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Numerical solution of problem of assessment of completeness characteristics of unmanned aerial vehicle by a method of structural-parametric synthesis

Keywords:

Tran Minh Hai – Post-graduate Student, Moscow Institute of Physics and Technology (State University)
E-mail: minhhai.kq80@gmail.com
Nguyen Quang Thuong – Dr.Sc.(Eng.), Professor, State University of Management (Moscow)
E-mail: tikhonovrus@gmail.com
F.F. Pashchenko – Dr.Sc.(Eng.), Professor, Moscow Institute of Physics and Technology (State University); V.A. Trapeznikov Institute of Control Sciences of RAS (Moscow)
E-mail: feodor@ipu.ru (veronika@ipu.ru)


The aerodynamic model of UAVs in the linear approximation and the vector of the project solution for aerodynamic derivatives are presented. Based on the founded aerodynamic derivatives, the experimental aerodynamic model of a UAV is reconstructed in a poly-nomial basis.
Using the method of structural-parametric synthesis, project-functional relationships between design parameters and criterial estimation of UAV characteristics were retrieved. Estimation of completeness of the experimental (approximating) UAV model is carried out by the determination criteria and by Durbin-Watson.
Numerical analysis of the completeness of the experimental aerodynamic model was carried out for three aerodynamic coefficients: Cx, Cy и my. Approximating models are consistently constructed for Cx, Cy, Cz, mx, my,mz in two stages. At the first stage an optimal approximating model is constructed. At the second stage, a structural analysis of the obtained model is carried out using the correlation matrix, where the most correlated members of the model are identified and with their further reduction.
A software-methodical complex for estimating the completeness of the UAV model is presented.
The obtained aerodynamic model of UAVs in the solution of the problem of estimating the completeness of aerodynamic characteristics from experimental data made it possible to obtain the trajectory of the UAV motion, which diverges with the experimental data with an accuracy of the order of 10−9. In this case, the magnitude of the overshoot was improved from the value 8.888 to 6.3.10−8.

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