Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey
arXiv:2209.11123 · doi:10.1016/j.ifacol.2020.12.126
Abstract
Over 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.
arXiv commentIFAC World Congress 2020
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