SVD-based complexity reduction to TS fuzzy models
Baranyi, P.; Yeung Yam; Varkonyi-Koczy, A.R.; Patton, R.J.; Michelberger, P.; Sugiyama, M.
Industrial Electronics, IEEE Transactions on
Volume 49, Issue 2, Apr 2002 Page(s):433 - 443
Digital Object Identifier 10.1109/41.993277
Summary: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
View citation and abstract |
Cart
