999). Transformation and Optimization of Fuzzy Controllers Using Signal Processing Techniques. In: Reusch, B. (eds) Computational Intelligence. Fuzzy Days 1999. Lecture Notes in Computer Science, vol 1625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48774-3_10
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DOI: https://doi.org/10.1007/3-540-48774-3_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66050-7
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