Learn to Flap: Foil Non-parametric Path Planning via Deep Reinforcement Learning

• Published in: arXiv.org
• Main Authors: Wang, Z P, Lin, R J, Zhao, Z Y, Guo, P M, Yang, N, Fan, D X
• Format: Paper
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 25.05.2023
• Subjects: Deep learning; Flapping; Fluid flow; Foils; Optimization; Sine waves; Training

To optimize flapping foil performance, the application of deep reinforcement learning (DRL) on controlling foil non-parametric motion is conducted in the present study. Traditional control techniques and simplified motions cannot fully model nonlinear, unsteady and high-dimensional foil-vortex inter...