AINeutralarXiv – CS AI · Mar 174/10
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Iterative Learning Control-Informed Reinforcement Learning for Batch Process Control
Researchers introduce IL-CIRL, a framework combining Iterative Learning Control with Deep Reinforcement Learning to address safety risks and stability issues in industrial batch process control. The method uses Kalman filter-based state estimation to guide DRL agents toward safer, constraint-satisfying control policies.