This paper presents the frame work for aerodynamic parameter estimation for small fixed wing unmanned aerial vehicle (UAV). The recent development in autopilot hardware for small UAV enables the in-flight data collection of flight characteristics. A methodology is outlined to collect, process and arrive at a conclusion from the in-flight data using commercial flight controller of under 2kg (micro) fixed wing aircraft, ‘VAF01’ for which a Fault Detection and Identification (FDI) system is under development. As a part of the FDI, the linear longitudinal (3 DOF) aerodynamic model is developed and in-flight experimental data is used to estimate the longitudinal aerodynamic parameters. The Flight Path Reconstruction is completed with the acquired parameters from in-flight experiments and results are discussed for further utilization of them.
Neural Partial Differentiation Based Nonlinear Parameter Estimation from Noisy Flight Data
