Evaluation of Steady-State and Dynamic Soft Sensors for Industrial Crude Distillation Unit under Parametric Constraints

被引：3

作者：

Torgashov, Andrei ^{[1
,2
]}

Goncharov, Anton ^{[1
,2
,3
]}

Zhuravlev, Evgeny ^{[4
]}

机构：

[1] Inst Automat & Control Proc FEB RAS, 5 Radio St, Vladivostok, Russia

[2] Far Eastern Fed Univ, Bldg 12 E,Campus FEFU, Vladivostok, Russia

[3] JSC Honeywell, 7 Kievskaya St, Moscow, Russia

[4] JSC Gazprom Neftekhim Salavat, 30 Molodogvardeitsev St, Salavat, Russia

来源：

IFAC PAPERSONLINE | 2018年 / 51卷 / 18期

基金：

俄罗斯基础研究基金会;

关键词：

Soft sensing; identification; constrained parameters; optimization; distillation columns; OPTIMIZATION; MODELS;

D O I：

10.1016/j.ifacol.2018.09.364

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The parametric identification problem for industrial crude distillation unit (CDU) is considered. We take the a priori knowledge of the process into account by using a system of constraints for parameters of soft sensors models. The identification problem is transformed into a constrained optimization problem, which we solved using the active set method. The static and dynamic soft sensors are evaluated for industrial CDU located at JSC "Gazprom neftekhim Salavat" refinery. It was found that the model performed better when we used the proposed constrained optimization approach for identification instead of robust regression methods. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：566 / 571

页数：6

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