Issues of choosing the architecture of the automatic control system of a convertible unmanned aerial vehicle – a tiltrotor


DOI: 10.34759/trd-2021-120-16

Аuthors

Apollonov D. V., Bibikova K. I.*, Gavrilova A. V.*, Shibaev M. V.

Central Aerohydrodynamic Institute named after N.E. Zhukovsky (TsAGI), 1, Zhukovsky str., Zhukovsky, Moscow Region, 140180, Russia

*e-mail: ccfstd@tsagi.ru

Abstract

The relevance of the research issue lies in the need to check and adjust algorithms of aviation systems at each stage of their development. In connection with the expansion of the application scope of aircraft developed by PJSC laquo;Sukhoi Companyraquo;, a need arises to solve the problem of geometry optimization in joint hydraulic and thermal calculations. For this purpose, special software complexes are being employed that allow replacing real complex systems structures with structural schemes in the form of blocks, i.e. mathematical models that fully describe these systemsrsquo; structures. Practice has shown that, along with the existing methods for technical condition monitoring of the air cooling system (SVO) as part of a prospective unmanned aerial vehicle (UAV), there is a necessary to perform automated monitoring of the trend of product parameters during flight tests [1]. Let us consider how the method applied in the presented article will affect economic efficiency on the example of a PJSC laquo;Sukhoi Companyraquo; prospective unmanned aerial vehicle (UAV). The insurance cost of the aircraft equals to 1.3 billion rubles, the insurance cost of the ground control point of a promising UAV is designated at 145 million rubles. Thus, the total price of the manufactured goods is 1.445 billion rubles [1]. The price is determined based on the cost recovery principle, where no more than 20% is the cost of the head contractorrsquo;s work. In summary we get the price of the goods produced of 1.445 million rubles, and the cost of the goods produced of 290 million rubles (20% of 1.445 billion rubles) [2]. To achieve this goal, the following tasks were identified and solved by the implementation and development of the algorithms SVO in the SimInTech PC, which allowed improving the efficiency of the workflow and eliminating system shortcomings. The structure of the SVO mathematical model building in the SimInTech PCSVO is a complex-branched network of pipelines, including various units such as heat exchangers, dampers, dehumidifiers, check valves, overpressure sensors and temperature sensors. Calculation of such systems manually or with the state-of-the-artn computational fluid dynamics software systems requires significant computational resources and labor intensity. Due to the laquo;Set conditionsraquo; block, various situations of electric fans operation (EV) are modeled, which ultimately allows apprehending of the system behavior in the situation being considered. It offers the possibility to simulate failure situations and timely detect and eliminate the system weaknesses. The method for creating the SVO mathematical model, which includes the physical processes, occurring in the system, and control algorithms, allows developing the basics for solving the problem of reliable control of the technical condition of the SVO as part of a promising UAV during operation. It allows as well detecting malfunctions occurrence, preventing thereby the irreversible process of the system destruction. The three considered cases of the SVO functioning simulation clearly demonstrate that application of the proposed method of working out allows identify the system operation shortcomings and increase the workflow efficiency.

Keywords:

unmanned aerial vehicle, helicopter, mathematical model, system of automatic control, quaternion

References

  1. Gessou A., Meiers I.G. Aerodinamika vertoleta (Aerodynamics of the helicopter), Moscow, Gosudarstvennoe izdatelrsquo;stvo oboronnoi promyshlennosti, 1954, 254 p.

  2. Kozhevnikov V.A. Avtomaticheskaya stabilizatsiya vertoleta (Automatic stabilization of Helicopter), Moscow, Mashinostroenie, 1977, 152 p.

  3. Esaulov S.Yu., Bakhov O.P., Dmitriev I.S. Vertolet kak obquot;ekt upravleniya (Helicopter as object of control), Moscow, Mashinostroenie, 1977, 191 p.

  4. Troshin I.S., Monashev V.M. Sistemy upravleniya i stabilizatsii vertoleta (Helicopter control and stabilization systems), Moscow, MAI, 1979, 116 p.

  5. Troshin I.S. Dinamika poleta vertoleta (Helicopter flight dynamics), Moscow, MAI, 1990, 189 p.

  6. Ignatkin Yu.M., Makeev P.V., Shomov A.I. Trudy MAI, 2016, no. 87. URL: http://trudymai.ru/eng/published.php?ID=65636

  7. A.R.S. Bramwell, George Done, David Balmford. Bramwellrsquo;s Helicopter Dynamics, Butterworth-Heinemann, Oxford OX2 8DP, UK, 2001, 373 p.

  8. Ignatkin Yu.M., Makeev P.V., Shomov A.I. Trudy MAI, 2010, no. 38. URL: http://trudymai.ru/eng/published.php?ID=14148

  9. Ignatkin Yu.M., Konstantinov S.G. Trudy MAI, 2012, no. 57. URL: http://trudymai.ru/eng/published.php?ID=30874

  10. Ivchin V.A. Nauchnyi vestnik MGTU GA, 2008, no. 125, pp. 54-63.

  11. Abdur Rasheed. Helicopter Attitude Control, International Conference on Computing, Mathematics and Engineering Technologies, 2018. DOI:10.1109/ICOMET.2018.8346421

  12. Ali Mortuza Munna, Md. Nazrul Islam, A. M. Azad, AKM Ferdous. Analysis of Stability and Control of Helicopter Flight Dynamics Through Mathematical Modeling in Matlab, Conference: 2020 IEEE Region 10 Symposium (TENSYMP), 2020. DOI:10.1109/TENSYMP50017.2020.9230900

  13. Shenrsquo;ao Yan, Weihong Wang, Sentang Wu, Ke Lu. Flight Dynamics Model of Helicopter Based on Simulink, Proceedings of the 36th Chinese Control Conference, 2017. DOI:10.23919/ChiCC.2017.8027696

  14. Danilov V.A. Vertolet Mi-8. Ustroistvo i tekhnicheskoe obsluzhivanie (Mil-8 helicopter. Construction design and maintenance), Moscow, Transport, 1988, 278 p.

  15. Marc D. Takahashi, Brian T. Fujizawa, Jeffery A. Lusardi, Matthew S. Whalley. Autonomous Guidance and Flight Control on a Partial-Authority Black Hawk Helicopter, AIAA Aviation 2020 Forum, 2020. DOI:10.2514/6.2020-3286

  16. Borisov E.A., Leontrsquo;ev V.A., Rubinshtein M.A., Rusakov I.V. Trudy MAI, 2018, no. 99. URL: http://trudymai.ru/eng/published.php?ID=91924

  17. Leontrsquo;ev V.A. Uchenye zapiski TsAGI, 2010, vol. 41, no. 5, pp. 67-80.

  18. Chelnokov Yu.N. Kvaternionnye i bikvaternionnye modeli i metody mekhaniki tverdogo tela i ikh polozheniya. Geometriya i kinematika dvizheniya (Quaternions and Bi-quaternions model and solid body mechanics methods and principles. Geometry kinematics), Saratov, Saratovskii natsionalrsquo;nyi issledovatelrsquo;skii gosudarstvennyi universitet imeni N.G. Chernyshevskogo, 2006, 236 p.

  19. Satoshi Suzuki, Kenzo Nonami. Quaternion-based Navigation and Control for Small Unmanned Helicopter, Conference: Automatic Control in Aerospace, 2010, vol. 43 (15), pp. 37-42. DOI:10.3182/20100906-5-JP-2022.00008

  20. Satoshi Suzuki, Daisuke Nakazawa, Kenzo Nonami, Makoto Tawara. Attitude Control of Small Electric Helicopter by Using Quaternion Feedback, Journal of System Design and Dynamics, 2011, vol. 5, no. 2. DOI:10.1299/jsdd.5.231


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