146 citations · 435 across the 22 of their papers we have counts for
3 papers · 1 filter
Optimal PID and Antiwindup Control Design as a Reinforcement Learning Problem
Nathan P. Lawrence, Gregory E. Stewart, Philip D. Loewen +3
Deep reinforcement learning (DRL) has seen several successful applications to process control. Common methods rely on a deep neural network structure to model the controller or pro…
Reinforcement Learning based Design of Linear Fixed Structure Controllers
Nathan P. Lawrence, Gregory E. Stewart, Philip D. Loewen +3
Reinforcement learning has been successfully applied to the problem of tuning PID controllers in several applications. The existing methods often utilize function approximation, su…
Deep Reinforcement Learning for Process Control: A Primer for Beginners
Steven Spielberg, Aditya Tulsyan, Nathan P. Lawrence +2
Advanced model-based controllers are well established in process industries. However, such controllers require regular maintenance to maintain acceptable performance. It is a commo…