14 citations · 20 across the 8 of their papers we have counts for
4 papers · 1 filter
Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes
Panagiotis Petsagkourakis, Benoit Chachuat, Ehecatl Antonio del Rio-Chanona
This paper proposes a new class of real-time optimization schemes to overcome system-model mismatch of uncertain processes. This work's novelty lies in integrating derivative-free…
Safe Chance Constrained Reinforcement Learning for Batch Process Control
Max Mowbray, Panagiotis Petsagkourakis, Ehecatl Antonio del Río Chanona +1
Reinforcement Learning (RL) controllers have generated excitement within the control community. The primary advantage of RL controllers relative to existing methods is their abilit…
Constrained Model-Free Reinforcement Learning for Process Optimization
Elton Pan, Panagiotis Petsagkourakis, Max Mowbray +2
Reinforcement learning (RL) is a control approach that can handle nonlinear stochastic optimal control problems. However, despite the promise exhibited, RL has yet to see marked tr…
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…