Estimation of Angles of Attack and Sideslip of Unmanned Aerial Vehicle in the Absence of Aerodynamic Angle Sensors
https://doi.org/10.17587/mau.22.274-280
Abstract
A method for estimating aerodynamic angles in the absence of appropriate sensors is proposed, using measurements of three projections of flight speed carried out by the navigation system and the values of the orientation angles. The relevance of the problem being solved is determined by the fact that on unmanned aerial vehicles (UAVs) sensors of aerodynamic angles, that is, angles of attack and slip, are often not installed due to restrictions on dimensions and mass. The proposed method is based on the joint use of mathematical models of aircraft motion, known from flight dynamics, and the theory of parametric identification of dynamic systems. The key factor ensuring the accuracy of the proposed method is the use of very accurate measurements of three UAV velocity projections performed by a satellite navigation system or an inertial navigation system with satellite correction. To account for the influence of wind, parametric identification of three projections of wind speed is provided. Another feature of the method is that instead of the missing aerodynamic angle sensors, it is proposed to use information about the aerodynamic coefficients of the lifting and lateral forces of the UAV. If these coefficients are known with errors, their values are also specified by identification methods. The dimension of the identification problem turns out to be low in the range of small and medium angles of attack when the aerodynamic dependencies are linear. The results of testing the proposed method based on simulation data on the flight test bench of a modern training aircraft for nine different flight modes under conditions of simulating random errors of onboard measurements corresponding to the flight experiment are presented.
Supporting agencies: This work was supported by the Russian Foundation for Basic Research (RFBR), project 20-08-00449.
About the Authors
O. N. Korsun
State Research Institute of Aviation Systems; Moscow Aviation Institute (NRU)
Russian Federation
Russian Federation
Korsun Oleg N., Dr. Sc., Professor, Head of Laboratories
Moscow, 125319
Moscow, 125993
A. I. Daneko
Moscow Aviation Institute (NRU)
Russian Federation
Russian Federation
Moscow, 125993
P. A. Motlich
Main Scientific Metrological Center
Russian Federation
Russian Federation
Mytishi, 141006
M. H. Om
Moscow Aviation Institute (NRU)
Russian Federation
Russian Federation
Moscow, 125993
References
1. Efremov A. V., Zakharchenko V. F., Ovcharenko V. N. et al. Flight dynamics: Textbook for students of higher educational institutions, Moscow, Mechanical Engineering, 2011, 776 p. (in Russian).
2. Vasilchenko K. K., Leonov V. A., Pashkovsky I. M., Poplavsky B. K. Flight tests of aircrafts, Moscow, Mashinostroenie, 1993 (in Russian).
3. Albokrinova A. S., Grumonds V. T. Flight dynamics of an unmanned plan-ning aircraft at low speeds and attitudes, Vestnik Moskovskogo aviacionnogo institute, 2017, vol. 24, no. 2, pp. 79—85 (in Russian).
4. Avgustov L. I., Babichenko A. V. et al. Aircraft navigation in near Earth space, Moscow, Nauchtekhlitizdat, 2015, 592 p. (in Russian).
5. Klein V., Morelli E. Aircraft System Identification. Theory and Practice. Reston, AIAA, 2006, 484 p.
6. Korsun O. N., Poplavsky B. K. Approaches for flight tests aircraft param-eter identification, 29th Congress of the International Council of the Aero-nautical Sciences, ICAS 2014, 2014—0210.
7. Jategaonkar R. V. Flight vehicle system identification: A time domain methodology, Reston, AIAA, 2006, 534 p.
8. Ovcharenko V. N. Aircraft aerodynamic parameters: flight data identification, Moscow, LENAND, 2019, 236 p. (in Russian).
9. Chowdhary G., Jategaonkar R. Aerodynamic parameter estimation from flight data applying extended and unscented Kalman filter, Aerospace Science and Technology, 2010, vol. 14, pp. 106—117.
10. Kachanov B. O., Kulabukhov V. S., Tuktareva N. A. Algorithm of a free-form aircraft orientation system with correction of measurements of inertial sensors based on satellite navigation system data, Datchiki i Sistemi, 2020, no. 11 (252), pp. 3—11 (in Russian).
11. Bulgakov V. V., Korsun O. N., Kulabukhov V. S., Stulovskii A. V., Timofeev D. S. Algorithms of increasing the calculation accuracy for an aircraft’s orientation angle, Journal of Computer and Systems Sciences International, 2016, vol. 55, no. 1, pp. 150—161.
12. Korsun O. N., Nikolaev S. V., Pushkov S. G. Algorithm for estimating systematic measurement errors for air velocity, angles of attack, and sliding angle in flight testing, Journal of Computer and Systems Sciences International, 2016, vol. 55, no. 3, pp. 446—457.
13. Korsun O. N., Motlich P. A. Estimation of on-board measurement errors based on the equations of motion of the aircraft, Vestnik Metrologa, 2020, no. 2, pp. 7—10 (in Russian).
14. Kyaw Zin Latt, Moung Htang Om. Development of wind velocity estimation method using the airspeed, Vestnik Moskovskogo aviacionnogo instituta, 2018, vol. 25, no. 2, pp. 152—159.
15. Korsun O. N., Om M. H., Latt K. Z. Determination of wind velocity projections taking into account measurements of airspeed, angle of attack and sideslip, Mekhatronika, Avtomatizatsiya, Upravlenie, 2021, vol. 22, no. 10, pp. 553—560 (in Russian).
16. Kulifeev Yu. B., Kulikov V. E. Formation of a spatial mathematical model of the effects of atmospheric turbulence on the flight of an aircraft, Trudi MIEA. Navigatsia i upravlenie letatelnimi apparatami, 2017, no. 18, pp. 13—34 (in Russian).
17. Korsun O. N., Motlich P. A. Integrated control of onboard measurements of the main flight parameters of an aircraft, Nauka i Obrazovanie: Nauchnoe izdanie Moskovskogo gosudarstvennogo tekhnicheskogo universiteta im. Baumana, 2013, no. 1, pp. 135—148 (in Russian).
18. Nikolaev S. V., Zhidelev A. V. Estimation of the reliability of the results of modeling the processes of functioning of aviation complexes, Aviakosmicheskoe Priborostroyenie, 2019, no. 5, pp. 26—33 (in Russian).
19. Nikolaev S. V. Method of simulation modeling in flight tests of aviation complexes, Prikladnaya Fizika i Matematika, 2017, no. 3, pp. 57—68 (in Russian).
20. Kulabukhov V. S. А general principle of isomorphism: integration of regulator and observer in the control system, IOP Conference Series: Materials Science and Engineering. 2019 Workshop on Materials and Engineering in Aeronautics, 2020, 012013.
21. Kulifeev Yu. B., Mironova M. M. Optimization of the trajectory of descent of a heavy unmanned aerial vehicle at the stage of full landing, Mekhatronika, Avtomatizatsiya, Upravlenie, 2016, vol. 17, no. 1, pp. 67—72 (in Russian).
22. Khachumov M., Khachumov V. Аrchitecture and mathematical support of intelligent control system for small UAV, 2019 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2019, 2019, 8742975.
23. Khachumov M., Khachumov V. Models for periodic task scheduling based on combining data processing cycles to support the onboard navigation and control system of a UAV, 2019 International Siberian Conference on Control and Communications, SIBCON 2019 — Proceedings, 2019, 8729581.
24. Korsun O. N., Gerilovich I. V., Om M. H. Atmospheric properties estimation for comparing aircraft simulated motion and the flight test data, Vestnik MGTU im. Baumana. Seria Priborastroeniya, 2021, no. 4, pp. 152—168 (in Russian).
Review
For citations:
Korsun O.N., Daneko A.I., Motlich P.A., Om M.H. Estimation of Angles of Attack and Sideslip of Unmanned Aerial Vehicle in the Absence of Aerodynamic Angle Sensors. Mekhatronika, Avtomatizatsiya, Upravlenie. 2022;23(5):274-280. (In Russ.) https://doi.org/10.17587/mau.22.274-280
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