An Asymptotically Stable Identifier Design for Unmanned Surface Vehicles Based on Neural Networks and Robust Integral Sign of the Error

  • Shengnan Gao
  • Lu Liu
  • Zhouhua PengEmail author
  • Dan WangEmail author
  • Nan Gu
  • Yue Jiang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11555)


In this paper, a robust identifier is developed for unmanned surface vehicles (USVs) subject to uncertain dynamics. The uncertain dynamics comes from parametric model uncertainty and external ocean disturbance. The identifier for USV is designed based on Robust Integral Sign of the Error (RISE) and neural networks. With the proposed identifier, asymptotic stability of the estimation errors can be proven in the presence of parametric model uncertainties and external ocean disturbances. The proposed method can be used in a variety of practical settings such as trajectory tracking and formation control of marine vehicles for achieving better performance.


Neural networks Unmanned surface vehicle Derivative estimation Robust identification 


  1. 1.
    Fossen, T.: Handbook of Marine Craft Hydrodynamics and Motion Control. Wiley, Hoboken (2011)Google Scholar
  2. 2.
    Peng, Z., Wang, J., Wang, J.: Constrained control of autonomous underwater vehicles based on command optimization and disturbance estimation. IEEE Trans. Ind. Electron. 66(5), 3627–3635 (2019)Google Scholar
  3. 3.
    Peng, Z., Wang, J., Han, Q.: Path-following control of autonomous underwater vehicles subject to velocity and input constraints via neurodynamic optimization. IEEE Trans. Ind. Electron. (2019, in press).
  4. 4.
    Jin, K., Wang, H., Yi, H., Liu, J., Wang, J.: Key technologies and intelligence evolution of maritime UV. Chin. J. Ship Res. 13(6), 1–8 (2018)Google Scholar
  5. 5.
    Li, F., Yi, H.: Application of USV maritime safety superition. Chin. J. Ship Res. 13(6), 27–33 (2018)Google Scholar
  6. 6.
    Zhao, R., Xu, J., Xiang, X., Xu, G.: A review of path planning and coopreative control for MAUV systems. Chin. J. Ship Res. 13(6), 58–65 (2018)Google Scholar
  7. 7.
    Ashrafiuon, H., Muske, K.R., McNinch, L.C., Soltan, R.A.: Sliding-mode tracking control of surface vessels. IEEE Trans. Ind. Electron. 55(11), 4004–4012 (2008)Google Scholar
  8. 8.
    Cui, R., Zhang, X., Cui, D.: Adaptive sliding-mode attitude control for autonomous underwater vehicles with input nonlinearities. Ocean Eng. 123, 45–54 (2016)Google Scholar
  9. 9.
    Xiang, X., Yu, C., Zhang, Q.: Robust fuzzy 3D path following for autonomous underwater vehicle subject to uncertainties. Comput. Oper. Res. 84, 165–177 (2017)Google Scholar
  10. 10.
    Peng, Z., Wang, J., Wang, D.: Distributed maneuvering of autonomous surface vehicles based on neurodynamic optimization and fuzzy approximation. IEEE Trans. Control Syst. Technol. 26(3), 1083–1090 (2018)Google Scholar
  11. 11.
    Chen, M., Ge, S.S., How, B.V.E., Choo, Y.S.: Robust adaptive position mooring control for marine vessels. IEEE Trans. Control Syst. Technol. 21(2), 395–409 (2013)Google Scholar
  12. 12.
    Peng, Z., Wang, D.: Robust adaptive formation control of underactuated autonomous surface vehicles with uncertain dynamics. IET Control Theory Appl. 5(12), 1378–1387 (2011)Google Scholar
  13. 13.
    Bhasin, S., Kamalapurkar, R., Johnson, M., Vamvoudakis, K.G., Lewis, F.L., Dixon, W.E.: A novel actor-critic-identifier architecture for approximate optimal control of uncertain nonlinear systems. Automatica 49(1), 82–92 (2013)Google Scholar
  14. 14.
    Peng, Z., Wang, D., Chen, Z., Hu, X., Lan, W.: Adaptive dynamic surface control for formations of autonomous surface vehicles with uncertain dynamics. IEEE Trans. Control Syst. Technol. 21(2), 513–520 (2013)Google Scholar
  15. 15.
    Zheng, Z., Sun, L.: Path following control for marine surface vessel with uncertainties and input saturation. Neurocomputing 177, 158–167 (2016)Google Scholar
  16. 16.
    Liu, L., Wang, D., Peng, Z.: ESO-based line-of-sight guidance law for path following of underactuated marine surface vehicles with exact sideslip compensation. IEEE J. Oceanic Eng. 42(2), 477–487 (2017)Google Scholar
  17. 17.
    Peng, Z., Wang, D., Shi, Y., Wang, H., Wang, W.: Containment control of networked autonomous underwater vehicles with model uncertainty and ocean disturbances guided by multiple leaders. Inf. Sci. 316(20), 163–179 (2015)Google Scholar
  18. 18.
    Peng, Z., Wang, J., Wang, D.: Containment maneuvering of marine surface vehicles with multiple parameterized paths via spatial-temporal decoupling. IEEE ASME Trans. Mechatron. 22(2), 1026–1036 (2017)Google Scholar
  19. 19.
    Peng, Z., Wang, J., Wang, D.: Distributed containment maneuvering of multiple marine vessels via neurodynamics-based output feedback. IEEE Trans. Ind. Electron. 64(5), 3831–3839 (2017)Google Scholar
  20. 20.
    Peng, Z., Wang, D., Zhang, H., Sun, G.: Distributed neural network control for adaptive synchronization of uncertain dynamical multiagent systems. IEEE Trans. Neural Netw. Learn. Syst. 25(8), 1508–1519 (2014)Google Scholar
  21. 21.
    Lei, Z.L., Guo, C.: Disturbance rejection control solution for ship steering system with uncertain time delay. Ocean Eng. 95(1), 78–83 (2015)Google Scholar
  22. 22.
    Calise, A.J., Hovakimyan, N., Idan, M.: Adaptive output feedback control of nonlinear systems using neural networks. Automatica 37(12), 1201–1211 (2001)Google Scholar
  23. 23.
    Peng, Z., Wang, D., Wang, W., Liu, L.: Containment control of networked autonomous underwater vehicles: a predictor-based neural DSC design. ISA Trans. 59, 160–171 (2015)Google Scholar
  24. 24.
    Lavretsky, E., Gibson, T.E.: Projection Operator in Adaptive Systems. arXiv:1112.4232 (2011)
  25. 25.
    Patre, P.M., MacKunis, W., Kaiser, K., Dixon, W.E.: Asymptotic tracking for uncertain dynamic systems via a multilayer neural network feedforward and RISE feedback control structure. IEEE Trans. Autom. Control 53(9), 2180–2185 (2008)Google Scholar
  26. 26.
    Filippov, A.: Differential equations with discontinuous right-hand side. Am. Math. Soc. Trans. 42(2), 199–231 (1964)Google Scholar
  27. 27.
    Xian, B., Dawson, D.M., Queiroz, M.S., Chen, J.: A continuous asymptotic tracking control strategy for uncertain nonlinear systems. IEEE Trans. Autom. Control 49(7), 1206–1211 (2004)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Marine Electrical EngineeringDalian Maritime UniversityDalianChina

Personalised recommendations