Applying fuzzy logic for developing simulation model of pilot's control actions

Dynamics, ballistics, movement control of flying vehicles


Аuthors

Vereshchikov D. V.*, Voloshin V. A., Ivashkov S. S.**, Vasil'ev D. V.

MESC Air Force “Air Force Academy named after professor N.E. Zhukovskii and Yu.A. Gagarin”, 54a, Starykh bol'shevikov, Voronezh, 394064, Russia

*e-mail: vdvikt@yandex.ru
**e-mail: ivashkov.sereja@yandex.ru

Abstract

Wide application of mathematical and in-line simulation modelling became vital and almost uncontested method of modern aircraft developing and trial. It allows reduce the amount of test flights and increase the informativity of conditions, as well as reduce degree of risk of flight experiment. Thus, one of primal problems is security of the obtained results adequacy. Adequacy of the simulation modelling results is ensured by application of Authentic mathematical models of aerial vehicles and Participation of the pilot-operator, as a obligatory link in the system “Pilot-Control system-aircraft” with its intrinsic behavior. However, the problems occur when it becomes necessary to perform a set of a target problem modelling of piloting to obtain statistically authentic results. As a result, the statistical data obtaining becomes a rather labor-consuming problem, requiring considerable amount of resources and time. Solution of this problem consists in developing authentic “pilot-operator” model.

At present, many works on creation of models of the pilot’s operations with subsequent simulation modelling are fulfilled. With up-to-date approaches to such models development it is possible to refer to:

− quasilinear models;

− theory of fuzzy sets and fuzzy logic;

− artificial neural webs;

− genetic algorithms.

Any quasi-linear model is understood as a model in which the relation between the input and output signals retains linear properties. Such model allows solving only single-loop single-channel problem. Thus, it is successfully employed, mainly, for the analysis of control systems. However, in real flight the pilot solves a multiple-loop multi-channel problem, and his responses to an input perturbing signal are of non-linear character, and, besides, apart from a linear component, “trail” component is also present among the pilot’s operations. Thus, the quasi-linear model is not capable to describe precisely enough the character of pilot’s operations, and it can be employed only for a narrow circle of problems. Artificial neural websnetworks and genetic algorithms are devoid of these shortages. However, in turn, they are complicated enough in the realization.

Keywords:

fuzzy logic, membership function, Matlab@Simulink, Fuzzy Logic Toolbox package, pilot’s actions model, optimization, fuzzy model, training sample, optimization target function

References

  1. Efremov A.V., Ogloblin A.V., Predtechenskii A.N., Rodchenko V.V. Letchik kak dinamicheskaya sistema (Pilot as a dynamic system), Moscow, Mashinostroenie, 1992, 336 p.

  2. Efremov A.V. Sistema samolet-letchik. Zakonomernosti i matematicheskie modeli povedeniya letchika (Aircraft-pilot system. Regularities and mathematical models of pilot’s behavior), Moscow, Izd-vo MAI, 2017, 196 p.

  3. Byushgens G.S., Studnev R.V. Aerodinamika samoleta: Dinamika prodol’nogo i bokovogo dvizheniya (Aircraft aerodynamics: Longitudinal and lateral movement dynamics), Moscow, Mashinostroenie, 1979, 352 p.

  4. McRuer D. T., Krendel E. S. Mathematical Models of Human Pilot Behavior, AGARD AG-188, 1974, 72 p.

  5. Jirgl M., Jirgl M., Bradac Z. Models of pilot behavior and their use to evaluate the state of pilot training, Journal of Electrical Engineering, 2016, vol. 67, no. 4, pp. 267 – 272.

  6. Suzuki S. Analysis of human pilot control inputs using neural network, Application Interrupt and Reset Control Register, 2006, vol. 43, no. 3, pp. 793 – 798.

  7. Vinogradov S.S. Trudy MAI, 2014, no. 73, available at: http://trudymai.ru/eng/published.php?ID=48562

  8. Chicherova E.V. Trudy MAI, 2015, no. 81, available at: http://trudymai.ru/eng/published.php?ID=57812

  9. Zadeh L. Fuzzy logic = Computing with words, IEEE Transactions on Fuzzy Systems, 1996, vol. 4, no. 2, pp. 169 – 239.

  10. Shtovba S.D. Proektirovanie nechetkikh sistem sredstvami MATLAB (Fuzzy systems design in MATLAB), Moscow, Goryachaya liniya – Telekom, 2007, 288 p.

  11. Shevri F., Geli F. Nechetkaya logika. Tekhnicheskaya kollektsiya Schneider Electric, (Fuzzy logic. Schneider Electric Engineering collection), 2009, no. 31, available at: http://netkom.by/docs/N31-Nechetkaya-logika.pdf

  12. Zade L. Ponyatie lingvisticheskoi peremennoi i ee primenenie k prinyatiyu priblizhennykh reshenii (Linguistic variable concept and its application to approximate decisions making), Moscow, Mir, 1976, 167 p.

  13. Rotshtein A.P., Shtovba S.D. Kibernetika i sistemnyi analiz, 2002, no. 5, pp. 169 – 176.

  14. Fuzzy Controllers, Theory and Applications. Edited by Dr. Lucian Grigorie, InTech, 2011, 368 p.

  15. Kostin P.S., Vereshchagin Yu.O., Voloshin V.A. Trudy MAI, 2015, no. 81, available at: http://trudymai.ru/eng/published.php?ID=57735

  16. Vereshchikov D.V., Majatsky S.А., Kostin P.S., Vereschagin Y.O., Grasko T.V. Patent na poleznuyu model’ SU 156567, 15.10.2014.

  17. Voloshin V.A., Vereshchikov D.V. Vos’maya Vserossiiskaya konferentsiya molodykh uchenykh i spetsialistov “Budushchee mashinostroeniya Rossii”. Sbornik dokladov, Moscow, MGTU im. N.E. Baumana, 23 −26.sentyabrya 2015, pp. 799 – 801.

  18. Leonenkov A.V. Nechetkoe modelirovanie v srede MATLAB i fuzzyTECH (Fuzzy modelling in MATLAB and fuzzyTECH), Saint-Petersburg, BKhV-Peterburg, 2005, 736 p.

  19. Terano T., Asai K., Sugeno M. Prikladnye nechetkie sistemy (Applied fuzzy systems), Moscow, Mir, 1993, 368 p.

  20. Izmailov A.F. Chislennye metody optimizatsii (Numerical optimisation methods), Moscow, Fizmatlit, 2008, 320 p.

  21. Shtovba S.D. Matematika v prilozheniyakh, 2003, no. 2 (2), pp. 9 – 15.

  22. Takagi T., Sugeno M., Fuzzy identification of systems and its applications to modeling and control, IEEE Transactions on Systems, Man and Cybernetics, 1985, vol. SMC-15, no. 1, pp. 116 – 132.


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