Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey
R. Bhushan Gopaluni, Aditya Tulsyan, Benoît Chachuat, Biao Huang, Jong Min Lee, F. Amjad, Seshu Kumar Damarla, Jong Woo Kim, Nathan P. Lawrence
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.
Topics & Concepts
Monitoring and controlControl (management)Process (computing)Computer scienceScale (ratio)Process controlIndustrial engineeringMachine learningArtificial intelligenceData scienceEngineeringControl engineeringPhysicsQuantum mechanicsOperating systemFault Detection and Control SystemsAdvanced Control Systems OptimizationControl Systems and Identification