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SVD-based Complexity Reduction to TS Fuzzy Models

TitleSVD-based Complexity Reduction to TS Fuzzy Models
Publication TypeJournal Article
Year of Publication2002
AuthorsBaranyi, P., Y. Y, A. Várkonyi-Kóczy, R. J. Patton, M. P, and S. M
JournalIEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume49
Issue2
Pagination433 - 443
Date Published2002
Publication Languageeng
Abstract

One of the typical important criteria to be considered in real-time control applications Is the computational complexity of the controllers, observers, and models applied. In this paper, a singular value decomposition (SVD)-based complexity reduction technique Is proposed for Takagi Sugeno (TS) fuzzy models. The main motivation is that the TS fuzzy model has exponentially growing computational complexity with the improvement of its approximation property through, as usually practiced, increasing the density of antecedent terms. The reduction technique proposed here Is capable of defining the contribution of each local linear model included in the TS fuzzy model, which serves to remove the weakly contributing ones as according to a given threshold. Reducing the number of models leads directly to the computational complexity reduction. This work also includes a number of numerical and application examples.
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