DocumentCode :
2847284
Title :
Soft sensing of sodium aluminate solution component concentrations via on-line clustering and fuzzy modeling
Author :
Wei Wang ; Tianyou Chai ; Lijie Zhao ; Qin, S.J.
Author_Institution :
State Key Lab. of Integrated Autom. for Process Ind., Northeastern Univ., Shenyang, China
fYear :
2011
fDate :
June 29 2011-July 1 2011
Firstpage :
2468
Lastpage :
2473
Abstract :
The component concentrations measurement of sodium aluminate solution are critical to the process of alumina production, they affect the product quality. However, they can not be measured online at present, thus the control and optimal operation is hardly to be achieved. This paper presents an on-line fuzzy modeling method to predict the component concentrations. It includes an on-line clustering approach which can be applied in a general class of fuzzy TKS models. Stable learning algorithms for the premise and the consequence parts of fuzzy rules are also given. A measuring device is developed to achieve the proposed method and industry experiments are conducted in the alumina production process, the predicted results show the effectiveness of the proposed method.
Keywords :
alumina; aluminium manufacture; fuzzy set theory; learning (artificial intelligence); pattern clustering; production engineering computing; sodium compounds; alumina production; component concentrations measurement; fuzzy TKS model; fuzzy rule; on-line clustering; on-line fuzzy modeling; product quality; sodium aluminate solution; soft sensing; stable learning algorithm; Conductivity; Laboratories; Predictive models; Production; Temperature measurement; Temperature sensors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2011
Conference_Location :
San Francisco, CA
ISSN :
0743-1619
Print_ISBN :
978-1-4577-0080-4
Type :
conf
DOI :
10.1109/ACC.2011.5990818
Filename :
5990818
Link To Document :
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