Mathematical model of a generalized quadcopter kinematic scheme and its software implementation
- Autores: Zelenskiy V.A.1, Kovalev M.A.1, Ovakimyan D.N.1, Kirillov V.S.1
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Afiliações:
- Samara National Research University, Samara, Russian Federation
- Edição: Volume 23, Nº 1 (2024)
- Páginas: 7-20
- Seção: AIRCRAFT AND SPACE ROCKET ENGINEERING
- URL: https://journal-vniispk.ru/2542-0453/article/view/311443
- DOI: https://doi.org/10.18287/2541-7533-2024-23-1-7-20
- ID: 311443
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Resumo
A generalized kinematic scheme of the installation of quadcopter motors is presented and its main advantages are described. In accordance with the scheme, a mathematical model of the kinematics of the quadcopter was developed. The model was implemented in the MatLab software environment. The presented mathematical expressions are used to calculate kinematic characteristics, such as the values of the thrust of the motors and the reverse effect of the motors on the body of the quadcopter. The comparison of the obtained data with the experimental characteristics showed a 5% deviation of the magnitude of the dependence of the thrust on the average value of the voltage on the motors and a 30% deviation of the magnitude of the dependence of the motor action on the thrust magnitude.
Sobre autores
V. Zelenskiy
Samara National Research University, Samara, Russian Federation
Autor responsável pela correspondência
Email: zelenskiy.va@ssau.ru
Doctor of Science (Engineering), Associate Professor, Professor of the Department of Radio Electronic Systems
RússiaM. Kovalev
Samara National Research University, Samara, Russian Federation
Email: kovalev.ma@ssau.ru
Doctor of Science (Engineering), Associate Professor, Professor of the Department of Aircraft Maintenance
RússiaD. Ovakimyan
Samara National Research University, Samara, Russian Federation
Email: ovakimyan.dn@ssau.ru
Director of the Center for Unmanned Systems
RússiaV. Kirillov
Samara National Research University, Samara, Russian Federation
Email: vskirilov2015@yandex.ru
Researcher of the Center for Unmanned Systems
RússiaBibliografia
- Kovalev M.A., Zelenskiy V.A., Ovakimyan D.N., Starostina T.V. UAV's autonomous navigation principe based on Earth remote sensing data. Proceedings of the 8th IEEE International Conference on Information Technology and Nano-technology, ITNT 2022 (May, 23-27, 2022, Samara, Russian Federation). doi: 10.1109/ITNT55410.2022.9848603
- Alhaddad M. Modeling and attitude control of a quadcopter using linear quadratic regulator. Materialy XII Mezhdunarodnoy nauchno-prakticheskoy konferentsii «Aktual'nye Problemy Aviatsii i Kosmonavtiki» (April, 15-16, 2016, Krasnoyarsk). V. 1. Krasnoyarsk: Siberian State Aerospace University Publ., 2016. P. 883-886. (In Russ.)
- Kuznetsov A.G. Automation of process of landing of the small-sized unmanned aerial vehicle in special situations. Trudy MAI. 2011. No. 45. (In Russ.)
- Saied M., Knaiber M., Mazeh H., Shraim H., Francis C. BFA fuzzy logic based control allocation for fault-tolerant control of multirotor UAVs. The Aeronautical Journal. 2019. V. 123, Iss. 1267. P. 1356-1373. doi: 10.1017/aer.2019.58
- Savelyev V.M., Antonov D.A. Strapdown inertial navigation system in-flight alignment for unmanned aircraft on the moving base. Trudy MAI. 2011. No. 45. (In Russ.)
- Sukhomlinov D.V., Medved A.N. Data integration in the aircraft information control system. Engine. 2014. No. 5 (95). P. 38-41. (In Russ.)
- Dolgiy O.V., Zhih A.I., Grishchenko V.A. Sensor fusion in navigation systems based on inertial elements. Scientific Horizons. 2019. No. 4 (20). P. 193-198. (In Russ.)
- Losev V.V., Kornilov A.V. A fusion of the measurement data from the inertial unit and the air data computer system being a part of the integrated standby instrument system. Bulletin of the Volga State Academy of Water Transport. 2017. No. 52. P. 31-39. (In Russ.)
- Yu G., Morel J.-M., ASIFT: An algorithm for fully affine invariant comparison. Image Processing On Line. 2011. V. 1. P. 11-38. doi: 10.5201/ipol.2011.my-asift
- Gasparyan O.N., Darbinyan H.G., Simonyan T.A. The control of quadcopters based on the feedback linearization method. Proceedings of NPUA. Information Technologies, Electronics, Radio Engineering. 2020. No. 2. P. 44-54.
- Yol A., Delabarre B., Dame A., Dartois J.-E., Marchand E. Vision-based absolute localization for unmanned aerial vehicles, intelligent robots and systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (September, 14-18, 2014, Chicago, IL, USA). 2014. doi: 10.1109/iros.2014.6943040
- Buslaev A., Seferbekov S., Iglovikov V., Shvets A. Fully convolutional network for automatic road extraction from satellite imagery. IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (June, 18-22, 2018, Salt Lake City, UT, USA). 2018. doi: 10.1109/cvprw.2018.00035
- Fowers S.G. Stabilization and control of a quad-rotor micro-UAV using vision sensors. Dissertations. Brigham Young University, 2008.
- Saeedi M., Trentini M., Seto M., Li H. Multiple-robot simultaneous localization and mapping: A review. Journal of Field Robotics. 2016. V. 33, Iss. 1. P. 3-46. doi: 10.1002/rob.21620
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