Aircraft centre-of-gravity estimation using Gaussian process regression models

Aircraft centre of gravity (C.G.) is important for aircraft safety and performance. This paper proposes the use of Gaussian process regression (GPR) models for the estimation of the C.G. location of fixed-wing aircraft. The major benefit of using a GPR model is that it is a data-based approach explicitly tackling uncertainties caused by the quality and quantity of the data as well as sensor measurement noise. The proposed method consists of two steps: the estimation of the fuel tank's C.G. using the GPR model trained with fuel weight property data, and the computation of aircraft C.G. by the C.G. equation. A numerical case study of a transport aircraft shows that the proposed method achieves small mean squared error and gives good estimate of the aircraft C.G. under simulated flight scenarios.