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July 18, 2026Aircraft Engineering and Aerospace Technology

Modeling and prediction of aircraft control surface angles using machine learning

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Authors

HKHatice Doğan KuzeyFDFatma Yıldırım Dalkıran

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Overview

Randomized trial predicts roll and trimmable horizontal stabilizer angles in aircraft, suggesting enhanced flight control stability.

Key Points

  • This study aims to predict critical aircraft control angles for improved flight stability using machine learning techniques.
  • Applied multivariate modeling approach using real flight data from Airbus A319's flight data recorder.
  • Utilized 16,864 data points, with a 70% training and 30% testing split.
  • Employed decision tree regressor and random forest regressor algorithms to model nonlinear relationships.
  • Random forest model predicted roll and THS angles with higher accuracy than decision tree model.
  • Both models effectively captured nonlinear relationships in the data.
  • Incorporating additional flight parameters could further improve model performance.

Cite This Study

Kuzey et al. (2026) studied this question.

synapsesocial.com/papers/6a5b17e818557b26c2039f85https://doi.org/10.1108/aeat-08-2025-0283
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