Synthesis of the Blade Tip Optimal Control Laws for the Helicopter Main Rotor Spin-Up and Deceleration under Wind Conditions

Aeronautical and Space-Rocket Engineering


Аuthors

Kargaev M. V.1, 2*, Korsun O. N.3, 2

1. National Helicopter Center Mil & Kamov, 26/1, Garshina str., Tomilino, Moscow region, 140070, Russia
2. Moscow Aviation Institute (National Research University), 4, Volokolamskoe shosse, Moscow, А-80, GSP-3, 125993, Russia
3. State Research Institute of aviation systems, Moscow, Russia

*e-mail: kargaev_mv@mail.ru

Abstract

Depending on the speed and direction of the wind at the helicopter parking lot, originating while the main rotor (MR) spin-up and deceleration, deflections of the of the MR ends blades may reach significant values and lead to the blades hitting the helicopter tail boom or other elements of its structure, and even on the runway surface. Thus, the limit wind speed, which ensures sufficient clearance between the MR blades and other parts of its structure to prevent the blades from hitting the airframe elements of the helicopter in any expected operating conditions, is of practical significance for the helicopter operator.
To expand the range of wind speeds allowing the MR safe spin-up or deceleration, the article considers the option of applying individual control of the MR blades by gapless active tips. The idea of individual control of the MR blades is consistent with the concept of active aeroelasticity. The tips application as the MR blades individual control means is not enough studied, however, it is of theoretical and practical interest due to its expected effectiveness.
The presented article adduces a method for optimal control synthesizing of a gapless blade tip during the helicopter MR spin-up and deceleration under wind conditions. The control laws are being represented in the form of the spline approximations, which parameters are being found by solving the identification task by the maximum likelihood method through solving the optimization problem in a finite-dimensional space. The modified Newton's method is used as an optimization method, and linear splines are employed for the control laws approximation. The reference dependencies of the blades end displacements during the spin-up or deceleration of the MR (observation vector) are those that occur during spin-up or deceleration in the absence of wind at the helicopter parking lot.
The study of the gapless controlled tip effectiveness to compensate for wind disturbances of the model blade when spinning the MR in wind conditions was performed in relation to the Mi-171A3 type helicopter. The article demonstrates numerically the possibility of increasing the limit wind speed when spinning the MR of the above said helicopter from 18.6 m/s to 27 m/s (by 45%) due to application of the controlled gapless tip with the largest selected restriction on the maximum angle of its deflection.

Keywords:

main rotor blade, wind loading, spin-up and deceleration of the main rotor, controlled gapless tip, maximum likelihood method, control optimization, modified Newton's method

References

  1. Airworthiness standards of civil helicopters of the USSR. 2nd ed. Moscow: Mezhduvedomstvennaya komissiya po normam letnoi godnosti grazhdanskikh samoletov i vertoletov SSSR; 1987. 411 p. (In Russ.).
  2.  Interstate Aviation Committee. Civil Aviation Safety Regulations. Part 29. Airworthiness standards for rotorcraft in the transport category. Moscow: Aviaizdat; 2018. 185 p. (In Russ.).
  3.  Standards of airworthiness of rotorcraft of the NLG-29 transport category. Moscow: TSENTRMAG; 2024. 252 p. (In Russ.).
  4.  Kargaev MV. Calculation of joint bending and torsional oscillations of the blade during the spin-up and deceleration of the helicopter main rotor in wind conditions. Aerospace MAI Journal. 2024;31(4):101-112. (In Russ.). URL: https://vestnikmai.ru/eng/publications.php?ID=183588
  5.  Loads and actions. SR 20.13330.2016. Moscow: Standartinform; 2018. 95 p. (In Russ.).
  6.  Amir'yants GA, Grigor'ev AV. Computational and experimental studies of the controlled wing shape. Trudy TsAGI. 2023(2819):82-85. (In Russ.).
  7.  Amiryants G.A. Active Wing Tip. Patent RU 2787983 C1, 16.01.2023. (In Russ.).
  8.  Amir'yants GA, Zichenkov MCh, Kalabukhov SI. et al. Aeroelasticity. Moscow: Innovatsionnoe mashinostroenie, 2019. 650 p. (In Russ.).
  9.  Animitsa VA, Borisov AE, Kritsky BS. et al. Analysis of computational and experimental researches on systems for individual control of the blades of the helicopter. Trudy MAI. 2016(85). (In Russ.). URL: https://trudymai.ru/eng/published.php?ID=65452
  10.  Helicopters: Proceedings of the MVZ Design Bureau named after ML. Mil. Issue 2. Moscow: Mashinostroenie-Polet; 2012. 334 p. (In Russ.).
  11.  Helicopters: Proceedings of the MVZ Design Bureau named after ML. Mil. Issue 3. Moscow: Mashinostroenie-Polet; 2018. 327 p. (In Russ.).
  12.  Norris G, Wagner M. Boeing 787 Dreamliner. Osceola, Wisconsin: Zenith Press; 2009. 160 p.
  13.  Amiryants GA, Paryshev SE, Grigoriev AV. Aeroelastic properties of active winglets. 31st Congress of the International Council of the Aeronautical Sciences (ICAS 2018; 09–14 сентября 2018; Belo Horizonte, Brazil).
  14.  Korsun ON. Methods of parametric identification of technical systems. Moscow: Bauman Moscow State Technical University; 2011. 69 p. (In Russ.).
  15.  Jategaonkar RV. Flight vehicle system identification. A time domain methodology. USA, Reston: AIAA; 2006. 410 p.
  16.  Ovcharenko VN. Aerodynamic characteristics of aircraft: Identification from flight data. Moscow: LENAND; 2019. 236 p. (In Russ.).
  17.  Bulgakov VV, Korsun ON, Kulabukhov VS. et al. Algorithms for improving the accuracy of calculating aircraft orientation angles. Izvestiya RAN. Teoriya i sistemy upravleniya. 2016(1):159-170. (In Russ.). DOI: 10.7868/S0002338815050030
  18.  Karpenko AP. Modern search engine optimization algorithms. Algorithms inspired by nature. 3rd ed. Moscow: Bauman Moscow State Technical University; 2021. 449 p. (In Russ.).
  19.  Morelli E, Grauer J. Advances in Aircraft System Identification at NASA Langley Research Center. Journal of Aircraft. 2023;60(4):1354-1370. DOI: 10.2514/1.C037274
  20.  Wang Y, Dong J, Liu X. et al. Identification and standardization of maneuvers based upon operational flight data. Chinese Journal of Aeronautics. 2015;28(1):133-140. DOI: 10.1016/j.cja.2014.12.026
  21.  Rao AV. A Survey of Numerical Methods for Optimal Control. Advances in the Astronautical Sciences. 2010;135(1):497-582.
  22.  Korsun ON, Stulovskii AV. Restoration of aircraft motion parameters using optimal control algorithms. Izvestiya RAN. Teoriya i sistemy upravleniya. 2023(1):44-55. (In Russ.). DOI: 10.31857/S0002338823010055
  23.  Vermel' V.D. Fundamentals of computational (engineering) geometry. Moscow: Innovatsionnoe mashinostroenie; 2021. 352 p. (In Russ.).

mai.ru — informational site of MAI

Copyright © 1994-2025 by MAI