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Radial Basis Function (RBF) neural network-based parameter estimation of coefficients from flight data is a promising approach that does not require solving a traditional analytical approach. This method, which is based on the Black Box concept, can be used to generate a longitudinal flight dynamic model of an aircraft. In this paper, the RBF-Delta method is used to estimate the control and stability derivatives of the HFB-320 aircraft. Comparison of the results has been done using the Least-Square, Delta, and ANFIS Delta methods, and the RBF-Delta method is shown to be the most robust.

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Applying RBF-Delta to Estimate the Aerodynamic Coefficients of an Aircraft in Longitudinal Flight

  • 会议论文

  • 发表日期：

    2025年

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  • Pratham Maheshwari,
  • Ajit Kumar

摘要

Radial Basis Function (RBF) neural network-based parameter estimation of coefficients from flight data is a promising approach that does not require solving a traditional analytical approach. This method, which is based on the Black Box concept, can be used to generate a longitudinal flight dynamic model of an aircraft. In this paper, the RBF-Delta method is used to estimate the control and stability derivatives of the HFB-320 aircraft. Comparison of the results has been done using the Least-Square, Delta, and ANFIS Delta methods, and the RBF-Delta method is shown to be the most robust.