Design of a neuro-sliding mode controller for interconnected quadrotor UAVs carrying a suspended payload

Özhan Bingöl; Haci Mehmet Güzey

Kybernetika (2023)

  • Volume: 59, Issue: 5, page 670-699
  • ISSN: 0023-5954

Abstract

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In this study, a generalized system model is derived for interconnected quadrotor UAVs carrying a suspended payload. Moreover, a novel neural network-based sliding mode controller (NSMC) for the system is suggested. While the proposed controller uses the advantages of the robust structure of sliding mode controller (SMC) for the nonlinear system, the neural network component eliminates the chattering effects in the control signals of the SMC and increases the efficiency of the SMC against time-varying dynamic uncertainties. After the controller design is carried out, a comprehensive stability analysis based on Lyapunov theory is given to assure the asymptotic stability of the system. Finally, extensive numerical simulations with detailed comparisons are used to verify the effectiveness of the proposed controller.

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Bingöl, Özhan, and Güzey, Haci Mehmet. "Design of a neuro-sliding mode controller for interconnected quadrotor UAVs carrying a suspended payload." Kybernetika 59.5 (2023): 670-699. <http://eudml.org/doc/299167>.

@article{Bingöl2023,
abstract = {In this study, a generalized system model is derived for interconnected quadrotor UAVs carrying a suspended payload. Moreover, a novel neural network-based sliding mode controller (NSMC) for the system is suggested. While the proposed controller uses the advantages of the robust structure of sliding mode controller (SMC) for the nonlinear system, the neural network component eliminates the chattering effects in the control signals of the SMC and increases the efficiency of the SMC against time-varying dynamic uncertainties. After the controller design is carried out, a comprehensive stability analysis based on Lyapunov theory is given to assure the asymptotic stability of the system. Finally, extensive numerical simulations with detailed comparisons are used to verify the effectiveness of the proposed controller.},
author = {Bingöl, Özhan, Güzey, Haci Mehmet},
journal = {Kybernetika},
keywords = {autonomous UAV; interconnected system; neuro-sliding mode control; payload transportation},
language = {eng},
number = {5},
pages = {670-699},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Design of a neuro-sliding mode controller for interconnected quadrotor UAVs carrying a suspended payload},
url = {http://eudml.org/doc/299167},
volume = {59},
year = {2023},
}

TY - JOUR
AU - Bingöl, Özhan
AU - Güzey, Haci Mehmet
TI - Design of a neuro-sliding mode controller for interconnected quadrotor UAVs carrying a suspended payload
JO - Kybernetika
PY - 2023
PB - Institute of Information Theory and Automation AS CR
VL - 59
IS - 5
SP - 670
EP - 699
AB - In this study, a generalized system model is derived for interconnected quadrotor UAVs carrying a suspended payload. Moreover, a novel neural network-based sliding mode controller (NSMC) for the system is suggested. While the proposed controller uses the advantages of the robust structure of sliding mode controller (SMC) for the nonlinear system, the neural network component eliminates the chattering effects in the control signals of the SMC and increases the efficiency of the SMC against time-varying dynamic uncertainties. After the controller design is carried out, a comprehensive stability analysis based on Lyapunov theory is given to assure the asymptotic stability of the system. Finally, extensive numerical simulations with detailed comparisons are used to verify the effectiveness of the proposed controller.
LA - eng
KW - autonomous UAV; interconnected system; neuro-sliding mode control; payload transportation
UR - http://eudml.org/doc/299167
ER -

References

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  1. Altug, E., Ostrowski, J. P., Taylor, C. J., , Int. J. Rob. Res. 24 (2005), 5, 329-341. DOI
  2. Bingöl, Ö., Güzey, H. M., , Adv. Robot. 35 (2021), 3-4, 255-266. DOI
  3. Bingöl, Ö., Güzey, H.-M., , Drones 6 (2022), 10, 311. DOI
  4. Bingöl, ., Güzey, H. M., , European J. Control 73 (2023), 100879. MR4612244DOI
  5. Bisgaard, M., Cour-Harbo, A. la, Dimon Bendtsen, J., Adaptive control system for autonomous helicopter slung load operations., Control Eng. Pract., 2010. 
  6. Bouabdallah, S., Murrieri, P., Siegwart, R., , In: Proc. IEEE International Conference on Robotics and Automation, ICRA'04, IEEE 2004. Vol. 5, pp. 4393-4398. DOI
  7. Chen, Y., Chen, H., , Kybernetika 59 (2023), 2, 273-293. MR4600378DOI
  8. Cruz, P. J., Oishi, M., Fierro, R., , In: Proc. Am. Control Conf. 2015, pp. 1887-1892. DOI
  9. Dhiman, K. K., Kothari, M., Abhishek, A., , J. Aerosp. Inf. Syst. 17 (2020), 8, 417-435. DOI
  10. Dierks, T., Jagannathan, S., Output feedback control of a quadrotor UAV using neural networks., IEEE Trans. Neural Networks 2010. 
  11. Ertugrul, M., Kaynak, O., , Mechatronics 10 (2000), 1-2, 239-263. DOI
  12. Faust, A., Palunko, I., Cruz, P., Fierro, R., Tapia, L., 10.1016/j.artint.2014.11.009, Artif. Intell. 2017. DOI10.1016/j.artint.2014.11.009
  13. Frikha, S., Djemel, M., Derbel, N., , Int. J. Control Autom. Syst. 16 (2018), 2, 559-565. DOI
  14. Gassner, M., Cieslewski, T., Scaramuzza, D., Dynamic collaboration without communication: Vision-based cable-suspended load transport with two quadrotors., In: Proc. IEEE Int. Conf. Robot. Autom. 2017, pp. 5196-5202. 
  15. Geng, J., Langelaan, J. W., , J. Guid. Control. Dyn. 43 (2020), 7, 1313-1331. DOI
  16. Grzonka, S., Grisetti, G., Burgard, W., , IEEE Trans. Robot. 28 (2012), 1, 90-100. DOI
  17. Guo, K., Jia, J., Yu, X., Guo, L., Xie, L., , Control Eng. Pract. 102 (2019), 104560. DOI
  18. Hoffmann, G., Huang, H., Waslander, S., Tomlin, C., Quadrotor helicopter flight dynamics and control: Theory and experiment., In: AIAA Quidance, Navigation and Control Conference and Exhibit 2007, p. 6461. 
  19. Hou, Z., Lu, P., Tu, Z., , Aerosp. Sci. Technol. 98 (2020), 105716. DOI
  20. Hwangbo, J., Sa, I., Siegwart, R., Hutter, M., , IEEE Robot. Autom. Lett. 2 (2017), 4, 2096-2103. DOI
  21. Jiang, Q., Kumar, V., , IEEE Trans. Robot. 29 (2013), 1, 136-145. DOI
  22. Slotine, J. J., Sastry, S. S., 10.1080/00207178308933088, Int. J. Control 38 (1083), 2, 465-492. MR0714077DOI10.1080/00207178308933088
  23. Lee, T., Leok, M., Mcclamroch, N. B., , Asian J. Control 15 (2013), 2, 391-408. MR3043449DOI
  24. Lei, R., Chen, L., , Kybernetika 57 (2021), 1, 160-173. MR4231862DOI
  25. Levant, Arie, , Automatica 43 (2007), 4, 576-586. MR2306701DOI
  26. Lewis, F. L., Neural network control of robot manipulators., IEEE Expert. Syst. their Appl. 1996. 
  27. Li, G., Ge, R., Loianno, G., , IEEE Robot. Autom. Lett. 6 (2021), 3, 5316-5323. DOI
  28. Lim, H., Park, J., Lee, D., Kim, H. J., Build your own quadrotor: Open-source projects on unmanned aerial vehicles., 2012. 
  29. Liu, Z., Liu, X., Chen, J., Fang, Ch., , IEEE Access 7 (2019), 9736-9744. DOI
  30. Noordin, A., Basri, M. A. M., Z.Mohamed, Mat Lazim, I., , Arab. J. Sci. Engrg. 46 (2021), 2, 963-981. DOI
  31. Palunko, I., Fierro, R., Cruz, P., , In: Proc. IEEE Int. Conf. Robot. Autom.,2012, pp. 2691-2697. DOI
  32. Pizetta, I. Henrique Beloti, Brandao, A. S., Sarcinelli-Filho, M., Modelling and control of a PVTOL quadrotor carrying a suspended load., In: Int. Conf. Unmanned Aircr. Syst. ICUAS 2015. 
  33. Plestan, F., Glumineau, A., Laghrouche, S., , Int. J. Robust Nonlinear Control 18 (2008), 4-5, 441-453. MR2392133DOI
  34. Pounds, P., Mahony, R., Corke, P., , Control Eng. Pract. 18 (2010), 7, 691-699. DOI
  35. Qian, Ch., Lin, W., , Syst. Control Lett. 42 (2001), 3, 185-200. MR2007048DOI
  36. Rossomando, F., Rosales, C., Gimenez, J., Salinas, L., Soria, C., Sarcinelli-Filho, M., Carelli, R., , J. Intell. Robot. Syst. Theory Appl. 100 (2020), 2, 519-530. DOI
  37. Shirani, B., Najafi, M., Izadi, I., , Aerosp. Sci. Technol. 84 (2019), 158-169. DOI
  38. Sreenath, K., Lee, T., Kumar, V., Geometric control and differential flatness of a quadrotor UAV with a cable-suspended load., In: 52nd IEEE Conf. Decis. Control, Vol. 2019, pp. 2269-2274. 
  39. Utkin, V. I., 10.1109/TAC.1977.1101446, IEEE Trans. Automat. Control 1977. MR0484664DOI10.1109/TAC.1977.1101446
  40. Vahdanipour, M., Khodabandeh, M., , Aerosp. Sci. Technol. 86 (2019), 737-747. DOI
  41. Villa, D. K. D., Brandão, A. S., Sarcinelli-Filho, M., , J. Intell. Robot. Syst. Theory Appl. 98 (2020), 2, 267-296. DOI
  42. Wang, J., Wang, F., Wang, X., Yu, L., , Kybernetika 55 (2019), 3, 586-603. MR4016000DOI
  43. Xiong, J. J., Zhang, G., Sliding mode control for a quadrotor UAV with parameter uncertainties., In: Proc. 2nd Int. Conf. Control. Autom. Robot. ICCAR 2016. MR3381053
  44. Yi, K., Gu, F., Yang, L., He, Y., Han, J., Sliding mode control for a quadrotor slung load system., In: Chinese Control Conf. CCC, 2017. 
  45. You, W., Li, F., Liao, L., Huang, M., , IEEE Access 8 (2020), 64971-64981. DOI
  46. Yu, G., Cabecinhas, D., Cunha, R., Silvestre, C., , IEEE/ASME Trans. Mechatronics 24 (2019), 5, 2304-2315. DOI
  47. Zhang, Ch., Li, S., Ding, S., Finite-time output feedback stabilization and control for a quadrotor mini-aircraft., Kybernetika 48 (2012), 2, 206-222. Zbl1246.93119MR2954321
  48. Zhou, B., Pan, J., Gao, F., Shen, S., , IEEE Trans. Robot. 37 (2021), 6, 1992-2009. DOI
  49. Zhou, X., Liu, R., Zhang, J., Zhang, X., , In: Proc. ASME Des. Eng. Tech. Conf. 2016. DOI

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