CATEGORY: SYNGAS
Preprints of the 8th IFAC Symposium on Advanced
Control of Chemical Processes, The International Federation of Automatic
Control, Furama Riverfront, Singapore, July 10-13, 2012
Application of a new dataset selection procedure
for the prediction of the Syngas composition of a gasification plant
S. M. Zanoli*, G. Astolfi* and L. Barboni **
s.zanoli@univpm.it
g.astolfi@univpm.it
l.barboni@gruppoapi.com
*D.I.I., Università Politecnica delle Marche, Ancona, Italy
** affidabilità automazioni- I&C,api raffineria di Ancona, Italy
Abstract:
Describes a model identification of a
gasification process for the estimation of the Syngas composition, as well as a
proposed new procedure for the selection of the identification dataset.
Estimations are needed to integrate the gascromathographic measurements of the
Syngas composition. These are often not
available because of periodic calibrations. The work described here is part of
a broader project for the development of a supervisory controller for process
optimization and for fault detection and isolation scope.
Improvements in the identification process from
standard procedures were obtained by means of a suitable selection of the input
data set. The proposed input data selection procedure is based on the
application of the Fuzzy C-means (FCM) algorithm for the generation of the main
clusters. Results on a gasification process of a refinery plant show the
effectiveness of the proposed FCM method in filtering a large dataset and the
reliability of the model in the prediction of the Syngas composition.
Free Full Text Source: http://scholar.google.com/scholar?start=130&q=automation+refinery&hl=en&as_sdt=0,11&as_ylo=2012
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