4 citations · 11 across the 6 of their papers we have counts for
8 papers
Constraint-Guided Symbolic Regression for Data-Efficient Kinetic Model Discovery
Miguel Ángel de Carvalho Servia, Ilya Orson Sandoval, King Kuok +4
The industrialization of catalytic processes hinges on the availability of reliable kinetic models for design, optimization, and control. Traditional mechanistic models demand exte…
An Attentive Graph Agent for Topology-Adaptive Cyber Defence
Ilya Orson Sandoval, Isaac Symes Thompson, Vasilios Mavroudis +1
As cyber threats grow increasingly sophisticated, reinforcement learning (RL) is emerging as a promising technique to create intelligent and adaptive cyber defense systems. However…
PC-Gym: Benchmark Environments For Process Control Problems
Maximilian Bloor, José Torraca, Ilya Orson Sandoval +6
PC-Gym is an open-source tool for developing and evaluating reinforcement learning (RL) algorithms in chemical process control. It features environments that simulate various chemi…
The Automated Discovery of Kinetic Rate Models -- Methodological Frameworks
Miguel Ángel de Carvalho Servia, Ilya Orson Sandoval, Klaus Hellgardt +4
The industrialization of catalytic processes requires reliable kinetic models for their design, optimization and control. Mechanistic models require significant domain knowledge, w…
Neural ODEs as Feedback Policies for Nonlinear Optimal Control
Ilya Orson Sandoval, Panagiotis Petsagkourakis, Ehecatl Antonio del Rio-Chanona
Neural ordinary differential equations (Neural ODEs) define continuous time dynamical systems with neural networks. The interest in their application for modelling has sparked rece…
Chance Constrained Policy Optimization for Process Control and Optimization
Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford +3
Chemical process optimization and control are affected by 1) plant-model mismatch, 2) process disturbances, and 3) constraints for safe operation. Reinforcement learning by policy…
Constrained Reinforcement Learning for Dynamic Optimization under Uncertainty
Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford +2
Dynamic real-time optimization (DRTO) is a challenging task due to the fact that optimal operating conditions must be computed in real time. The main bottleneck in the industrial a…
Reinforcement Learning for Batch Bioprocess Optimization
Panagiotis Petsagkourakis, Ilya Orson Sandoval, Eric Bradford +2
Bioprocesses have received a lot of attention to produce clean and sustainable alternatives to fossil-based materials. However, they are generally difficult to optimize due to thei…