A new data-based methodology for nonlinear process modeling

被引：294

作者：

Cheng, C ^{[1
]}

Chiu, MS ^{[1
]}

机构：

[1] Natl Univ Singapore, Dept Chem & Biomol Engn, Singapore 119260, Singapore

来源：

CHEMICAL ENGINEERING SCIENCE | 2004年 / 59卷 / 13期

关键词：

process modeling; just-in-time learning; distance measure; angle measure; stability;

D O I：

10.1016/j.ces.2004.04.020

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

A new data-based method for nonlinear process modeling is developed in this paper. In the proposed method, both distance measure and angle measure are used to evaluate the similarity between data, which is not exploited in the previous work. In addition, parametric stability constraints are incorporated into the proposed method to address the stability of local models. Furthermore, a new procedure of selecting the relevant data set is proposed. Literature examples are presented to illustrate the modeling capability of the proposed method. The adaptive capability of the proposed method is also evaluated. (C) 2004 Elsevier Ltd. All rights reserved.

引用

页码：2801 / 2810

页数：10

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