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Fast-adaption thrust optimization by cluster-based control for a pitching foil
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DOI：10.1063/5.0230049.png)
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To optimize flapping motion for pitching foil dynamics, we significantly expand the search space to include non-periodic feedback laws through the application of the cluster-based control method, which is integrated with interpolation and machine learning optimization techniques. This approach allows for dynamic adjustment between transient and steady-state conditions, leading to an 18% increase in thrust efficiency compared to traditional sinusoidal waveforms. By clustering flow field dynamics into two cycle categories with eight clusters and optimizing closed-loop control laws, we achieve accelerated convergence to the optimal thrust cycle. The proposed approach not only refines control strategies for pitching foil dynamics but also ensures robustness and efficiency in the system performance.
期刊
IF:
4.3
论文数:
2.9W
被引数:
8.0W
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