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Отказоустойчивое управление групповым полетом мультикоптеров

https://doi.org/10.17285/0869-7035.0064

Аннотация

В статье для решения задачи оперативной оптимизации в процессе распределенного управления строем гексакоптеров без лидера используется алгоритм управления искусственным пчелиным роем, наилучший в глобальном смысле (Gbest-Guided Artificial Bee Colony – GABC, АУПР-ГЛ). АУПР-ГЛ обеспечивает оптимизацию целевой функции для каждого агента при приближении гексакоптера к заданной точке и обходе препятствий и других беспилотных летательных аппаратов (БПЛА). Показано, что он может конкурировать с другими применяемыми бионическими алгоритмами, например оптимизации роя частиц (Particle Swarm Optimization – PSO, ОРЧ). Представлены методы отказоустойчивого управления, которые протестированы на разных сценариях, в частности для случая потери агентов и отказа актюаторов в строе. Результаты демонстрируют, что предлагаемые методы отказоустойчивого управления способны минимизировать влияние отказов на конечную задачу строя БПЛА.

Об авторах

M. Слим
Американский университет Бейрута (Ливан), Ливанский университет (Хадат, Ливан)
Ливан

Слим Малак. Аспирант, Американский университет Бейрута (Ливан); Научно-исследовательский центр приборостроения, факультет приборостроения, Ливанский университет (Хадат, Ливан). 



M. Сайед
Ливанский университет (Хадат, Ливан)
Ливан

Сайед Мадж. Доцент



Х. Мазех
Университетский колледж Матна (Бейрут, Ливан), Ливанский университет (Хадат, Ливан)
Ливан

Мазех Хусейн. Преподаватель



Х. Шраим
Ливанский университет (Хадат, Ливан)
Россия

Шраим Хасан. Декан



К. Франсис
Ливанский университет (Хадат, Ливан)
Россия

Франсис Кловис. Директор, Научно-исследовательский центр приборостроения



Список литературы

1. Shakhatreh, H., Sawalmeh, A., Al-Fuqaha, A., Dou, Z., Almaita, E., Khalil, I., Othman, N., Khreishah, A., and Guizani, M., Unmanned Aerial Vehicles (UAVs): A survey on civil applications and key research challenges, IEEE Access 7, 2019, pp. 48572-48634.

2. Sreenath, K. and Kumar, V., Dynamics, control and planning for cooperative manipulation of payloads suspended by cables from multiple quadrotor robots, in Robotics: Science and Systems, Berlin, 2013.

3. Franchi, A., Secchi, C., Ryll, M., Bulthoff, H., and Giordano, P., Shared control: Balancing autonomy and human assistance with a group of quadrotor UAVs, IEEE Robot. Autom. Mag., 2012, vol. 19, no. 3, pp. 57–68.

4. Ritz, R. and D’Andrea, R., Carrying a flexible payload with multiple flying vehicles, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan, 3-7 November 2013, pp. 3465–3471.

5. Jiang, Q. and Kumar, V., The inverse kinematics of cooperative transport with multiple aerial robots, IEEE Trans. Robot., 2013, vol. 29, no. 1, pp. 136–145.

6. Kushleyev, A., Kumar, V., and Mellinger, D., Towards a swarm of agile micro quadrotors, Proc. Robot., Sci. Syst., Sydney, NSW, Australia, 2012.

7. Michael, N., Fink, J., and Kumar, V., Cooperative manipulation and transportation with aerial robots, Proc. Robot., Sci. Syst., Seattle, WA, USA, 2009.

8. Dames, P. and Kumar, V., Autonomous localization of an unknown number of targets without data association using teams of mobile sensors, IEEE Trans. Autom. Sci. Eng., 2015, vol. 12, no. 3, pp. 850–864.

9. Saska, M. et al., Autonomous deployment of swarms of micro-aerial vehicles in cooperative surveillance, Proc. Int. Conf. Unmanned Aircraft Syst. (ICUAS), Orlando, FL, USA, 27-30 May 2014, pp. 584–595.

10. Hou, Z. and Fantoni, I., Interactive leader-follower consensus of multiple quadrotors based on composite nonlinear feedback control, IEEE Transactions on Control Systems Technology, 2018, vol. 26, no. 5, pp. 1732–1743.

11. Vasarheyli, G., Viragh, Cs., Somorjai, G., Tarcai, N., Szorenyi, T., Nepusz, T., and Viscek, T., Outdoor flocking and formation flight with autonomous aerial robots, Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, USA, 14–18 September 2014.

12. Scollig, A., Augugliaro, F., Lupashin, S., and D’Andrea, R., Synchronizing the motion of a quadcopter to music, IEEE International Conference on Robotics and Automation, Anchorage, AK, USA, May 3–8 2010, pp. 3355–3360.

13. Kushleyev, A., Mellinger, D., Powers, C., and Kumar, V., Towards a swarm of agile micro quadrotors, Autonomous Robots, 2013, vol. 35, no. 4, pp. 287–300.

14. Reynolds, C., Flocks, Herds, and Schools: A distributed behavioral model, Proc. of the 14th Annual Conference on Computer Graphics and Interactive Techniques, 1987, pp. 25–34.

15. Olfati-Saber, R., Flocking for multi-agent dynamic systems: algorithms and theory, IEEE Transactions on Automatic Control, 2007, vol. 51, pp. 863–868.

16. Antonelli, G., Arrichiello, F., and Chiaverini, S., Flocking for multirobot systems via the nullspace based behavioral control, Swarm Intelligence, 2010, vol. 4, no. 37.

17. Bellingham, J., Tillerson, M., Alighanbari, M., and How, J., Cooperative path planning for multiple UAVs in dynamic and uncertain environments, Proc. IEEE Conference on Decision and Control, Las Vegas, NV, USA, 2002.

18. Richards, A. and How, J., Aircraft trajectory planning with collision avoidance using mixed integer linear programming, Proc. IEEE American Control Conference, Anchorage, AK, USA, 2002.

19. Tanner, H., Jadbabaie, A., and Pappas, G., Flocking in fixed and switching networks, IEEE Transactions on Automatic Control, 2007, vol. 52, no. 5, pp. 863–868.

20. Bakule, L., Decentralized control: An overview, Annual Reviews in Control, 2008, vol. 32, no. 1, pp. 87–98.

21. Jovanovic, M., Modeling, analysis, and control of spatially distributed systems, PhD Thesis, University of California, Santa Barbara, 2004.

22. Brunet, L., Consensus-based auction approaches for decentralized task assignment, AIAA Guidance, Navigation and Control Conference and Exhibit, Honolulu, Hawaii, 2008.

23. Quin, J., and Yu, C., Cluster consensus control of generic linear multi-agent systems under directed topology with acyclic partition, Automatica, 2013, vol. 49, no. 9, pp. 2898–2905.

24. Belkadi, A., Ciarletta, L., and Theilliol, D., UAVs fleet control design using distributed particle swarm optimization: A leaderless approach, International Conference on Unmanned Aircraft Systems (ICUAS), Arlington, VA, USA, 2016.

25. Belkadi, A., Abaunza, H., Ciarletta, L., Castillo, P., and Theilliol, D., Distributed path planning for controlling a fleet of UAVs: Application to a team of quadrotors, IFAC-PapersOnline, 2017, vol. 50, no. 1, pp. 15983–15989.

26. Abdmouleh, Z., Gastli, A., Ben-Brahim, L., Haouari, M., and Al-Emadi, N., Review of optimization techniques applied for the integration of distributed generation from renewable energy sources, Renewable Energy, 2017, vol. 113, pp. 266–280.

27. Karaboga, D. and Basturk, B., Artificial Bee Colony (ABC) optimization algorithm for solving constrained optimization problems, Foundations of Fuzzy Logic and Soft Computing, Berlin: Springer-Verlag, 2007, pp. 789–798.

28. Bhattacharjee, P., Rakshit, P., Goswami, I., Konar, A., and Nagar, A., Muti-robot path-planning using artificial bee colony optimization algorithm, Proc. World Congress on Nature and Biologically Inspired Computing, Salamanca, Spain, 2011.

29. Soyinka, O. and Duan, H., Satellite formation keeping via chaotic artificial bee colony, Aircr. Eng. Aerosp. Technol., 2017, vol. 89, no. 2, pp. 246–256.

30. Zhou, B., Wang, W., and Ye, H., Cooperative control for consensus of multi-agent systems with actuator faults, Computers & Electrical Engineering, 2014, vol. 40, no. 7, pp. 2154–2166.

31. Saska, M., Krajnik., T., Vonasek, V., Kasl, Z., Spurny, V., and Preucil, L., Fault-tolerant formation driving mechanism designed for heterogeneous MAVs-UGVs groups, Journal of Intelligent & Robotic Systems, 2014, vol. 73, no. 1, pp. 603–622.

32. Belkadi, A., Conception de commande tolerante aux defauts pour les systemes multi-agents: application au vol en formation d’une flotte de vehicules autonomes aeriens, Ph.D. dissertation, University of Lorraine, France, 2017.

33. Diestel, R., Graph Theory. Graduate Texts in Mathematics, Heidelberg: SpringerVerlag, 2005, third edition.

34. Sanahuja, G., Castillo, P., and Sanchez, A., Stabilization of n integrators in cascade with bounded input with experimental application to a VTOL laboratory system, International Journal of Robust and Nonlinear Control, 2010, vol. 20, no. 10, pp. 1129–1139.

35. Lalitha, M., Reddy, N., and Reddy, V., Optimal DG placement for maximum loss reduction in radial distribution system using ABC algorithm, Int. J. Rev. Comput, 2010, vol. 3, pp. 44–52.

36. Zhu, G. and Knowg, S., Gbest-guided artificial bee colony algorithm for numerical function optimization, Applied Mathematics and Computation, 2010, vol. 217, no. 7, pp. 3166–3173.

37. Saied, M., Knaiber, M., Mazeh, H., Shraim, H., and Francis, C., BFA fuzzy logic based control allocation for fault-tolerant control of multirotor UAVs, The Aeronautical Journal, 2019, vol. 123, pp. 1356–1373.

38. Mazeh, H., Saied, M., Shraim, H., and Francis, C., Fault-tolerant control of an hexarotor unmanned aerial vehicle applying outdoor tests and experiments. IFAC-PapersOnline, 2018, vol. 51, no. 22, pp. 312–317.


Рецензия

Для цитирования:


Слим M., Сайед M., Мазех Х., Шраим Х., Франсис К. Отказоустойчивое управление групповым полетом мультикоптеров. Гироскопия и навигация. 2021;29(2):78-96. https://doi.org/10.17285/0869-7035.0064

For citation:


 M.S., Saied M., Mazeh H., Shraim H., Francis C. Fault-Tolerant Control Design for Multirotor UAVs Formation Flight. Gyroscopy and Navigation. 2021;29(2):78-96. https://doi.org/10.17285/0869-7035.0064

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ISSN 0869-7035 (Print)
ISSN 2075-0927 (Online)