Preview

Mekhatronika, Avtomatizatsiya, Upravlenie

Advanced search

Fuzzy Model of Situational Control of the Flight Parameters of an Autonomous Unmanned Aircraft under Uncertainty Conditions

https://doi.org/10.17587/mau.22.650-659

Abstract

The article outlines the main problems of automatic planning of the behavior of an autonomous unmanned aerial vehicle in unstable air conditions. It is shown that the urgency of the problem is due to the fact that an autonomous unmanned aerial vehicle independently forms and implements its flight route without support from a ground control station. There is therefore a need to develop a method for automatic control of programmed movements associated with the implementation of the route constructed by the problem solver. To solve this problem we propose an approach to regulating the parameters of the state of dynamic objects based on the principle of situational control of the goal-directed behavior of complex systems in changing environmental conditions. The expediency of choosing this control principle is due to the fact that the state of an autonomous unmanned aerial vehicle during its flight is characterized by a large number of parameters and disturbing environmental factors. In order to effectively implement this control principle, we introduce the concept of a complete problematic situation, which consists of deviations of the state parameters of an autonomous unmanned aerial vehicle from the required values during flight and disturbing environmental factors. On this basis, a fuzzy model of situational control of the state parameters of an autonomous unmanned aerial vehicle functioning in an unstable environment is developed, in which linguistic variables and functions are used to provide a generalized presentation of reference problem situations, as well as to describe the deviations of the state parameters and disturbing environmental factors. The conditions are determined under which the reference indistinctly presented problem situations generalize the actual problem situations that arise at the control object. This makes it possible to significantly reduce the number of logical-transformational decision rules in the situational control model and to promptly automatically determine effective control actions in problematic situations that ensure the effective implementation of programmed movements of an autonomous unmanned aerial vehicle under conditions of uncertainty. In conclusion, it is shown that for the implementation of control actions which are selected on a situational basis with increased requirements for the accuracy of regulation of the time-varying parameters of the control object and a significant level of possible discrepancies between their actual and specified values in conditions of uncertainty, it is advisable to use indistinctly implemented proportional, integral and differential regulation laws.

About the Authors

V. B. Melekhin
Dagestan State Technical University
Russian Federation

Melekhin Vladimir B., D. Sc., Professor

Makhachkala, 367015



M. V. Khachumov
Federal research center "Computer Science and Control" Russian Academy of Sciences; Program Systems Institute of the Russian Academy of Sciences
Russian Federation

Moscow, 117312; Veskovo, 152021



References

1. Merino L., Martinez-de-dios JR., Ollero A. Cooperative Unmanned Aerial Systems for Fire Detection, Monitoring, and Extinguishing. Handbook of Unmanned Aerial Vehicles. Springer, 2014, pp. 2693—2722.

2. Sergeev A. A., Filimonov A. B., Filimonov N. B. Control of autonomous landing of aircraft-type UAVs on static and dynamic landing sites along "flexible" kinematic trajectories. Mekhatronika, Avtomatizatsiya, Upravlenie, 2021, vol. 22, no. 3, pp. 156—167 (in Russian).

3. Melekhin V. B., Hachumov M. V. Planning the route of a purposeful flight of an autonomous aircraft at low altitude under conditions of uncertainty, Aviakosmicheskoe Priborostroenie, 2018, no. 1, pp. 18—27 (in Russian).

4. Melekhin V. B., Hachumov M. V. On one approach to solving the traveling salesman problem for planning an autonomous unmanned aerial vehicle of target fly-over routes, Bulletin of the Dagestan State Technical University. Technical science, 2021, vol. 48, no. 1, pp. 106—115 (in Russian)

5. Lebedev G. N., Efimov A. V. The use of dynamic programming for routing overflights of mobile objects in the controlled region, Bulletin of the Samara State Aerospace University, 2011, no. 6, pp. 234—241 (in Russian)

6. Ligo Tan’, Fomichyov A. V. Planning the spatial route of unmanned aerial vehicles using partial integer linear programming methods, Bulletin of the Moscow State Technical University named after N. E. Bauman. Ser. Instrumentation, 2016, no. 2, pp. 53—66 (in Russian).

7. Melekhin V. B., Hachumov M. V. Planning by an autonomous unmanned aerial vehicle of effective routes of overflights of targets, Aviakosmicheskoe priborostroenie, 2020, no. 4, pp. 3—14 (in Russian).

8. CHernyj M. A., Korablin V. I. Air navigation, Moscow, Transport, 1991, 432 p. (in Russian).

9. Moiseev V. S. Fundamentals of the theory of effective use of unmanned aerial vehicles, Kazan’, SHkola, 2015, 444 p. (in Russian).

10. Rysdyk R. Unmanned Aerial Vehicle path following for target observation in wind, Journal of Guidance, Control, and Dynamics, 2006, vol. 29, no. 5, pp. 1092—1100.

11. Veremeenko K. K., ZHeltov S. Yu., Kim N. G., Serebryakov G. G., Krasil’nikov M. N. Modern information technologies in the tasks of navigation and guidance of unmanned maneuverable aircraft, Moscow, Fizmatlit, 2009, 554 p. (in Russian).

12. Pospelov D. A. Situational management: theory and practice, Moscow, Nauka, 1986, 288 p. (in Russian).

13. Filimonov A. B., Filimonov N. B. Situational approach in the tasks of automation of management of technical objects, Mekhatronika, Avtomatizatsiya, Upravlenie, 2018, vol. 19, no. 9, pp. 562—578 (in Russian).

14. Melekhin V. B., Hachumov V. M. Management of effective implementation of technological processes of mechanical processing of parts in mechanical engineering, Problems of Management, 2020, no. 1, pp. 71—82 (in Russian).

15. Zade L. The concept of a linguistic variable and its application for making approximate decisions. Moscow, Mir, 1976, 168 p. (in Russian).

16. Passino K. M., Yurkovich S. Fuzzy Control, Boston (USA), Addison Wesley Longman, 1998, 522 p.

17. Melihov A. N., Bershtejn L. S., Korovin S. Ya. Situational advising systems with fuzzy logic, Moscow, Nauka, 1990, 272 p. (in Russian).

18. Abduragimov T. T., Melekhin V. B., Hachumov V. M. Information-analytical model of a fuzzy PID controller, Bulletin of the Dagestan State Technical University, Technical science, 2017, vol. 44, no. 1, pp. 48—60 (in Russian).


Review

For citations:


Melekhin V.B., Khachumov M.V. Fuzzy Model of Situational Control of the Flight Parameters of an Autonomous Unmanned Aircraft under Uncertainty Conditions. Mekhatronika, Avtomatizatsiya, Upravlenie. 2021;22(12):650-659. (In Russ.) https://doi.org/10.17587/mau.22.650-659

Views: 544


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


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