An online-trained PPO controller with a finite return horizon aligned to convective time stabilizes a low-duty-cycle actuation pattern and yields a forward-flow fraction of about 53% at the feedback sensor, about one percentage point above optimized periodic open-loop control.
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Deep reinforcement learning for separation control in turbulent wind-tunnel flow
An online-trained PPO controller with a finite return horizon aligned to convective time stabilizes a low-duty-cycle actuation pattern and yields a forward-flow fraction of about 53% at the feedback sensor, about one percentage point above optimized periodic open-loop control.