International Journal of Naval Architecture and Ocean Engineering

  • 제10권3호
  • /
  • Pages.282-293
  • /
  • 2018
  • /
  • 2092-6782(pISSN)
  • /
  • 2092-6790(eISSN)
대한조선학회 (The Society of Naval Architects of Korea)
권호 표지
DOI QR코드

DOI QR Code

Three-dimensional trajectory tracking for underactuated AUVs with bio-inspired velocity regulation

  • 투고 : 2016.10.04
  • 심사 : 2017.08.19
  • 발행 : 2018.05.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This paper attempts to address the motion parameter skip problem associated with three-dimensional trajectory tracking of an underactuated Autonomous Underwater Vehicle (AUV) using backstepping-based control, due to the unsmoothness of tracking trajectory. Through kinematics concepts, a three-dimensional dynamic velocity regulation controller is derived. This controller makes use of the surge and angular velocity errors with bio-inspired models and backstepping techniques. It overcomes the frequently occurring problem of parameter skip at inflection point existing in backstepping tracking control method and increases system robustness. Moreover, the proposed method can effectively avoid the singularity problem in backstepping control of virtual velocity error. The control system is proved to be uniformly ultimately bounded using Lyapunov stability theory. Simulation results illustrate the effectiveness and efficiency of the developed controller, which can realize accurate three-dimensional trajectory tracking for an underactuated AUV with constant external disturbances.

키워드

참고문헌

  1. Aguiar, A., Joao, P., 2007. Trajectory-tracking and path-following of under- actuated autonomous vehicles with parametric modeling uncertainty. IEEE Trans. Autom. Control 52 (8), 1362-1379. https://doi.org/10.1109/TAC.2007.902731
  2. Bi, F.Y., Wei, Y.J., Zhang, J.Z., Cao, W., 2010. Position-tracking control of underactuated autonomous underwater vehicles in the presence of un- known ocean currents. IET Control Theory Appl. 4 (11), 2369-2380. https://doi.org/10.1049/iet-cta.2009.0265
  3. Do, K.D., 2015. Control of fully actuated ocean vehicles under stochastic environmental loads in three dimensional space. Ocean Eng. 99, 34-43. https://doi.org/10.1016/j.oceaneng.2015.03.005
  4. Do, K.D., 2015. Robust adaptive tracking control of underactuated ODINs under stochastic sea loads. Robotics Aut. Syst. 2015 (72), 152-163.
  5. Do, K.D., Pan, J., 2009. Control of Ships and Underwater Vehicles: Design for Underactuated and Nonlinear Marine Systems. Springer, London, UK.
  6. Elmokadem, Taha, Zribi, Mohamed, Youcef-Toumi, Kamal, 2016. Trajectory tracking sliding mode control of underactuated AUVs. Nonlinear Dyn. 84 (2), 1079-1091. https://doi.org/10.1007/s11071-015-2551-x
  7. Fossen, Thor I., 2011. Handbook of Marine Craft Hydrodynamics and Motion Control. A John Wiley& Sons, Ltd., Publication.
  8. Fossen, T.I., Pettersen, K.Y., Galeazzi, R., 2015. Line-of-sight path following for Dubins paths with adaptive sideslip compensation of drift forces. IEEE Trans. Control Syst. Technol. 23 (2), 820-827. https://doi.org/10.1109/TCST.2014.2338354
  9. Grossberg, S., 1983. Absolute stability of global pattern formation and parallel memory storage by compective neural networks. IEEE Trans. Syst Man Cybern. 13 (5), 815-826.
  10. Grossberg, S., 1988. Nonlinear neural networks: principles, mechanisms, and architecture. Neural Netw. 1 (1), 17-61. https://doi.org/10.1016/0893-6080(88)90021-4
  11. He-ming, Jia, Li-jun, Zhang, Xiang-qin, Cheng, Xin-qian, Bian, Zhe- ping, Yan, Zhou, Jiajia, 2012. Three-dimensional path following control for an underactuated AUV based on nonlinear iterative sliding mode. Acta Autom. Sin. 38 (2), 308-314. https://doi.org/10.3724/SP.J.1004.2012.00308
  12. He-ming, Jia, Xiang-qin, Cheng, Li-jun, Zhang, Xin-qian, Bian, Zhe-ping, Yan, 2012. Three-dimensional path tracking control for under- actuated AUV based on adaptive backstepping. Control Decis. 27 (5), 652-664.
  13. Hodgkin, A.L., Huxley, A.F., 1952. A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol. 117 (4), 500-544. https://doi.org/10.1113/jphysiol.1952.sp004764
  14. Hong-Jian, Wang, Zi-Yin, Chen, He-Ming, Jia, Li, Juan, 2015. Three-dimen-sional path-following control of underactuated autonomous underwater vehicle with command filtered backstepping. Acta Autom. Sin. 41 (3), 631-645.
  15. Kim, Do Wan, 2015. Tracking of REMUS autonomous underwater vehicles with actuator saturations. Automatica 58, 15-21. https://doi.org/10.1016/j.automatica.2015.04.029
  16. Pan, Chang-Zhong, Lai, Xu-Zhi, Yang, Simon X., Wu, Min, 2013. An efficient neural network approach to tracking control of an autonomous surface vehicle with unknown dynamics. Expert Syst. Appl. 40, 1629-1635. https://doi.org/10.1016/j.eswa.2012.09.008
  17. Pettersen, K.Y., Egeland, O., 1999. Time-varying exponential stabilization of the position and attitude of an underactuated autonomous underwater vehicle. IEEE Trans. Autom. Control 44 (1), 112-115. https://doi.org/10.1109/9.739086
  18. Simon, X., Yang, T. Hu, 2002. An efficient neural network approach to real- time control of a mobile robot with unknown dynamics. Differ. Equ. Dyn. Syst. 1 (10), 151-168.
  19. Sun, Bing, Zhu, Daqi, Yang, Simon X., 2014. A bioinspired filtered back- stepping tracking control of 7000-m manned submarine vehicle. IEEE Trans. Ind. Electron. 61 (7), 3682-3693. https://doi.org/10.1109/TIE.2013.2267698
  20. Sun, Bing, Zhu, Daqi, Yang, Simon X., 2014. A bio-inspired cascaded approach for three-dimensional tracking control of unmanned underwater vehicles. Int. J. Robot. Automat. 29 (4), 349-358.
  21. Sun, Yu-shan, Ran, Xiang-rui, Li, Yue-ming, Zhang, Guo-cheng, Zhang, Ying-hao, 2016. Thruster fault diagnosis method based on Gaussian particle filter for autonomous underwater vehicles. Int. J. Nav. Archit. Ocean Eng. 8, 243-251.
  22. Xu, Jian, Wang, Man, Qiao, Lei, 2014. Backstepping-based controller for three-dimensional trajectory tracking of underactuated underwater vehicles. Control Theory Appl. 31 (11), 1589-1596.
  23. Yan, Zheping, Yu, Haomiao, Zhang, Wei, Li, Benyin, Zhou, Jiajia, 2015. Globally finite-time stable tracking control of underactuated AUVs. Ocean Eng. 107, 132-146. https://doi.org/10.1016/j.oceaneng.2015.07.039
  24. Yang, Simon X., Zhu, Anmin, Yuan, Guangfeng, Meng, Max Q.-H., 2012. A bioinspired neurodynamics-based approach to tracking control of mobile robots. IEEE Trans. Ind. Electron. 59 (8), 3211-3220. https://doi.org/10.1109/TIE.2011.2130491
  25. Zhou, Jiajia, Tang, Zhaodong, Zhang, Honghan, Jiao, Jianfang, 2013. Spatial path following for AUVs using adaptive neural network controllers. Math. Probl. Eng. 1-9.

피인용 문헌

  1. An Improved DSA-Based Approach for Multi-AUV Cooperative Search vol.2018, pp.None, 2018, https://doi.org/10.1155/2018/2186574
  2. Three-dimensional trajectory tracking control of an underactuated autonomous underwater vehicle with a robust adaptive algorithm vol.43, pp.2, 2018, https://doi.org/10.1139/tcsme-2018-0123
  3. Three-dimensional trajectory tracking of a hybrid autonomous underwater vehicle in the presence of underwater current vol.185, pp.None, 2018, https://doi.org/10.1016/j.oceaneng.2019.05.030
  4. Backstepping active disturbance rejection control for trajectory tracking of underactuated autonomous underwater vehicles with position error constraint vol.17, pp.2, 2018, https://doi.org/10.1177/1729881420909633
  5. Trajectory tracking sliding mode control for underactuated autonomous underwater vehicles with time delays vol.17, pp.3, 2018, https://doi.org/10.1177/1729881420916276
  6. Numerical Test of Several Controllers for Underactuated Underwater Vehicles vol.10, pp.22, 2020, https://doi.org/10.3390/app10228292
  7. Autonomous Underwater Robot Fuzzy Motion Control System with Parametric Uncertainties vol.5, pp.1, 2018, https://doi.org/10.3390/designs5010024
  8. New hybrid control of autonomous underwater vehicles vol.94, pp.11, 2018, https://doi.org/10.1080/00207179.2020.1749938