DocumentCode :
1603214
Title :
Polymer properties on-line estimation for an industrial polyethylene process based on suboptimal strong tracking filter
Author :
Zhao, Zhong ; Ning, Yu ; Gao, Yukun
Author_Institution :
Res. Inst. of Autom., Beijing Univ. of Chem. Technol., Beijing, China
fYear :
2009
Firstpage :
841
Lastpage :
846
Abstract :
A major difficulty affecting the control of product quality in industrial polymerization reactors is the lack of suitable on-line polymer property measurements. In this article, a predictive model of polymer properties is deduced for industrial polyethylene process based on the kinetics of ethylene polymerization. According to the approximation error upper bound of the deduced predictive model, a method of design the suboptimal strong tracking filter is proposed to update the estimation of polymer properties based on the off-line lab analysis data. The application result of the proposed method to the industrial UNIPOL licensed linear low-density polyethylene process has verified its feasibility and effectiveness. With the proposed method, polymer properties of industrial polyethylene process can be on-line estimated and make it possible for achieving the advanced on-line product quality control.
Keywords :
approximation theory; chemical reactors; plastic products; polymer melts; polymerisation; quality control; tracking filters; approximation error upper bound model; ethylene polymerization kinetics; industrial UNIPOL license; industrial polyethylene process; industrial polymerization reactors; melt index; off-line lab analysis data; polymer property; product quality control; suboptimal strong tracking filter; Approximation error; Filters; Inductors; Industrial control; Kinetic theory; Plastics industry; Polyethylene; Polymers; Predictive models; Upper bound;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Asian Control Conference, 2009. ASCC 2009. 7th
Conference_Location :
Hong Kong
Print_ISBN :
978-89-956056-2-2
Electronic_ISBN :
978-89-956056-9-1
Type :
conf
Filename :
5276267
Link To Document :
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