文章基本信息

标题：Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey
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作者：R. Bhushan Gopaluni ; Aditya Tulsyan ; Benoit Chachuat 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：218-229
DOI：10.1016/j.ifacol.2020.12.126
语种：English
出版社：Elsevier
摘要：AbstractOver the last ten years, we have seen a significant increase in industrial data, tremendous improvement in computational power, and major theoretical advances in machine learning. This opens up an opportunity to use modern machine learning tools on large-scale nonlinear monitoring and control problems. This article provides a survey of recent results with applications in the process industry.
关键词：Keywordsstatistical machine learningdeep learningreinforcement learningmonitoringcontrol