146 citations · 435 across the 22 of their papers we have counts for
4 papers · 1 filter
Data Quality Over Quantity: Pitfalls and Guidelines for Process Analytics
Lim C. Siang, Shams Elnawawi, Lee D. Rippon +2
A significant portion of the effort involved in advanced process control, process analytics, and machine learning involves acquiring and preparing data. Literature often emphasizes…
Modern Machine Learning Tools for Monitoring and Control of Industrial Processes: A Survey
R. Bhushan Gopaluni, Aditya Tulsyan, Benoit Chachuat +6
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.…
Meta-Reinforcement Learning for Adaptive Control of Second Order Systems
Daniel G. McClement, Nathan P. Lawrence, Michael G. Forbes +3
Meta-learning is a branch of machine learning which aims to synthesize data from a distribution of related tasks to efficiently solve new ones. In process control, many systems hav…
Meta-Reinforcement Learning for the Tuning of PI Controllers: An Offline Approach
Daniel G. McClement, Nathan P. Lawrence, Johan U. Backstrom +3
Meta-learning is a branch of machine learning which trains neural network models to synthesize a wide variety of data in order to rapidly solve new problems. In process control, ma…