A systematic method for optimum sensor selection in inferential control systems

被引：22

作者：

Kookos, IK ^{[1
]}

Perkins, JD ^{[1
]}

机构：

[1] Univ London Imperial Coll Sci Technol & Med, Dept Chem Engn, Ctr Proc Syst Engn, London SW7 2BY, England

来源：

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH | 1999年 / 38卷 / 11期

关键词：

D O I：

10.1021/ie9902737

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

This paper considers the optimal selection of sensor locations in square inferential control systems, where the number of measurements employed is equal to the number of actuators. A mixed-integer linear programming (MILP) problem formulation is proposed based on the assumption that the control objectives can be related to the variability of certain process variables. The method is applied to three case studies including a methanol-water column, a deisobutanizer column, and a benzene, toluene, o-xylene column. The selection of tray temperatures for inferential composition control is the problem considered in these case studies. To investigate the validity of the proposed method, closed-loop simulations are carried out. The method is shown to provide a satisfactory answer to the optimum sensor selection problem.

引用

页码：4299 / 4308

页数：10

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