求解非线性化工过程鲁棒数据校正的新方法

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求解非线性化工过程鲁棒数据校正的新方法

周凌柯^a,b; 苏宏业^b; 褚健^b

^a Department of Automation, Nanjing University of Science & Technology, Nanjing 210094, China
^b Institute of Advanced Process Control, Zhejiang University, Hangzhou 310027, China

收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2006-06-28 发布日期:2006-06-28
通讯作者: 周凌柯

A New Method to Solve Robust Data Reconciliation in Nonlinear Process

ZHOULingke^a,b; SUHongye^b; CHUJian^b

^aDepartment of Automation, Nanjing University of Science & Technology, Nanjing 210094, China
^b Institute of Advanced Process Control, Zhejiang University, Hangzhou 310027, China

Received:1900-01-01 Revised:1900-01-01 Online:2006-06-28 Published:2006-06-28
Contact: ZHOU Lingke

摘要/Abstract

摘要： Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. Robust estimators can significantly reduce the effect of gross errors and yield less-biased results. In this article, a new method is proposed to solve the robust data reconciliation problem of nonlinear chemical process. By using several technologies including linearization method, penalty function, virtual observation equation, and equivalent weights method, the robust data reconciliation problem can be transformed into least squares estimator problem which leads to the convenience in computation. Simulation results in a nonlinear chemical process demonstrate the efficiency of the proposed method.

关键词: data reconciliation;robust estimator;equivalent weights method

Abstract: Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. Robust estimators can significantly reduce the effect of gross errors and yield less-biased results. In this article, a new method is proposed to solve the robust data reconciliation problem of nonlinear chemical process. By using several technologies including linearization method, penalty function, virtual observation equation, and equivalent weights method, the robust data reconciliation problem can be transformed into least squares estimator problem which leads to the convenience in computation. Simulation results in a nonlinear chemical process demonstrate the efficiency of the proposed method.

Key words: data reconciliation, robust estimator, equivalent weights method

周凌柯, 苏宏业, 褚健. 求解非线性化工过程鲁棒数据校正的新方法[J]. CIESC Journal.

ZHOULingke, SUHongye, CHUJian. A New Method to Solve Robust Data Reconciliation in Nonlinear Process
[J]. .

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求解非线性化工过程鲁棒数据校正的新方法

A New Method to Solve Robust Data Reconciliation in Nonlinear Process

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