Algorithm for Fuzzy Relation Identification

Author

Bara, A.

Author_Institution

Dept. of Control Syst. & Appl. Informatics, Oradea Univ.

Volume

1

fYear

2006

fDate

25-28 May 2006

Firstpage

96

Lastpage

101

Abstract

Fuzzy model identification of a system can be performed either by subjective or objective methods. Subjective methods assume the describing of system operation in statements of type If...Then... and their summarization in a fuzzy relation. The objective methods are performed in an experimental approach. The second class is a common one and assumes fuzzy model identification without an expert. This presumes an estimation algorithm for the fuzzy relation of a system based on an input-output data set. The paper presents an approach for identification of fuzzy relation based on square prediction error minimization and the results achieved through simulation on the Box-Jenkins data set

Keywords

fuzzy set theory; identification; minimisation; Box-Jenkins data set; estimation algorithm; fuzzy model identification; fuzzy relation identification; objective method; square prediction error minimization; subjective method; Control systems; Equations; Fuzzy control; Fuzzy sets; Fuzzy systems; Humans; Informatics; Mathematical model; Predictive models; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation, Quality and Testing, Robotics, 2006 IEEE International Conference on

Conference_Location

Cluj-Napoca

Print_ISBN

1-4244-0360-X

Electronic_ISBN

1-4244-0361-8

Type

conf

DOI

10.1109/AQTR.2006.254505

Filename

4022827