Title :
SFNN model for control and prediction hot metal silicon content in BF
Author_Institution :
Math. Dept., Jiaxing Univ., Jiaxing
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;
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
DOI :
10.1109/ICAL.2008.4636468
