Guoqing Xia, Ang Zhao, Huiyong Wu, and Ju Liu


  1. [1] R. Skjetne, T.I. Fossen, and P.V. Kokotovi´c, Adaptive maneuvering, with experiments, for a modle ship in a marine control laboratory, Automatica, 41(2), 2005, 289–298.
  2. [2] J. Wu, H. Peng, K. Ohtsu, G. Kitagawa, and T. Itoh, Ship’s tracking control based on nonlinear time series model, Applied Ocean Research, 36, 2012, 1–11.
  3. [3] H. Ashrafiuon, K.R. Muske, L.C. McNinch, and R.A. Soltan, Sliding-mode tracking control of surface vessels, IEEE Transactions on Industrial Electronics, 55(11), 2008, 4004–4012.
  4. [4] M. Wondergem, E. Lefeber, K.Y. Pettersen, and H. Nijmeijer, Output feedback tracking of ships IEEE Transactions on Control Systems Technology, 19(2), 2011, 442–448.
  5. [5] T.I. Fossen and ˚A. Grøvlen, Nonlinear output feedback control of dynamically positioned ships using vectorial observer back-stepping, IEEE Transactions on Control Systems Technology, 6(1), 1998, 121–128.
  6. [6] O.M. Aamo, M. Arcak, and T.I. Fossen, Global output tracking control of a class of euler-lagrange systems with monotonic nonlinearities in the velocities, Int J of Nonlinear Control, 74(7), 2000, 649–658.
  7. [7] D.C. Theodoridis, Y.S. Boutalis, and M.A. Christodoulou, A new adaptive neuro-fuzzy controller for trajectory tracking of robot manipulators International Journal of Robotics and Automation, 26(1), 2011, 64–75.
  8. [8] T.L. Mai, Y.N. Wang, and T.Q. Ngo, Adaptive tracking control for robot manipulators using fuzzy wavelet neural networks, International Journal of Robotics and Automation, 30(1), 2015, 26–39.
  9. [9] K. Kherraz, M. Hamerlain, and N. Achour, Robust neuro-fuzzy sliding mode controller for a flexible robot manipulator, International Journal of Robotics and Automation, 30(1), 2015, 40–49.
  10. [10] K.P. Tee and S.S. Ge, Control of fully actuated ocean surface vessels using a class of feedforward approximators, IEEE Transactions on Control Systems Technology, 14(4), 2006, 750–7568.
  11. [11] L. Zhang, H.M. Jia, and X. Qi, NNFFC-adaptive outputfeedback trajectory tracking control for a surface at hightspeed, Ocean Engineering, 38, 2011, 1430–1438.
  12. [12] J. Du, Y. Yang, D. Wang, and C. Guo, A robust adaptiveneural networks controller for maritime dynamic positioningsystem, Neurocomputing, 110(13), 2013, 128–136.
  13. [13] C. Wen, J. Zhou, Z. Liu, and H. Su, Robust adaptive control of uncertain nonlinear systems in the presence of input saturation and external disturbance, IEEE Transactions on Automatic Control, 56(7), 2011, 1672–1678.
  14. [14] L. Sonneveldt, Q.P. Chu, and J.A. Mulder, Nonlinear flight control design using constrained adaptive backstepping, Journal of Guidance, Control and Dynamics, 30(2), 2007, 322–336
  15. [15] R. Yuan, X. Tan, G. Fan, and J. Yi Robust adaptive neural network control for a class of uncertain nonlinear systems with actuator amplitude and rate saturations, Neurocomputing, 125(11), 2014, 72–80.
  16. [16] N.E. Kahveci and P.A. Ioannou, Indirect adaptive control for systems with input rate saturation, 2008 American Control Conference Westin Seattle Hotel, Seattle, Washington, USA June 11–13, 2008.
  17. [17] A. Leonessa, W.M. Haddad, T. Hayakawa, and Y. Morel,Adaptive control for nonlinear uncertain systems with actuator amplitude and rate saturation constraints, Int. J. Adapt. Control Signal Process, 23(1), 2009, 73–96.
  18. [18] K.C. Hsu, W.Y. Wang, and P.Z. Lin, Sliding mode control for uncertain nonlinear systems with multiple inputs containing sector nonlinearities and dead-zone, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 34(1), 2004, 374–380.
  19. [19] K.K. Shyu, W.J. Liu, and K.C. Hsu, Decentralized variable structure control of uncertain large-scale systems containing a dead-zone, IEEE Proceedings of Control Theory and Applications, 150(5), 2003, 467–475.
  20. [20] K.T. Woo, F.L. Lewis, L.X. Wang, and Z.X. Li, Deadzonecompensation in motion control systems using adaptive fuzzylogic control, Proceedings of the 1997 IEEE InternationalConference on Robotics and Automation, Albuquerque, NewMexico, 1997, 1424–1429.
  21. [21] R.R. Selmic and F.L. Lewis, Deadzone compensation in motion control systems using neural networks, IEEE Trans. Automat. Contr., 45(4), 2000, 602–613.
  22. [22] T.P. Zhang and S.S. Ge, Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form, Automatica, 44(7), 2008, 1895–1903.
  23. [23] Q. Hu, G. Ma, and L. Xie, Robust and apative variablestructure output feedback control of uncertain systems withinput nonlinearity, Automatica, 44(2), 2008, 552–559.
  24. [24] M. Chen, S.S. Ge, B.V. Ee How, and Y.S. Choo, Robustadaptive position mooring control for marine vessels, IEEETransactions on Control Systems Technology, 21(2), 2013,395–409, 2013.
  25. [25] M. Chen, B. Jiang, J. Zou, and X. Feng, Robust adaptive tracking control of the underwater robot with input nonlinearity using neural networks, Int J of Computational Inteligence Systems, 3(5), 2010, 646–655.
  26. [26] G. Xia, X. Shao, A. Zhao, and H. Wu Adaptive neuralnetwork control with backstepping for surface ships with input dead-zone, Mathematical Problems in Engineering, Article ID 530162, 2013.
  27. [27] S.S. Ge, C.C. Hang, T.H. Lee, and T. Zhang, Stable adaptive neural network control (Boston, MA: Kluwer Academic, 2001).
  28. [28] Y.H. Kim, F.L. Lewis, and C.T. Abdallah, A dynamic recurrent neural-network-based adaptive observer for a class of nonlinear systems, Automatica, 33(8), 1997, 1539–1543.
  29. [29] N. Hovakimyan, F. Nardi, A. Calise, and N. Kim, Adaptive output feedback control of uncertain nonlinear systems using single-hidden-layer neural networks, IEEE Transactions on Neural Networks, 13(6), 2002, 1420–1431.

Important Links:

Go Back