Aerospace Technic and Technology

This study addresses the critical issue of modernizing existing unmanned aerial vehicles (UAVs) to enhance their applicability in the contemporary conditions of hybrid warfare. The research focuses on adapting the structural design of UAVs through reengineering, enabling their deployment in swarm attack operations against high-priority enemy targets. Thus, this publication explores the essential measures for planning project activities related to UAV modernization, aiming to align their capabilities with the operational needs of military forces on the battlefield. The primary objective of this study is to develop a comprehensive set of mathematical and simulation models that facilitate the planning of UAV modernization projects. The models are intended to optimize new functions related to control, coordination, and navigation, enabling UAVs to perform as part of drone swarms in military missions. This research analyzes the existing challenges in reengineering high-tech systems for evolving operational environments and presents possible UAV reengineering strategies. A particular emphasis is placed on the component-based approach to designing new UAVs or upgrading existing ones. The study categorizes UAV components into three types within the architecture of modern high-tech systems: existing components, components requiring modernization, and newly developed components. The findings highlight the necessity of balancing the reuse of existing components with the integration of innovative technologies. While innovative components enhance UAV capabilities, they also increase project duration, costs, and associated risks – factors that are particularly critical during a state of war. This study also examines the currently deployed UAV models to assess their suitability for modernization projects. In the initial stages of UAV modernization, expert assessments from specialists in complex system manufacturing and military operations are used to evaluate and rank potential modernization options. These qualitative evaluations, represented as linguistic variables, were processed using the lexicographic ordering of alternatives to identify the most reasonable option for implementation. Integrating new components into existing UAV architectures necessitates optimizing reengineering decisions under constraints such as limited time, budget, and heightened risks due to national security conditions. To address this, an optimization model based on integer (Boolean) programming was developed for selecting the most rational UAV component architecture. Additionally, significant attention is given to structuring the sequence of project activities, estimating the project completion time, and evaluating the risks associated with UAV modernization. A simulation model was constructed to analyze the lifecycle of new UAV components or the modernization of existing ones within a specified time scale. The entire modernization project was also simulated to assess the feasibility and efficiency. Using the agent-based platform AnyLogic, interactive simulation modeling of the UAV modernization processes was conducted. The scientific novelty of this research lies in the development of original models that enable comprehensive UAV analysis for modernization. These models facilitate the selection of new UAV components, assess modernization project timelines and risks, and apply simulation modeling to evaluate the sequence of project activities. The research findings provide a foundation for planning UAV modernization processes to enhance their operational effectiveness in modern hybrid warfare. By integrating aerial operations with ground-based military actions, this approach contributes to strengthening national defense capabilities.

Modernization of UAVs; strategies; system analysis; multiple options; component design; lexicographic ordering; mathematical models; simulation modeling; project activities; and multi-criteria optimization

Zhang, J., Campbell, J., Sweeney, D., & Hupman, A. Energy consumption models for delivery drones: A comparison and assessment. Transportation Research Part D: Transport and Environment, 2023, vol. 90, article no. 102668. DOI: 10.1016/j.trd.2020.102668.

Abdelkader, M., Güler, S., Jaleel, H., & Shamma, J. S. Aerial swarms: Recent applications and challenges. Current robotics reports, 2021, no. 2, pp. 309-320. DOI: 10.1007/s43154-021-00063-4.

Asaamoning, G., Mendes, P., Rosário, D., & Cerqueira, E. Drone swarms as networked control systems by integration of networking and computing. Sensors, 2021, no. 21 (8), article no. 2642. DOI:10.3390/s21082642.

Fedorovych, O., Kritskiy, D., Malieiev, L., Rybka, K., & Rybka, A. Military logistics planning models for enemy targets attack by a swarm of combat drones. Radioelectronic and Computer Systems, 2024, no. 1, pp. 207-216. DOI: 10.32620/reks.2024.1.16.

Qian, F., Su, K., Liang, X., & Zhang, K. Task Assignment for UAV Swarm Saturation Attack: A Deep Reinforcement Learning Approach. Electronics, 2023, vol. 12, iss. 6, article no. 1292. DOI: 10.3390/electronics12061292.

Matrunchyk, D. M. Modernization of the Military-Industrial and Security Complex as the Main Link in the Innovative Transformation of the Post-War Economy of the Regions of Ukraine. Problemy Ekonomiky, 2023, no. 3, pp. 81-87. DOI: 10.32983/2222-0712-2023-3-81-87.

Mosov, S. Swarming of military drones: realities and prospects. Collection of scientific papers of the Centre for Military and Strategic Studies of the National Defence University of Ukraine, 2024, no. 1 (80), pp. 77-86. DOI: 10.33099/2304-2745/2024-1-80/77-86.

Fedorovich, O., Uruskiy, O., Pronchakov, Y., & Lukhanin, M. Method and information technology to research the component architecture of products to justify investments of high-tech enterprise. Radioelectronic and Computer Systems, 2021, no. 1, pp. 150-157. DOI: 10.32620/reks.2021.1.13.

Kushnir, O. I., Davykoza, O. P., & Kucherenko, Y. F. Analysis of the impact of hybrid warfare on the development of an automated aviation and air defense control system of the Air Force of Ukraine. Science and Technology of the Air Force of Ukraine, 2017, no. 2, pp. 116-120. Available at: http://nbuv.gov.ua/UJRN/Nitps_2017_2_25.

Puente-Castro, A., Rivero, D., Pazos, A., & Fernandez-Blanco, E. A review of artificial intelligence applied to path planning in UAV swarms. Neural Computing and Applications, 2022, no. 34, pp. 153–170. DOI: 10.1007/s00521-021-06569-4.

Caballero-Martin, D., Lopez-Guede, J. M., Estevez, J., & Graña, M. Artificial intelligence applied to drone control: A state of the art. Drones, 2024, no. 8, iss. 7, article no. 296. DOI: 10.3390/drones8070296.

Sanchez-Lopez, J.L., Pestana, J., de la Puente, P., & Campoy P. A Reliable Open-Source System Architecture for the Fast Designing and Prototyping of Autonomous Multi-UAV Systems: Simulation and Experimentation. Journal of Intelligent & Robotic Systems, 2016, no. 84, pp. 779–797. DOI: 10.1007/s10846-015-0288-x.

Gromada, K. A., & Stecz, W. M. Designing a Reliable UAV Architecture Operating in a Real Environment. Applied Sciences, 2022, no. 12, iss. 1, article no. 294. DOI: 10.3390/app12010294.

Movchan, K. O. Classification systems for unmanned aerial vehicles and their application in various industries. Scientific notes of Taurida National V.I. Vernadsky University. Series: Technical Science, 2024, vol. 35 (74), no. 6, part 1, pp. 1-7. DOI: 10.32782/2663-5941/2024.6.1/01.

Fan, B., Li, Y., Zhang, R., & Fu, Q. Review on the technological development and application of UAV systems. Chinese Journal of Electronics, 2020, no. 29, 2, pp. 199-207. DOI: 10.1049/cje.2019.12.006.

Fedorovich, O., Lutai, L., Kompanets, V., & Bahaiev, I. The Creation of an Optimisation Component-Oriented Model for the Formation of the Architecture of Science-Based Products. In: Integrated Computer Technologies in Mechanical Engineering - 2023. ICTM 2023. Lecture Notes in Networks and Systems, 2024, vol. 996, pp. 415-426, Springer, Cham. DOI: 10.1007/978-3-031-60549-9_31.

Fedorovich, O., Lutai, L., Trishch, R., Zabolotnyi, О., Khomiak, E., & Nikitin, A. Models for Reducing the Duration and Cost of the Aviation Equipment Diagnostics Process Using the Decomposition of the Component Architecture of a Complex Product. In: Information Technology for Education, Science, and Technics. ITEST 2024. Lecture Notes on Data Engineering and Communications Technologies, 2024, vol. 221, pp. 108-125, Springer, Cham. DOI: 10.1007/978-3-031-71801-4_9.

Demidov, B. O., Velichko, O. F., Kucherenko, Y. F., & Kutsak, M. V. Project management for the creation of weapons and military equipment samples in conditions of uncertainty and risk factors. Armaments and military equipment, 2016, no. 2, pp. 14-18. Available at: http://nbuv.gov.ua/UJRN/ovt_2016_2_4. (accessed 1.12.2024).

Chepkov, I. B., Lukhanin, M. I., & Borokhvostov, I. V. Armaments and military equipment, 2016, no. 4, pp. 3-8. Available at: http://nbuv.gov.ua/UJRN/ovt_2016_4_2. (accessed 11.12.2024).

Idries, A., Mohamed, N., Jawhar, I., Mohamed F., & Al-Jaroodi, J. Challenges of developing UAV applications: A project management view. Proceedings of the 2015 International Conference on Industrial Engineering and Operations Management (IEOM), Dubai, United Arab Emirates, 2015, pp. 1-10. DOI: 10.1109/IEOM.2015.7093730.

Nechyporuk, M., Fedorovich, O., Popov, V., & Romanov M. Modeling of specialists’ profiles for planning and implementation of projects for the creation of innovative products of aerospace techniques. Radioelectronic and Computer Systems, 2022, no. 1, pp. 23-35. DOI: 10.32620/reks.2022.1.02.

Samusenko, D., & Sych, M. Innovations in 3D printing technology and their application to create UAVs with minimization of defects using lightweight plastic. Collection of Scientific Papers «ΛΌГOΣ», (February 14, 2025; Boston, USA), pp. 167–171. DOI: 10.36074/logos-14.02.2025.035.

Fan, B., Li, Y., Zhang, R., & Fu, Q. Review on the technological development and application of UAV systems. Chinese Journal of Electronics, 2020, no. 29, iss. 2, pp. 199-207. DOI: 10.1049/cje.2019.12.006.

Fedorovich, O., Pronchakov, Y., Leshchenko, Y., & Yelizieva, A. Using of the component method in logistics of supplies of high-tech production components. Advanced Information Systems, 2021, no. 5, iss. 3, pp. 40–45. DOI: 10.20998/2522-9052.2021.3.06.

Hashemi, S. R., Arasteh, A. & Paydar, M. M. Risk Management of Disruption and Sustainable Development of Supply Chains. Interdisciplinary Journal of Management Studies (Formerly known as Iranian Journal of Management Studies), 2023, no. 16, iss. 1, pp. 277-297. DOI: 10.22059/ijms.2022.329830.674732.

Antonova, A., Aksyonov, K., & Ziomkovskaya, P. Development of a Method and a Software for Decision-Making, System Modeling and Planning of Business Processes. In: Frontiers in Software Engineering. ICFSE 2021. Communications in Computer and Information Science, 2021, vol. 1523, pp. 148-157. Springer, Cham. DOI: 10.1007/978-3-030-93135-3_10.

Fedorovich, O., Pronchakov, Y., Yelizieva, A. & Leshchenko, Y. Simulation of the business processes of the developing enterprise to create complex products with multi-level component architecture. Aerospace Technic and Technology, 2021, no. 4, pp. 79-86. DOI: 10.32620/aktt.2021.4.11.

Pavlov, A., & Kyselov, M. Математичні моделі та методи узгодженого планування. Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information Technologies, 2023, no. 2 (10), pp. 3-8. DOI: 10.20998/2079-0023.2023.02.01.

Rybalchenko, A. An improved method of cutting off non-promising options for the problem of integer linear programming with Boolean variables based on the rank approach. Scientific Works of Kharkiv National Air Force University, 2023, no. 3 (77), pp. 62-66. DOI: 10.30748/zhups.2023.77.09.