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Takeoff Monitoring Algorithm with Prediction

  • FLIGHT DYNAMICS AND CONTROL OF FLIGHT VEHICLES
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An Erratum to this article was published on 01 September 2020

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Abstract

A takeoff-monitoring algorithm is proposed that allows predicting the rate of an aircraft takeoff run and recognizing emergency situations that require reject the takeoff. The algorithm is based on combined use of a polynomial approximation of the dependence of the takeoff speed on time and the CUSUM test to detect abrupt changes in the dynamics of the aircraft. Mathematical modeling of the algorithm is presented using a model of a lightweight aircraft.

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REFERENCES

  1. Aviatsionnye pravila. Ch. 25. Normy letnoi godnosti samoletov transportnoi kategorii (Federal Aviation Regulations. Part 25. Airworthiness Standards: Transport Category Airplanes), Moscow: Aviaizdat, 2015.

  2. Xu, J., Overview of Certification of Aeroplane Takeoff and Landing Performance on Contaminated Runways, Proc. of the 2nd International Symposium on Aircraft Airworthiness, 2011, Beijing, vol. 17, pp. 13–23.

    Google Scholar 

  3. Brown, A.P. and Abbasi, H., Takeoff Performance Monitoring Systems, Technology, Certificatability and Operability Status, URL: https://nrc-publications.canada.ca/eng/view/fulltext/?id=0fa746bc-edb1-46f9-aa83-af93ee3b2d49.

  4. Aerospace Standard AS-8044. Takeoff Performance Monitor (TOPM) System, Airplane, Minimum Performance Standard for, URL: https://saemobilus.sae.org/content/AS8044.

  5. Glubokaya, M.G., The Current State of Solving the Take-Off Safety Problem, Iskusstvennyi Intellekt, 2005, no. 3, pp. 370–380.

    Google Scholar 

  6. Glubokaya, M.G., Method of Take-Off Monitoring by Means of Effective Take-Off Mass Function, Uchenye Zapiski TsAGI, 2009, vol. 40, no. 1, pp. 82–91 [TsAGI Science Journal (Engl. Transl.), vol. 40, no. 1, pp. 117–129].

    Google Scholar 

  7. Shevchenko, A.M., Pavlov, B.V., and Nachinkina, G.N., Method of Aircraft Takeoff Forecasting in the Presence of High-Altitude Obstacles, Izv. YuFU. Tekhnicheskie Nauki, 2012, no. 3 (128), pp. 167–172.

    Google Scholar 

  8. Zammit-Mangion, D., Design and Development of an Algorithm for a Take-off Performance Monitor, Cranfield: Cranfield University, 2001.

    Google Scholar 

  9. Brown, R.L., Durbin, J., and Evans, J.M., Techniques for Testing the Constancy of Regression Relationships over Time, Journal of the Royal Statistical Society, Series B, 1975, vol. 37, no. 2, pp. 149–192.

    MathSciNet  MATH  Google Scholar 

  10. Kotik, M.G., Dinamika vzleta i posadki samoletov (Dynamics of Aircraft Takeoff and Landing), Moscow: Mashinostroenie, 1984.

    Google Scholar 

  11. Efremov, A.V., Tyaglik, M.S., Irgaleev, I.Kh., and Gorbatenko, S.A., Predictive Information Design for the Novel Generation of Display for the Highly-Augmented Aircraft, Izv. Vuz. Av. Tekhnika, 2017, vol. 60, no. 2, pp. 87–92 [Russian Aeronautics (Engl. Transl.), vol. 60, no. 2, pp. 257–262].

    Google Scholar 

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ACKNOWLEDGEMENTS

This work was supported by the Russian Foundation for Basic Research grant no. 18-08-01045.

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Correspondence to V. I. Garkushenko.

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Garkushenko, V.I., Lazareva, P.A. Takeoff Monitoring Algorithm with Prediction. Russ. Aeronaut. 63, 222–229 (2020). https://doi.org/10.3103/S1068799820020063

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