Aircraft system identification has been widely used to this day in applications like control law design, building simulators or extending flight envelopes. It can also be utilized for determining flight-mechanical characteristics in the preliminary design phase of a flight vehicle. In this thesis, three common time-domain methods were implemented in MATLAB for determining the aerodynamic derivatives of a subscale aircraft. For parameter estimation, the equation-error method is quick, robust and can provide good parameter estimates on its own. The output-error method is computationally intensive but keeps account of the aircraft's evolution in time, being more suitable for fine-tuning predictive models. A new model structure is identified using multivariate orthogonal functions with a predicted squared error stopping criteria. This method is based on linear regression (equation-error). The code written is flexible and can also be used for other aircraft and with other aerodynamic models. Simulations are compared with experimental data from a previous flight test campaign for validation. In the future, this tool may help taking decisions in conceptual design after a prototype is tested.

This doctoral study aims to develop a methodology for use in determining aerodynamic models and parameters from actual flight test data for different types of autonomous flight vehicles. The stepwise regression method and equation error method are utilized for the aerodynamic model identification and parameter estimation. A closed loop aerodynamic parameter estimation approach is also applied in this study which can be used to fine tune the model parameters. Genetic algorithm is used as the optimization kernel for this purpose. In the optimization scheme, an input error cost function is used together with a final position penalty as opposed to widely utilized output error cost function. Available methods in the literature are developed for and mostly applied to the aerodynamic system identification problem of piloted aircraft / a very limited number of studies on autonomous vehicles are available in the open literature. This doctoral study shows the applicability of the existing methods to aerodynamic model identification and parameter estimation problem of autonomous vehicles. Also practical considerations for the application of model structure determination methods to autonomous vehicles are not well defined in the literature and this study serves as a guide to these considerations.

Tato práce je zaměřena na odhad letových parametrů malého letounu, konkrétně letounu Evektor SportStar RTC. Pro odhad letových parametrů jsou použity metody "Equation Error Method", "Output Error Method" a metody rekurzivních nejmenších čtverců. Práce je zaměřena na zkoumání charakteristik aerodynamických parametrů podélného pohybu a ověření, zda takto odhadnuté letové parametry odpovídají naměřeným datům a tudíž vytvářejí předpoklad pro realizaci dostatečně přesného modelu letadla. Odhadnuté letové parametry jsou dále porovnávány s a-priorními hodnotami získanými s využitím programů Tornado, AVL a softwarovéverze sbírky Datcom. Rozdíly mezi a-priorními hodnotami a odhadnutými letovými paramatery jsou porovnány s korekcemi publikovanými pro subsonické letové podmínky modelu letounu F-18 Hornet.