文章基本信息

标题：Novel common and special feature extraction method for modeling multi-grade processes
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作者：Jingxiang Liu ; Tao Liu ; Junghui Chen 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2018
卷号：51
期号：18
页码：494-499
DOI：10.1016/j.ifacol.2018.09.376
语种：English
出版社：Elsevier
摘要：AbstractIn the processing industries, operating conditions often change to meet the requirements of the market and customers. To cope with the difficulty of on-line quality prediction for such multi-grade processes widely operated in process industries, a novel common and special feature extraction method is proposed for modeling multi-grade processes. A common feature extraction algorithm is proposed to determine the common directions shared by different grades of these processes. After extracting the common features, a partial least-squares modelling algorithm is used to extract the special directions for each grade, respectively. Hence, product quality prediction can be simply conducted by integrating the common and special parts of each grade for model building. A numerical case and an industrial polyethylene process are used to demonstrate the effectiveness and advantage of the proposed method.
关键词：Keywordsmulti-grade processcommon feature extractionsoft sensorlimited dataPLS