Machine learning

Machine learning in process systems engineering: Challenges and opportunities
This “white paper” is a concise perspective of the potential of machine learning in the process systems engineering (PSE) domain, based …
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Linearizing nonlinear dynamics using deep learning
The majority of systems of practical interest are characterized by nonlinear dynamics. This renders the control and optimization of …
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Distributional reinforcement learning for inventory management in multi-echelon supply chains
Reinforcement Learning (RL) is an effective method to solve stochastic sequential decision-making problems. This is a problem …
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Hybrid data-driven and first principles monitoring applied to the Tennessee Eastman process
In this work we present a hybrid monitoring approach for fault detection using the Tennessee Eastman (TE) process. We benchmark our …
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Investigating physics-informed neural networks for bioprocess hybrid model construction
Integrating physical knowledge and machine learning is a cost-efficient solution to modelling complex biochemical processes when the …
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Online Feedback Optimization of Compressor Stations with Model Adaptation using Gaussian Process Regression
Online Feedback Optimization is a method used to steer the operation of a process plant to its optimal operating point without …
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Convex Q-learning: Reinforcement learning through convex programming
Over the last decade, Reinforcement Learning (RL) has received significant attention as it promises novel and efficient solutions to …
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Data-driven optimization for process systems engineering applications
Most optimization problems in engineering can be formulated as ‘expensive’ black box problems whose solutions are limited by the number …
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Constrained model-free reinforcement learning for process optimization
Reinforcement learning (RL) is a control approach that can handle nonlinear stochastic optimal control problems. However, despite the …
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Machine learning for biochemical engineering: A review
The field of machine learning is comprised of techniques, which have proven powerful approaches to knowledge discovery and construction …
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