Deep reinforcement learning discovers high-frequency bang-bang and low-frequency lock-on rotary controls that suppress vibrations in fully and underactuated tandem cylinders by 70-95%.
Triantafyllou, and George Em Karniadakis
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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An LLM-based self-evolving agent discovers a traveling-wave controller with body-frame guidance and yaw feedback that generalizes to unseen targets for an underactuated fluid swimmer.
Reformulating DRL in a moving reference frame enables reliable control of rapid transitions between mode-locked states in a 1D RDE model by separating fast detonation propagation from slower operating-mode dynamics.
citing papers explorer
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Self-Evolving Scientific Agent Discovers Generalizable Physically-Reasoned Fluid Control
An LLM-based self-evolving agent discovers a traveling-wave controller with body-frame guidance and yaw feedback that generalizes to unseen targets for an underactuated fluid swimmer.