Online Data Reconciliation with Poor Redundancy Systems

被引：18

作者：

Manenti, Flavio ^{[1
]}

Grottoli, Maria Grazia ^{[1
]}

Pierucci, Sauro ^{[1
]}

机构：

[1] Politecn Milan, CMIC Dept Giulio Natta, I-20133 Milan, Italy

来源：

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH | 2011年 / 50卷 / 24期

关键词：

MODEL-PREDICTIVE CONTROL; NONLINEAR ALGEBRAIC MODELS; PARAMETER-ESTIMATION; PATH OPTIMIZATION; CHALLENGES; ENTERPRISE; OXIDATION;

D O I：

10.1021/ie202259b

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

The paper deals with the integrated solution of different model-based optimization levels to face the problem of inferring and reconciling online plant measurements practically, under the condition of poor measure redundancy, because of a lack of instrumentation installed in the field. The novelty of the proposed computer-aided process engineering (CAPE) solution is in the simultaneous integration of different optimization levels: (i) the data reconciliation based on a detailed process simulation; (ii) the introduction and estimation of certain adaptive parameters, to match the current process conditions as well as to confer a certain generality on it; and (iii) the use of a set of efficient optimizers to improve,plant operations. The online feasibility of the proposed CAPE solution is validated on a large-scale sulfur recovery unit (SRU) of an oil refinery.

引用

页码：14105 / 14114

页数：10

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