DEVELOPMENT OF CONTROL LAWS OF UNMANNED AERIAL VEHICLES FOR PERFORMING GROUP FLIGHT AT THE STRAIGHT-LINE HORIZONTAL FLIGHT STAGE
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Abstract
The article proposes an improved approach to controlling groups of unmanned aerial vehicles (UAVs) aimed at increasing the overall efficiency and flexibility of the control process. The use of a heterogeneous external field, which varies both in magnitude and direction, allows achieving greater adaptability and accuracy in controlling a group of UAVs. A vector field for unmanned aerial vehicles determines the direction and intensity of the vehicles' movement in space. Such vector fields can be used to develop UAV control laws, including determining optimal flight paths, controlling speed, avoiding obstacles, and ensuring coordination of a group of UAVs. The subject of the study is the methods of controlling groups of autonomous UAVs, where each vehicle may have different speeds and flight directions. To solve this problem, various methods of using a heterogeneous field have been developed and proposed. Instead of using a homogeneous field that provides a constant flight speed, a vector field is used that adapts to different conditions and characteristics of the vehicles in the group. This method allows for effective group management, ensuring the necessary coordination and interaction between the vehicles. An analysis of recent research and publications in the field of autonomous system control indicates the feasibility of using machine learning, vector fields, and a large amount of data to successfully coordinate the movement of autonomous systems. These approaches make it possible to create efficient and reliable control systems. The aim of the study is to develop laws for controlling the movement of a group of autonomous unmanned aerial vehicles at the stage of straight-line horizontal flight based on natural analogues to improve the efficiency and reliability of their coordinated movement in different conditions. The main conclusions of the research are that the proposed method of controlling groups of UAVs based on a heterogeneous field can be implemented. It takes into account a variety of vehicle characteristics and environmental conditions that are typical for real-world use scenarios. This work opens up prospects for further improving the management of UAV groups and their use in various fields of activity. The article emphasises the relevance of technology development for autonomous unmanned systems, especially in the context of autonomous transport systems.
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Yeremiyev, M.B., Karatanov, O.V., Kritsky, D.N. and Pogudina, O.K. (2019), “Automated system of the variable-pitch propeller rotation control”, 2019 IEEE 14th International Conference on Computer Sciences and Information Technologies (CSIT), IEEE, 2019. p. 186–191, doi: https://doi.org/10.1109/STC-CSIT.2019.8929757
Pohudina, O., Kritskiy, D., Bykov, A.N. and Szalay, T. (2020), “Method for identifying and counting objects”, Integrated Computer Technologies in Mechanical Engineering: Synergetic Engineering, Springer International Publishing, Cham, pp. 161-172, doi: https://doi.org/10.1007/978-3-030-37618-5_15
Kritskiy, D., Karatanov A., Koba S. and Druzhinin E. (2018), “Increasing the reliability of drones due to the use of quaternions in motion”, 2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies (DESSERT), IEEE, pp. 348-352, doi: https://doi.org/10.1109/DESSERT.2018.8409157
Podorozhniak, A., Liubchenko, N., Sobol, M. and Onishchenko, D. (2023), “Usage of mask R-CNN for automatic license plate recognition”, Advanced Information Systems, Vol. 7, no. 1, pp. 54–58, doi: https://doi.org/10.20998/2522-9052.2023.1.09
Bychok, M.A.and Pogudina, O.K. (2021), “Evaluation of use of design templates in the software development”, Radioelectronic and Computer Systems, 2021, No. 1(97), pp. 101–109, doi: https://doi.org/10.32620/reks.2021.1.09
Kritsky, D.N., Ovsiannik, V.M., Pogudina, O.K., Shevel, V.V. and Druzhinin, E.A. (2019), “Model for intercepting targets by the unmanned aerial vehicle”, Mathematical Modeling and Simulation of Systems, International scientific-practical conference, Springer International Publishing, Cham, pp. 197–206, doi: https://doi.org/10.1007/978-3-030-25741-5_20
Kane, S., Moody, V. and Harradon, M. (2021), “Towards Incorporating AI into the Mission Planning Process”, International Conference on Human-Computer Interaction, Springer International Publishing, Cham, pp. 216–228, doi: https://doi.org/10.1007/978-3-030-77772-2_14
Akcakoca, M., Bilge, M.A., Basak, G., Sinan, O., Umut, D., Mustafa, D., Emre, S., Burak, Y., Emre, K., Ramazan, Y. and Gokhan, I. (2019), “A simulation-based development and verification architecture for micro UAV teams and swarms”, AIAA Scitech 2019 Forum, pp. 1–12, doi: https://doi.org/10.2514/6.2019-1979
Furrer, F., Burri M., Achtelik, M. and Siegwart, R. (2016), “Rotors-a modular gazebo mav simulator framework”, Robot Operating System (ROS), The Complete Reference, Vol. 1, pp. 595-625, doi: https://doi.org/10.1007/978-3-319-26054-9_23
Kovalenko, A., Kuchuk, H., Kuchuk, N. and Kostolny, J. (2021), “Horizontal scaling method for a hyperconverged network”, International Conference on Information and Digital Technologies 2021, IDT 2021, pp. 331–336, 9497534, doi: https://doi.org/10.1109/IDT52577.2021.9497534
Kuchuk, N., Mozhaiev, O., Mozhaiev, M. and Kuchuk, H. (2017), “Method for calculating of R-learning traffic peakedness”, 2017 4th International Scientific-Practical Conference Problems of Infocommunications Science and Technology, PIC S and T 2017 – Proceedings, pp. 359–362, doi: https://doi.org/10.1109/INFOCOMMST.2017.8246416
Kovalenko, A. and Kuchuk, H. (2022), “Methods to Manage Data in Self-healing Systems”, Studies in Systems, Decision and Control, Vol. 425, pp. 113–171, doi: https://doi.org/10.1007/978-3-030-96546-4_3
Bittar, A., Figuereido, H.V., Guimaraes, P.A. and Mendes, A.C. (2014), “Guidance software-in-the-loop simulation using X-plane and simulink for UAVs”, 2014 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 993–1002, doi: https://doi.org/10.1109/ICUAS.2014.6842350
Meola, D., Iannelli, L. and Glielmo, L. (2013), “Flight control system for small-size unmanned aerial vehicles: Design and software-in-the-loop validation”, 21st Mediterranean Conference on Control and Automation, pp. 357–362, doi: https://doi.org/10.1109/MED.2013.6608746
Podorozhniak, A., Liubchenko, N., Kvochka, M. and Suarez, I. (2021), “Usage of intelligent methods for multispectral data processing in the field of environmental monitoring”, Advanced Information Systems, Vol. 5, No. 3, pp. 97–102, doi: https://doi.org/10.20998/2522-9052.2021.3.13,
Fontaine, S. and Johnson, E. (2001), “Using flight simulation to complement flight testing of low-cost UAVs”, AIAA Modeling and Simulation Technologies Conference and Exhibit, p. 1–6, doi: https://doi.org/10.2514/6.2001-4059
Dakhno, N., Barabash, O., Shevchenko, H., Leshchenko, O. and Dudnik, A. (2021), “Integro-differential Models with a K-symmetric Operator for Controlling Unmanned Aerial Vehicles Using an Improved Gradient Method”, "Actual Problems of Unmanned Aerial Vehicles Development (APUAVD), 2021 IEEE 6th International Conference Proceedings, October 19–21, Kyiv, Ukraine, pp. 61– 65, doi: https://doi.org/10.1109/APUAVD53804.2021.9615431
Barabash, O., Dakhno, N., Shevchenko, H. and Sobchuk, V. (2019), “Unmanned Aerial Vehicles Flight Trajectory Optimization on the Basis of Variational Enequality Algorithm and Projection Method”, Actual Problems of Unmanned Aerial Vehicles Developments (APUAVD), Proceedings 2019 IEEE 5th International Conference, 22-24 October, National Aviation University, Kyiv, Ukraine, pp. 136–139, doi: https://doi.org/10.1109/APUAVD47061.2019.8943869