Preview

Mekhatronika, Avtomatizatsiya, Upravlenie

Advanced search

Planning the Number of Aircraft in a Group Flight with their Survivability and the Required Observation Duration of Ground Objects

https://doi.org/10.17587/mau.23.430-439

Abstract

In the interests of improving the quality of a group aircraft flight planning, the developing algorithms problem formulation for the operational determination of the permissible observation duration for ground objects is formulated. An algorithm for determining the observation duration when servicing the next request to be described in the form of a fuzzy logic procedure is proposed. To implement the algorithm for determining the duration of observation, a specialized expert system has been developed. The input of the expert system receives values that describe the influence of the factors in assessing the priority of servicing the next object. At the output of the expert system, an alternative is formed to continue searching for an object or to stop. A new approach to solving the target distribution problem between aircraft in a group flight is proposed. It is based on the joint use of two dynamic priorities in the minimax algorithm for selecting observation objects and for assigning service aircraft. An original approach to determine the rational aircrafts composition in one flight is proposed. This is done with the help of the queuing theory apparatus, which takes into account the random nature of the dynamic situation. To estimate the required aircrafts composition when servicing the flow of requests, the countermeasures process is described using two nonlinear differential equations (of the Riccati type). A general formula for determining aircrafts composition in one flight has been obtained. Mathematical model of the aircraft survivability loss in the form of the Bernoulli equation is formed. Computer simulation of the aircraft survivability losses in one flight was carried out for three cases: with weak interference, with equal opposing forces, with strong counteraction. 

About the Authors

V. I. Goncharenko
Moscow Aviation Institute (National Research University)
Russian Federation

Dr. of Eng. Sc., Associate Professor,

Moscow, 125993



G. N. Lebedev
Moscow Aviation Institute (National Research University)
Russian Federation

Moscow, 125993



D. A. Mikhaylin
Moscow Aviation Institute (National Research University)
Russian Federation

Moscow, 125993



V. B. Malygin
Moscow State Technical University of Civil Aviation
Russian Federation

Moscow



A. V. Rumakina
Moscow Aviation Institute (National Research University)
Russian Federation

Moscow, 125993



References

1. Kim N. V., Krylov I. G. Group use of an unmanned aerial vehicle in observation tasks, Proceedings of the MAI, 2012, no. 62, available at: http://mai.ru//upload/iblock/bbb/gruppovoe-primenenie-bespilotnogo-letatelnogo-apparata-v-zadachakh-nablyudeniya.pdf (date of access: 03.02.2021) (in Russian).

2. Evdokimenkov V. N., Krasilshchikov M. N., Kozorez D. A. Development of pre-flight planning algorithms for the functionalprogram prototype of a distributed intellectual control system of unmanned flying vehicle groups, INCAS Bulletin, 2019, vol. 11, no. 1, рр. 75—88.

3. Melekhin V. B., Khachumov M. V. Effective routes planning by an autonomous unmanned aerial vehicle of targets overflights, Aviakosmicheskoe priborostroenie, 2020, no. 4, рр. 3—14 (in Russian). 4. Ozlem Sahin Meric. Optimum Arrival Routes for Flight Efficiency, Journal of Power and Energy Engineering, 2015, no. 3, pp. 449—452.

4. Patent 02321954 USA MPK8 B 61 L 3/12 3/22, H 04 L1 / 00, H 04 Q 7/38 7/20. Intelligent communication, control, and monitoring system for land vehicles / Peltz D. M., Smith Yu.A., Kraeling M., Foy R. D., Peltonen G. P., Kellner S. E., Bryant R. F., Johnson DK, Delaruel DG; applicant and patentee General Electric Company. — no. 2004136603/09; declared from 01.04.2003; publ. 10.04.2008.

5. Rebrov V. A., Rudelson L. E., Chernikova M. A. A model of flight request collection and processing in the flight scheduling problem, Journal of Computer and Systems Sciences International, 2007, vol. 46, no. 3, pp. 429—443.

6. Sebryakov G. G., Krasilshchikov M. N., Evdokimenkov V. N. Algorithmic and software-mathematical support for pre-flight planning of unmanned aerial vehicles group actions, Fundamental problems of group interaction of robots: materials of the RFBR reporting event for the "ofi-m" competition (topic 604) within the framework of an international scientific and practical conference, Volgograd, 2018, pp. 30—32 (in Russian).

7. Nikolaev S. V. Determination in tests of detecting ground objects probability from the aircraft board, Scientific Bulletin of MSTU GA, 2017, vol. 20, no. 5, pp. 131—144 (in Russian).

8. Fomin A. N., Tyapkin V. N., Dmitriev D. D. et al. Theoretical and physical foundations of radar and special monitoring, Krasnoyarsk, Sib. Fed. un-ty, 2016, 292 p. (in Russian).

9. Lebedev G. N., Mirzoyan L. A. Neural network actions planning to fly over ground objects by a group of aircraft, Aviakosmicheskoe priborostroenie, 2005, no. 12, pp. 34—40 (in Russian).

10. Ivashova N. D., Mikhaylin D. A., Chernyakova M. E., Shanygin S. V. A neural network solution to the problem of operational route flight planning of unmanned aerial vehicles and the observation time ground objects appointment using fuzzy logic when displaying these results on a computer screen before departure, Proceedings of the MAI, 2019, no. 104, рр. 17 (in Russian).

11. Goncharenko V. I., Lebedev G. N., Martynkevich D. S., Rumakina A. V. Formulation of the problem of planning the routes of aircraft when servicing a random flow of incoming requests in flight, Bulletin of computer and information technologies, 2021, vol. 18, no. 1, pp. 17—27 (in Russian).

12. Zadeh L. A. Fuzzy sets, Information and Control, 1965, vol. 8, no. 3, рр. 338—353.

13. Zade L. The concept of a linguistic variable and its application to making approximate decisions, Moscow, Mir, 1976, 166 p. (in Russian).

14. Beloglazov D. A., Gaiduk A. R., Kosenko E. Yu. et al. Group control of mobile objects in uncertain environments, Moscow, Publishing company "Physical and mathematical literature" LLC, 2015, 305 p. (in Russian).

15. Eremin A. I., Kulchak A. M., Lebedev G. N., Selvesyuk N. I. Two-level intelligent system for preventing dangerous flight situations in difficult conditions, Informatics and Control Systems, 2020, no. 3 (65), pp. 87—101.

16. Evdokimenkov V. N., Krasilshchikov M. N., Orkin S. D. Mixed groups of manned and unmanned aerial vehicles control in a single information and control field, Moscow, MAI, 2015, 272 p. (in Russian).

17. Goncharenko V. I., Zheltov S. Yu., Knyaz V. A., Lebedev G. N., Mikhaylin D. A., Tsareva O. Yu. Intelligent System for Planning Group Actions of Unmanned Aircraft in Observing Mobile Objects on the Ground in the Specified Area, Journal of Computer and Systems Sciences International, 2021, vol. 60, no. 3, pp. 379—395.

18. Knyaz V., Zheltov S., Lebedev G., Mikhaylin D., Goncharenko V. Intelligent mobile object monitoring by unmanned aerial vehicles, Proceedings of the 18th IEEE International Conference on Smart Technologies, EUROCON 2019, 1—4 July, 2019 Novi Sad, Serbia, Publisher IEEE, New York, USA, 2019, pp. 1—6.

19. Goncharenko V. I., Lebedev G. N., Mikhaylin D. A., Nechaev V. V. The many sporting events shooting planning in a vast territory by a group of unmanned aerial vehicles, Modern information technologies and IT education, 2019, vol. 15, no. 3, рр. 651—660 (in Russian).

20. Mefyodov A. V. Algorithm for optimal target allocation of an autonomous attack unmanned aerial vehicles group, Information and Space, 2018, no. 3, pp. 167—171 (in Russian).

21. Broeder G. G., Ellison G. G., Emerling R. E. On Optimum Target Assignments, Operations Research, 1959, vol. 7, рр. 322—326.

22. Saati T. L. Elements of queuing theory and its applications, Moscow, Sov. radio, 1965, 510 p. (in Russian).

23. Verba V. S., Gandurin V. A., Merkulov V. I. Survivability of aviation complexes of radar patrol and guidance, Efficiency of radio control systems 2014, Book 2, рр. 112—118 (in Russian).

24. Moiseev V. S. Group application of unmanned aerial, Kazan, Shkola Editorial and Publishing Center, 2017, 572 p. (in Russian).

25. Isaacs R. Differential games, Moscow, Mir, 1967, 480 p. (in Russian). 27. Korepanov V. O., Novikov D. A. Strategic behavior models in the diffuse bomb problem, Control Problems, 2015, no. 2, pp. 38—44 (in Russian).

26. Kalyaev I. A., Gaiduk A. R., Kapustyan S. G. Collective control models and algorithms in groups of robot, Moscow, Publishing company "Physics and Mathematics Literature" LLC, 2009, 280 p. (in Russian).

27. Gaiduk A. R., Martjanov O. V., Medvedev M. Yu., Pshikhopov V. Kh., Hamdan N., Farhood A. Neural Network Based Control System for Robots Group Operating in 2-d Uncertain Environment, Mekhatronika, Avtomatizatsiya, Upravlenie, 2020, vol. 21, no. 8, pp. 470—479.

28. Person J. D. Approximation methods in optimal control, J. of Electronics and Contro, 1962, vol. 12, pp. 453—469.

29. Mrasek C. P., Clouter J. R. Control design for the nonlinear benchmark problem via sdre method, Int. J. of Robust and Nonlinear Control, 1998, vol. 8, pp. 401—433.

30. Menon P. K., Ohlmeyer E. J. Integrated Design of Angel Missile Guidance and Control Systems, Proc. 17th Mediterranean Conf. on Control and Automation (MED99). Haifa, Israel, June 28—30, 1999, pp. 1470—1494.


Review

For citations:


Goncharenko V.I., Lebedev G.N., Mikhaylin D.A., Malygin V.B., Rumakina A.V. Planning the Number of Aircraft in a Group Flight with their Survivability and the Required Observation Duration of Ground Objects. Mekhatronika, Avtomatizatsiya, Upravlenie. 2022;23(8):430-439. (In Russ.) https://doi.org/10.17587/mau.23.430-439

Views: 394


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1684-6427 (Print)
ISSN 2619-1253 (Online)