文章基本信息

标题：Robust soft sensor development using multi-rate measurements * * This work was supported by Natural Sciences and Engineering Research Council (NSERC) of Canada.
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作者：Ouyang Wu ; Hariprasad Kodamana ; Nabil Magbool Jan 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：10190-10195
DOI：10.1016/j.ifacol.2017.08.1768
语种：English
出版社：Elsevier
摘要：AbstractTwo different types of measurements are often available for the key quality variables in process industries - (a) an accurate “slow-rate” laboratory measurements, and (b) a less accurate “fast-rate” online analyser measurements. Also, the analyser measurements are prone to fail due to hardware issues. Therefore, the main objective of this work is to present a novel approach for developing an accurate, fast-rate, inferential model of quality variables which is robust to outliers. For this purpose, we present a maximum likelihood based approach to integrate the multi-rate output data in the model building task, using Expectation Maximization algorithm. The efficacy of the proposed approach is demonstrated using a simulation example.
关键词：Keywordssoft sensorstatic modelmulti-rateExpectation Maximization algorithmt—distributionflat-toppedt—distribution