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Reinforcement Learning For Process Control: Applications To Energy Systems, Elijah Ballard Hedrick
Reinforcement Learning For Process Control: Applications To Energy Systems, Elijah Ballard Hedrick
Graduate Theses, Dissertations, and Problem Reports
Reinforcement learning (RL) is a machine learning method that has recently seen significant research activity owing to its successes in the areas of robotics and gameplaying (Silver et al., 2017). However, significant challenges exist in the extension of these control methods to process control problems, where state and input signals are nearly always continuous and more stringent performance guarantees are required. The goal of this work is to explore ways that modern RL algorithms can be adapted to handle process control problems; avenues for this work include using RL with existing controllers such as model predictive control (MPC) and adapting …