Statistical approach to the problem of identifying the aerodynamic characteristics of an unmanned aerial vehicle from the experimental data
- 1 Dr.Sc. (Eng.), Professor, Institute of UMIM and MB State University of Management (GUU)
- 2 Dr.Sc. (Eng.), Professor, Moscow Institute of Physics and Technology (State University)
- 3 Post-graduate Student, Moscow Institute of Physics and Technology (State University)
Abstract
In considering of the problem in structural and parametric synthesis of UAV based on morphological and combinatorial design principles for searching optimal alternative solution here will presented mathematical apparatus of multipartite graphs (T-partite), the method of morphological boxes, morphological variety of options to describe the functional systems in the form of morphological tables and methods of information with statistics analysis models based random sample of the experimental data.
Presented searching algorithms of optimal structures on the base of structural and parametric synthesis of: 1) one-criterion algorithms of structural and parametric identification; 2) two-criteria algorithms of structural and parametric identification; 3) The algorithms of speed (sequential) orthogonalization of basis (method step evaluation).
Rely on the statistical approach in here, showed the problem in identification of aerodynamic characteristics for the UAV from the ex-perimental data. Presented aerodynamic model UAV.
Quality of reformation of aerodynamic dependencies in the software will estimated by two statistical criteria: criteria of regularity; un-biased criteria. Given here regular criteria for all six of aerodynamic coefficients.
The problem of identification characteristics of the UAV is the selection of project solution that meet the functional limitations System.
How to cite
Тхыонг Н.К., Назаров А.Н., Хай Ч.М. Статистический подход к задаче идентификации аэродинамических характеристик беспилотного летательного аппарата по экспериментальным данным // Успехи современной радиоэлектроники. 2017. № 1. С. 10–16.
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