Shaping of molecular weight distribution using B-spline based predictive probability density function control

被引：0

作者：

Yue, H ^{[1
]}

Zhang, JF ^{[1
]}

Wang, H ^{[1
]}

Cao, LL ^{[1
]}

机构：

[1] Univ Manchester, Inst Sci & Technol, Control Syst Ctr, Manchester M60 1QD, Lancs, England

来源：

PROCEEDINGS OF THE 2004 AMERICAN CONTROL CONFERENCE, VOLS 1-6 | 2004年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Issues of modelling and control of molecular weight distributions (MWDs) of polymerization products have been studied under the recently developed framework of stochastic distribution control, where the purpose is to design the required control inputs that can effectively shape the output probability density functions (PDFs) of the dynamic stochastic systems. The B-spline Neural Network has been implemented to approximate the function of MWDs provided by the mechanism model, based on which a new predictive PDF control strategy has been developed. A simulation study of MWD control of a pilot-plant styrene polymerization process has been given to demonstrate the effectiveness of the algorithms.

引用

页码：3587 / 3592

页数：6

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