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Authors

Berezin M. A.

Degree
Senior Mathematician, Intelligent Systems Modeling and Control Laboratory, Institute of Control Sciences n. a. V. A. Trapeznikov of Russian Academy of Sciences
Location
Moscow
Articles

Fuzzy systems parameters identification using stable recurrent algorithm

Takagi-Sugeno fuzzy models have recently become a quite powerful engineering tool for complex systems modeling and control. However many tasks including the neurofuzzy identification and control stability problem are so far unsolved. The paper suggests the recurrent relaxation algorithm for identification of parameter consequents of Takagi-Sugeno fuzzy rules. Using «input-to-state» approach the stability of this algorithm is proving.

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