Reducing the high dimensionality problem in fuzzy dynamic models

Author

Vachkov, Gancho ; Hirota, Kaoru

Author_Institution

Dept. of Autom. of Ind., Univ. of Chem. Technol. & Metall., Sofia, Bulgaria

Volume

3

fYear

1996

fDate

8-11 Sep 1996

Firstpage

1807

Abstract

An incremental type of fuzzy dynamic model suitable for one-step-ahead prediction of non-linear dynamic processes is presented and analysed. It is realized by a two-dimensional fuzzy inference procedure with inputs being the change-of-input and change-of-output of the process. Another second-level fuzzy tuning block is used to recursively update the scaling factors (borders of the membership functions) of the first inference procedure. Thus the proposed method is able to predict high-order non-linear or time varying processes by means of only 2 two-dimensional fuzzy inference procedures

Keywords

fuzzy logic; fuzzy set theory; inference mechanisms; nonlinear dynamical systems; predictive control; time-varying systems; change-of-input; change-of-output; fuzzy dynamic models; high dimensionality problem; nonlinear dynamic processes; one-step-ahead prediction; scaling factors; second-level fuzzy tuning block; time varying processes; two-dimensional fuzzy inference procedure; Automation; Chemical analysis; Chemical industry; Chemical technology; Electronic mail; Fuzzy sets; Fuzzy systems; Industrial plants; Metals industry; Predictive models;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on

Conference_Location

New Orleans, LA

Print_ISBN

0-7803-3645-3

Type

conf

DOI

10.1109/FUZZY.1996.552645

Filename

552645