Mathematical model and optimization of helicopter vertical takeoff considering operational conditions and aerodynamic damping


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Abstract

A mathematical model of helicopter vertical takeoff was created. The model takes into account operating conditions and individual performance capabilities of a given helicopter. An optimization technique based on a genetic algorithm was introduced. The influence of mass, initial height and outside air temperature on the parameters of the optimal control law in case of vertical takeoff of Mi-8MT helicopter was estimated.

About the authors

Yu. P. Onushkin

Branch of Air Force Academy, Syzran

Author for correspondence.
Email: onushkin163@gmail.com

Candidate of Science (Engineering),
Professor of the Department of Aerodynamics and Flight Dynamics

Russian Federation

D. A. Sizov

Branch of Samara State Technical University, Syzran

Email: sizov.syzran@gmail.com

Candidate of Science (Engineering),
Associate Professor of the Department of Engineering Mechanics

Russian Federation

V. A. Poluyakhtov

Branch of Air Force Academy, Syzran

Email: halfboat@mail.ru

Candidate of Science (Engineering),
Associate Professor of the Department of Aerodynamics and Flight Dynamics

Russian Federation

A. V. Ostrovoy

Center of sci-tech services “Dinamika”, Zhukovsky

Email: dinamika@dinamika-avia.ru

Candidate of Science (Engineering),
executive director

Russian Federation

References

  1. Schmitz F.H. Optimal Takeoff Trajectories of a Heavily Loaded Helicopter. Journal of Aircraft. 1971. V. 8, Iss. 9. P. 717-723. doi: 10.2514/3.59162
  2. Cerbe T., Reichert G. Optimization of helicopter takeoff and landing. Journal of Aircraft. 1989. V. 26, Iss. 10. P. 925-931. doi: 10.2514/3.45863
  3. Okuno Y., Kawachi K. Optimal Takeoff of a Helicopter for Category A V/STOL Operations. Journal of Aircraft. 1993. V. 30, Iss. 2. P. 235-240. doi: 10.2514/3.48271
  4. Zhao Y., Jhemi A.A., Chen R.T.N. Optimal Vertical Takeoff and Landing Helicopter Operation in One Engine Failure. Journal of Aircraft. 1996. V. 33, Iss. 2. P. 337-346. doi: 10.2514/3.46943
  5. Phillips C., Karr C., Walker G. Helicopter Flight Control with Fuzzy Logic and Genetic Algorithms. Engineering Applications of Artificial Intelligence. 1996. V. 9, Iss. 2. P. 175-184. doi: 10.1016/0952-1976(95)00008-9
  6. Goldberg D.E. Genetic Algorithms in Search, Optimization and Machine Learning. Boston: Addison-Wesley Publishing Company, 1989. 432 p.
  7. Bottasso C.L., Croce A., Leonello D., Riviello L. Optimization of critical trajectories for rotorcraft vehicles. Journal of the American Helicopter Society. 2005. V. 50, Iss. 2. P. 165-177. doi: 10.4050/1.3092853
  8. Auzyak A.G., Budin V.I., Dremov F.V. Mathematical modeling of an optimal controlled helicopter flight at vertical regimes. Russian Aeronautics. 2010. V. 53, Iss. 1. P. 26-32. doi: 10.3103/s1068799810010046
  9. Instruktsiya ekipazhu vertoleta Mi-8MT. Kniga 1 [Helicopter Mi-8MT. Operating Procedures. V. 1]. Moscow: Voenizdat Publ., 1982. 440 p.
  10. Instruktsiya ekipazhu vertoleta Mi-24V. Kniga 1 [Helicopter Mi-24V. Operating Procedures. V. 1]. Moscow: Voenizdat Publ., 1987. 311 p.
  11. Rukovodstvo poletnoy ekspluatatsii vertoleta Mi-26T. Kniga 1 [Helicopter Mi-26T. Flight Manual. V. 1]. Moscow: Ministerstvo Grazhdanskoy Aviatsii SSSR Publ., 1988. 402 p.
  12. Mikhailov S.A., Onushkin A.Yu. Power balance method in calculation of helicopter maneuverability taking into account specific operational conditions. Russian Aeronautics. 2007. V. 50, Iss. 2. P. 121-128. doi: 10.3103/s106879980702002x
  13. Deb K. An efficient constraint handling method for genetic algorithms. Computer Methods in Applied Mechanics and Engineering. 2000. V. 186, Iss. 2-4. P. 311-338. doi: 10.1016/s0045-7825(99)00389-8

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