Self-organizing neural fuzzy inference network for intelligent control

Author

Constantin, Nicolae ; Dumitrache, Ion ; Mihu, Ioana

Author_Institution

Dept. of Control & Syst. Eng., Univ. Politehnica of Bucharest, Romania

fYear

2000

fDate

2000

Firstpage

375

Lastpage

379

Abstract

A self-organizing neural fuzzy inference network (SONFIN) is proposed. This network is built for realizing the basic elements and functions of dynamic fuzzy inference, considered like a series of dynamic fuzzy rules. Each node and weight represent an element in a fuzzy rule. These are created online based an a concurrent structure and parameter identification. The structure learning together with the parameter learning forms the learning algorithms for a dynamic neural fuzzy network. The aligned clustering-based algorithm is used for reducing the number of generated fuzzy rules. Efficiency of the SONFIN is verified from simulation results

Keywords

fuzzy control; fuzzy neural nets; intelligent control; multilayer perceptrons; neurocontrollers; parameter estimation; self-organising feature maps; clustering-based algorithm; concurrent structure; dynamic fuzzy inference; dynamic fuzzy rules; dynamic neural fuzzy network; parameter identification; parameter learning; self-organizing neural fuzzy inference network; structure learning; Clustering algorithms; Control systems; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy reasoning; Fuzzy systems; Inference algorithms; Intelligent control; Neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control, 2000. Proceedings of the 2000 IEEE International Symposium on

Conference_Location

Rio Patras

ISSN

2158-9860

Print_ISBN

0-7803-6491-0

Type

conf

DOI

10.1109/ISIC.2000.882953

Filename

882953