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“The role of fuzzy logic in modeling, identification and control”

Authors: Lotfi A. Zadeh,
Affiliation: University of California at Berkeley
Reference: 1994, Vol 15, No 3, pp. 191-203.

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Keywords: Fuzzy logic, fuzzy contol, fuzzy modeling

Abstract: In the nearly four decades which have passed since the launching of the Sputnik, great progress has been achieved in our understanding of how to model, identify and control complex systems. However, to be able to design systems having high MIQ (Machine Intelligence Quotient), a profound change in the orientation of control theory may be required. More specifically, what may be needed is the employment of soft computing - rather than hard computing - in systems analysis and design. Soft computing - unlike hard computing - is tolerant of imprecision, uncertainty and partial truth.

PDF PDF (1796 Kb)        DOI: 10.4173/mic.1994.3.9

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  title={{The role of fuzzy logic in modeling, identification and control}},
  author={Zadeh, Lotfi A.},
  journal={Modeling, Identification and Control},
  publisher={Norwegian Society of Automatic Control}


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