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Fuzzy Logic Controller Design for the Ground Collision Avoidance System (GCAS)

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Abstract

This article presents the design of an automatic ground collision avoidance system for the aircraft PZL-130 Orlik TCII. The project attempts at designing a fuzzy logic controller for generating control signals for the flight stick and the throttle depending upon four major input parametres (roll, pitch, indicated airspeed and rotation speed of the gas generator). The main task of the system is to properly manage energy and space orientation by the execution system - actuators which steer the lay of the control stick and the throttle. The project uses Matlab and Fuzzy Logic Toolbox software. The authors show performance of the system based on twenty samples for research, which simulate recovery from two dangerous situations. They present levels of steering the system, which facilitate its performance analysis, as well as the simulation process in the Simulink software package with the preset values.

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References

  1. Anderson, G.: Applying fuzzy logic in the real world. Reprinted with permission of Sensor magazine. Helmers Publishing. Inc. (1992), www.sensormag.com

  2. Azadeh, A., Ebrahimipour, V., Bavar, P.: A fuzzy inference system for pump failure diagnosis to improve maintenance process: the case of a petrochemical industry. Expert Syst. Appl. 37, 627–639 (2010)

    Article  Google Scholar 

  3. Baban, M., Baban, C.F., Blaga, F.S.: Maintenance planing of cold plastic deformation tools using fuzzy logic. Eksploatacja i Niezawodnosc - Maintenance Reliab. 3, 21–26 (2010). ISSN 1507-2711

    Google Scholar 

  4. Chaudhari, S., Patil, M.: Study and review of fuzzy inference systems for decision making and control. Am. Int. J. Res. Sci. Technol. Eng. Math. (2014). ISSN (Print): 2328–3491, ISSN (Online): 2328-3580, ISSN (CD-ROM): 2328-3629

    Google Scholar 

  5. Demirci, S., Hajiyev, Ch., Schwenke, A.: Fuzzy logic-based automated engine health monitoring for commercial aircraft. Aircr. Eng. Aerosp. Tech. 80(5), 516–525 (2008)

    Article  Google Scholar 

  6. Grzesik, N.: Podstawy sterowania rozmytego. Projektowanie rozmytych systemów eksperckich w środowisku Matlab-Simulink. Wyższa Szkoła Oficerska Sił Powietrznych (2012)

    Google Scholar 

  7. Hadjimichael, M.: A fuzzy expert system for aviation risk assessment. Expert Syst. Appl. 36(3), 6512–6519 (2009)

    Article  Google Scholar 

  8. Huang, H.-Z.: Structural reliability analysis using fuzzy sets theory. Eksploatacja i Niezawodnosc - Maintenance Reliab. 4, 284–294 (2012). ISSN 1507-2711

    Google Scholar 

  9. Jia, L., Edward, L.: Fuzzy Logic controllers for aircraft flight control. Fuzzy Logic Intell. Syst. Int. Ser. Intell. Technol. 3, 85–124 (1995)

    Google Scholar 

  10. Kacprzyk, J., Yager, R.R.: Emergency-Oriented expert systems: a fuzzy approach. Inf. Sci. 37(1), 143–155 (1985)

    Article  MATH  Google Scholar 

  11. Nho, K., Agarwal, R.K.: Automatic landing system design using fuzzy logic. J. Guid. Control Dyn. 23(2), 298–304 (2000)

    Article  Google Scholar 

  12. Lower, M., Magott, J., Skorupski, J.: Analiza incydentów lotniczych z zastosowaniem zbiorów rozmytych. Prace naukowe Politechniki Warszawskiej, Transport, Warszawa (2013)

    Google Scholar 

  13. Mamdani, E.H., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man Mach. Stud. 7(1), 1–13 (1975). doi:10.1016/S0020-7373(75)80002-2

    Article  MATH  Google Scholar 

  14. Pedrycz, W.: Fuzzy multimodels. IEEE Trans. Fuzzy Syst. 4(2), 139–148 (1996)

    Article  MathSciNet  Google Scholar 

  15. Giang, Phan H.: Decision making under uncertainty comprising complete ignorance and probability. Int. J. Approximate Reasoning 62, 27–45 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  16. Usta, M.A., Akyazi, O., Akpinar, A.S.: Aircraft roll control system using LQR and fuzzy logic controller. Innovations in Intelligent Systems and Applications (INISTA) (2011)

    Google Scholar 

  17. Nair, V.G., Dileep, M.V., Prahalad, K.R.: Design of fuzzy logic controller for lateral dynamics control of aircraft by considering the cross-coupling effect of yaw and roll on each other. Int. J. Comput. Appl. (0975–888) 47(13) (2012)

    Google Scholar 

  18. Żurek, J., Grzesik, N.: Fuzzy expert aircraft onboard control systems assistant. Safety reliability and risk analysis: Beyond the horizon. In: ESREL Conference Proceedings, pp. 250–251. Taylor & Francis Group, London (2013)

    Google Scholar 

  19. Dowództwo Sił Powietrznych Instrukcja użytkowania i techniki pilotowania samolotu PZL-130TCII Orlik. Ministerstwo Obrony Narodowej (2004)

    Google Scholar 

  20. National Aeronautics and Space Administration. https://www.nasa.gov/centers/armstrong/AutoGCAS_Installed_in_USAF_F16s.html

  21. https://www.youtube.com/watch?v=WkZGL7RQBVw

  22. https://pl.wikipedia.org/wiki/Lockheed_F-22_Raptor

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Correspondence to Konrad Kuźma .

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Mazur, K., Grzesik, N., Kuźma, K. (2018). Fuzzy Logic Controller Design for the Ground Collision Avoidance System (GCAS). In: Kacprzyk, J., Szmidt, E., Zadrożny, S., Atanassov, K., Krawczak, M. (eds) Advances in Fuzzy Logic and Technology 2017. EUSFLAT IWIFSGN 2017 2017. Advances in Intelligent Systems and Computing, vol 642. Springer, Cham. https://doi.org/10.1007/978-3-319-66824-6_44

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  • DOI: https://doi.org/10.1007/978-3-319-66824-6_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66823-9

  • Online ISBN: 978-3-319-66824-6

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