arXiv · 2209.11123
Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey
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.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
R. Bhushan Gopaluni, Aditya Tulsyan, Benoit Chachuat, Biao Huang, Jong Min Lee, Faraz Amjad, Seshu Kumar Damarla, Jong Woo Kim, Nathan P. Lawrence. 2022-09-22. Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey. https://doi.org/10.1016/j.ifacol.2020.12.126
Cite the original work for its findings. Save a collection to share your selection of sources.