SFNN model for control and prediction hot metal silicon content in BF

Author

Qihui, Li

Author_Institution

Math. Dept., Jiaxing Univ., Jiaxing

fYear

2008

fDate

1-3 Sept. 2008

Firstpage

1896

Lastpage

1898

Abstract

A new intelligent control and prediction model, based on SFNN, was developed to approach the change of hot metal silicon content in BF ironmaking system, where, noise influencing the system was thoroughly considered. Nonuniform function fuzzification, fuzzy rules, fuzzy inference and special defuzzification are included in the SFNN model, presented in this paper. The result of control and prediction to hot metal silicon content is very successful. Data, used in this paper, was collected online from No.1 BF at Laiwu Iron and Steel Group Co.

Keywords

blast furnaces; fuzzy control; fuzzy neural nets; fuzzy reasoning; iron; metals; neurocontrollers; silicon; stochastic processes; blast furnace ironmaking system; fuzzy inference; fuzzy rule; hot metal silicon content prediction; intelligent control; nonuniform function; stochastic fuzzy neural network; Blast furnaces; Fuzzy control; Fuzzy neural networks; Fuzzy sets; Input variables; Mathematical model; Predictive models; Silicon; Steel; Thermal variables control; SFNN Model; control; prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on

Conference_Location

Qingdao

Print_ISBN

978-1-4244-2502-0

Electronic_ISBN

978-1-4244-2503-7

Type

conf

DOI

10.1109/ICAL.2008.4636468

Filename

4636468