Multimode-oriented polynomial transformation-based defuzzification strategy and parameter learning procedure

Author

Jiang, Tao ; Li, Yao

Author_Institution

Sapient Corp., Jersey, NJ, USA

Volume

27

Issue

5

fYear

1997

fDate

9/1/1997 12:00:00 AM

Firstpage

877

Lastpage

883

Abstract

In an earlier paper (1996), we proposed a set of generalized defuzzification strategies which can be characterized as single-mode-oriented strategies. A single-mode-oriented defuzzification strategy, although useful in many research projects and real world applications, cannot be applied to a multimode situation where two or more distinct possibility peaks exist in its membership function distribution. In this paper, for multimode-oriented generalized defuzzification applications, a multimode-oriented polynomial transformation based defuzzification strategy (M-PTD) is introduced. The new M-PTD strategy, which uses the Kalman filter in parameter learning procedure, offers a constraint-free and self-renewal defuzzification solution

Keywords

Kalman filters; fuzzy control; learning (artificial intelligence); Kalman filter; multimode-oriented polynomial transformation-based defuzzification; parameter learning procedure; self-renewal defuzzification solution; Acceleration; Algorithm design and analysis; Cities and towns; Fuzzy control; Fuzzy logic; Fuzzy sets; Fuzzy systems; Lighting control; National electric code; Polynomials;

fLanguage

English

Journal_Title

Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on

Publisher

ieee

ISSN

1083-4419

Type

jour

DOI

10.1109/3477.623241

Filename

623241