06.2 - Flight Dynamics and Control (UAV related)
ENSEMBLE MACHINE LEARNING FOR UAV PROPELLER PERFORMANCE PREDICTION WITH UNCERTAINTY QUANTIFICATION
M.I. Alam¹, A.H. Baluch¹, S.H. Vattathurvalappil¹; ¹King Fahd University of Petroleum and Minerals, Saudi Arabia
This work presents a physics-informed ML framework for UAV propeller prediction with dual Uncertainty Quantification. Achieving R²>0.92 on 30,188 samples, it offers real-time, accurate predictions with safety margins. This enables reliability-aware optimization, addressing critical safety gaps in electric UAV design.
DOI: 10.71945/icas2026_0529