Practical inferential estimation using artificial neural networks

被引：3
|
作者：
Tham, MT [1 ]
Montague, GA [1 ]
Glassey, J [1 ]
Willis, MJ [1 ]
机构：
[1] Univ Newcastle, Dept Chem & Proc Engn, Newcastle, NSW 2308, Australia
来源：
MEASUREMENT & CONTROL | 2002年 / 35卷 / 01期
关键词：
Computer control systems - Feedforward neural networks - Inference engines - Linear control systems - Nonlinear control systems - Process control - Process engineering - Quality control - SCADA systems;
D O I：
10.1177/002029400203500102
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
When on-line measurement devices are not available to perform the required task, an alternative approach is to estimate the variable using available on-line measurements and a model that relates these measurements to the quality parameter. Such a model is commonly called a "software sensor". In this paper, the concepts of software sensors and the issues that arise are highlighted using a bioprocess as a case study.
引用
收藏
页码：5 / 9
页数：5
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