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2023
Diploma Thesis
Title
Identification of the Aerodynamic Derivatives of a VTOL Aircraft from Flight Data
Abstract
This thesis presents a general method for the identification of aerodynamic derivatives using flight data, that is applicable to fixed-wing aircraft or VTOL aircraft in fixed-wing mode. The proposed method consists of seven steps including the initial aerodynamic analysis, maneuver/input design, simulation/flight test, data processing, aerodynamic model structure determination, aerodynamic derivatives identification, and model validation. The software Flow5, AVL, and Matlab/Simulink were implemented to develop and validate the proposed method. Although a flight test was not able to be carried out as planned, the sensor measurement system which includes an extended Kalman Filter with an IMU and a GPS sensor was modeled and included as part of the simulation, with the aim of better resembling the realworld measured flight data. The simulation results have verified the reliability of the proposed technique for accurately identifying aerodynamic derivatives, provided that the flight data is close to ideal, in another word, the flight data does suffer significantly from signal noises and distortion. The methodology presented in this work can be utilized as a baseline method for identifying aerodynamic derivatives from flight data. At each step in the procedures, additional techniques and methods can be explored and integrated to optimize the efficiency and accuracy of the identification process.
Thesis Note
Dresden, TU, Dipl.-Arb., 2023
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Advisor(s)