Размещение бортового оборудования в пространстве фюзеляжа беспилотного летательного аппарата с применением генетического алгоритма
Работая с нашим сайтом, вы даете свое согласие на использование файлов cookie. Это необходимо для нормального функционирования сайта, показа целевой рекламы и анализа трафика. Статистика использования сайта отправляется в «Яндекс» и «Google»
Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Placing on-board equipment in the fuselage space of an unmanned aerial vehicle using a genetic algorithm

idGainutdinov R.R. idChermoshentsev S.F.

UDC 681.396.6.049.77
DOI: 10.26102/2310-6018/2024.44.1.021

  • Abstract
  • List of references
  • About authors

The current stage of unmanned aircraft system development is characterized by the widespread introduction of automated and intelligent electronic systems. One of the most difficult and critical stages in the development of unmanned aerial vehicles is determining the optimal locations for placing on-board equipment in the fuselage space. To solve this problem, the approach for determining the optimal installation locations for on-board equipment in the fuselage space of an unmanned aerial vehicle is proposed. The approach is based on the use of a genetic algorithm. A meaningful and mathematical formulation of the problem of determining the optimal installation locations for on-board equipment in the fuselage space of an unmanned aerial vehicle is given. Criteria and restrictions have been developed. As optimization criteria, first of all, electromagnetic compatibility criteria are considered, which are characterized by minimizing the sensitivity of on-board equipment above the level of electromagnetic field strength at the installation sites of on-board equipment, as well as limiting the excess of the threshold level of susceptibility of on-board equipment over the electromagnetic environment resulting from electromagnetic influences or interactions. Additionally, criteria for minimizing the total weighted length of cable connections are considered, and the maximum load-carrying capacity of the fuselage compartments of an unmanned aerial vehicle is limited. The plan has been developed for the installation of on-board equipment in the fuselage space using a developed program that implements a genetic algorithm.

1. Kirillov V.Yu., Fuentes R.K. An algorithm for designing an on-board cable network of mobile objects taking into account electromagnetic compatibility. Tekhnologii elektromagnitnoy sovmestimosti = Technologies of electromagnetic compatibility. 2008;(2):47–50. (In Russ.).

2. Gainutdinov R.R., Chermoshentsev S.F. Methodology for Studying the Electromagnetic Resistance of Technical Systems under External Electromagnetic Effect from Several Sources. Russian Aeronautics. 2023;66(2):146–153. DOI: 10.3103/S1068799823010208.

3. Gaynutdinov R.R., Chermoshentsev S.F. Metaelement Parameters Optimization for Creation Metamaterial with Given Electromagnetic Properties. In: 2021 International Russian Automation Conference, RusAutoCon 2021, 05-11 September 2021, Sochi, Russia. IEEE; 2021. p. 775–779.

4. Averin S.V., Kirillov V.Yu., Mashukov E.V., Reznikov S.B., Shevtsov D.A. Ensuring the electromagnetic compatibility of onboard cables for unmanned aerial vehicles. Russian Aeronautics. 2017;60(3):442–446. DOI: 10.3103/S1068799817030175.

5. Gainutdinov R.R., Chermoshentsev S.F. Methodology to ensure the intrasystem electromagnetic compatibility of UAV avionics. Russian Aeronautics. 2016;59(4):613–618. DOI: 10.3103/S1068799816040279.

6. Gladkov L.A., Kureychik V.V., Kureychik V.M. Genetic algorithms. M.: Fizmatlit; 2006. 320 р. (In Russ.).

7. Belousov A.O., Gazizov T.T., Gazizov T.R. Multicriteria optimization of four-conductor modal filter by genetic algorithms. In: 2017 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON), 18-22 September 2017, Novosibirsk, Russia. IEEE; 2017. p. 445–448.

8. Suzdaltsev I.V., Chermoshencev S.F., Bogula N.Yu. Bionic algorithms for multi-criteria design of electronic equipment printed circuit board. In: 2017 XX IEEE International Conference on Soft Computing and Measurements (SCM), 24-26 May 2017, Saint-Petersburg, Russia. IEEE; 2017. p. 394−396.

9. Tsarev I.V. Planning the aircraft cable assembly lines, taking into account intersystem electromagnetic compatibility. In: IEEE 6th International Symposium on Electromagnetic Compatibility and Electromagnetic Ecology, 21-24 June 2005, Saint-Petersburg, Russia. IEEE; 2005. p. 163−166.

Gainutdinov Rustam Rafkatovich
Candidate of Engineering Sciences
Email: emc-kai@mail.ru

WoS | Scopus | ORCID | eLibrary |

Kazan National Technical University named after A.N. Tupolev

Kazan, the Russian Federation

Chermoshentsev Sergey Fedorovich
Doctor of Engineering Sciences

ORCID |

Kazan National Technical University named after A.N. Tupolev

Kazan, the Russian Federation

Keywords: placement, optimization, on-board equipment, genetic algorithm, unmanned aerial vehicle

For citation: Gainutdinov R.R. Chermoshentsev S.F. Placing on-board equipment in the fuselage space of an unmanned aerial vehicle using a genetic algorithm. Modeling, Optimization and Information Technology. 2024;12(1). Available from: https://moitvivt.ru/ru/journal/pdf?id=1484 DOI: 10.26102/2310-6018/2024.44.1.021 (In Russ).

89

Full text in PDF

Received 12.12.2023

Revised 22.01.2024

Accepted 12.03.2024

Published 13.03.2024