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dc.contributor.authorZhu, J.
dc.contributor.authorGui, W.
dc.contributor.authorLiu, J.
dc.contributor.authorXu, Honglei
dc.contributor.authorYang, C.
dc.date.accessioned2017-01-30T13:44:54Z
dc.date.available2017-01-30T13:44:54Z
dc.date.created2016-02-21T19:30:26Z
dc.date.issued2016
dc.identifier.citationZhu, J. and Gui, W. and Liu, J. and Xu, H. and Yang, C. 2016. Combined fuzzy based feedforward and bubble size distribution based feedback control for reagent dosage in copper roughing process. Journal of Process Control. 39: pp. 50-63.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/34652
dc.identifier.doi10.1016/j.jprocont.2015.12.003
dc.description.abstract

All rights reserved. A combined fuzzy based feedforward (FBF) and bubble size distribution (BSD) based feedback reagent dosage control strategy is proposed to implement the product indices in copper roughing process. A fuzzy theory based feedforward compensator will be used to calculated the reagent dosage in advance to eliminate the influence of large disturbances according to ore grade and handling capacity. Since the bubble size is believed to be closely related to flotation performance and responds to changes in the reagent dosage, using BSD based feedback predictive control calculates the reagent dosage to stabilize the flotation running. Instead of simple statistic feature, the bubble size with non-Gaussian feature is characterized to be probability density function (PDF) by using B-spline. A multi-output least square support vector machine (MLS-SVM) based is then applied to establish a dynamical relationship between the weights of B-spline and the reagent dosage since the weights are interrelated and related to the reagent dosage. A multiple step based optimization algorithm is finally proposed to determine the reagent dosage. Experimental results can show the effectiveness of the proposed method.

dc.publisherElsevier Ltd
dc.titleCombined fuzzy based feedforward and bubble size distribution based feedback control for reagent dosage in copper roughing process
dc.typeJournal Article
dcterms.source.volume39
dcterms.source.startPage50
dcterms.source.endPage63
dcterms.source.issn0959-1524
dcterms.source.titleJournal of Process Control
curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusFulltext not available


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