Optimization of the conceptual development of unmanned aerial vehicles

Аuthors

Huseynova R. ^1*, Gumbatov D. A.^2**

1. Azerbaijan University of Architecture and Construction, Baku, Republic of Azerbaijan
2. National Aerospace Agency of Azerbaijan Republic, NASA, 1, Suleyman Sani Akhundov str., Baku, AZ1115, Azerbaijan Republic

*e-mail: Rena.huseynova55@mail.ru
**e-mail: h.dilan@mail.ru

Abstract

The issues of flight reliability aerodynamic ensuring occupy special place while solving the problems on the UAV design. The basic factors affecting the UAV flight range, such as flight altitude, velocity, wind impact, propeller operating efficiency, are being considered in the MALE UAV robust design method. Accounting for these factors in the robust design method, which includes both optimization and probabilistic analysis performing is a substantial advantage of the robust approach compared to the conventional optimization without accounting for random factors. The purpose of the presented work consists in further improvement of the robust optimization process by extra optimization procedures introduction into it to account for some random factors impact on the quality target of the UAV operation. The article adduces the problems of the UAV robust design in terms of minimizing the normalized random component of the UAV real key figure at the given goal value of the same indicator with account for the random affecting factors (flight speed, flight altitude). The authors computed marginal optimal ratios of random component of the given goal value and derivatives of the basic figure by random factors at which the optimization goal function random component reaches its minimum.
The obtained results allow selecting separately the values of pairs of computed indicators according to a certain rule, allowing minimizing the random component of the value of the objective function of the optimization under certain specified restrictive conditions for the desired functions of the introduced relationship of indicators. New optimization problems of the conceptual unmanned aerial vehicles development have been formed and solved in the context of the well-known MALE UAV methodology. To account for the impact of such random indicators as altitude and flight speed on some basic UAV performance indicator, the task of the random component minimizing of the UAV target function estimate. The values of the selected pairs of indicators are determined, allowштп minimize the random component of the objective function value.

Keywords:

UAV, conceptual design, optimization, objective function, flight altitude, flight speed

References

1. Kochkarov A.A. Proektirovanie budushchego. Problemy tsifrovoi real'nosti, 2018, no. 1 (1), pp. 113-121. DOI: 10.20948/future-2018-17
2. Timoshenko A.V., Baldychev M.T., Marenkov I.A., Pivkin I.G. Trudy MAI, 2020, no. 111. URL: https://trudymai.ru/eng/published.php?ID=115145. DOI: 10.34759/trd-2020-111-10
3. Koshkarov A.S., Gulii D.D., Baryaksheva V.A. Trudy MAI, 2023, no. 132. URL: https://trudymai.ru/eng/published.php?ID=176835
4. Turkin I.K., Trokhov D.A. Nauchnyi vestnik MGTU GA, 2015, no. 221, pp. 106-114.
5. Yatsyna Yu.F. Izvestiya Natsional'noi akademii nauk Belarusi. Seriya fiziko-tekhnicheskikh nauk, 2018, vol. 63, no. 3, pp. 368-380. URL: https://doi.org/10.29235/1561-8358-2018-63-3-368-380
6. Bulat P.V., Minin O.P. Nauchno-tekhnicheskii vestnik informatsionnykh tekhnologii, mekhaniki i optiki, 2017, vol. 17, no. 6, pp. 961-996.
7. Prisyazhnyuk A.S., Aref'ev A.D., Cherepanov A.S., Khraban A.V. Informatsiya i kosmos, 2015, no. 2, pp. 124-129.
8. Akhramovich S.A., Barinov A.V., Malyshev V.V., Starkov A.V. Vestnik Samarskogo universiteta. Aerokosmicheskaya tekhnika, tekhnologiya i mashinostroenie, 2018, vol. 17, no. 2, pp. 7-22.
9. Vavilov V.E., Ismagilov F.R., Mustaev E.I., Urazbakhtin R.R. Trudy MAI, 2023, no. 131. URL: https://trudymai.ru/eng/published.php?ID=175917. DOI: 10.34759/trd-2023-131-11
10. Karimov A.Kh. Trudy MAI, 2011, no. 47. URL: https://trudymai.ru/eng/published.php?ID=26769
11. Uglov M.A., Akmaliev A.N. Vestnik nauki, 2023, no. 12 (69), vol. 3. URL: https://www.vestnik-nauki.RF/article/11751
12. Egorov A.A., Ul'yanov D.V. Avtomatizatsii i IT v neftegazovoi oblasti, 2021, no. 1 (43), pp. 34-44.
13. Sobieszczanski-Sobieski J., Haftka R.T. Multidisciplinary aerospace design optimization: survey of recent developments, Structural and multidisciplinary optimization, 1997, vol. 14, no 1, pp. 1-23. DOI: 10.1007/BF01197554
14. Dimitri N.M., Bandte O., De Laurentis D.A. Robust design simulation: a probabilistic approach to multidisciplinary design, Journal of aircraft, 1999, vol. 36, no. 1, pp. 298-307.
15. Park G.J., Lee T.H., Lee K.H., Hwang K.H. Robust design: an overview, AIAA Journal, 2006, vol. 44, no. 1, pp. 181-191. DOI: 10.2514/1.13639
16. Doltsinis I., Kang Z. Robuts design of structures using optimization methods, Computer Methods in applied mechanics and engineering, 2004, vol. 193, no. 23-26, pp. 2221-2237. DOI: 10.1016/j.cma.2003.12.055
17. Park H.U., Kim S.H., Lee J.W., Byun Y.H. Design of very light jet (VJL) aircraft using robust design optimization approach, CJK 5th proceedings, Jeju. Korea, 2008.
18. Chen W., Garimella R., Michelena N. Robust design for improved vehicle handling under a range of maneuver conditions, Engineering Optimization, 2001, vol. 33, no. 3, pp. 303-326.
19. Nguyen N.V., Maxim T., Park H.U., Kim S., Lee J.W. A multidisciplinary robust optimization framework for UAV conceptual design, Aeronautical Journal, 2014, vol. 118, no. 1200, pp. 123–142.
20. El'sgol'ts L.E. Differentsial'nye uravneniya i variatsionnoe ischislenie (Differential equations and calculus of variations), Moscow, Nauka, 1974, 432 p.

Download