Daqi Zhu, Man Mei, and Bing Sun


  1. [1] L. Lionel and S. Didik Nonlinear path-following control of anAUV, Ocean Engineering, 34(2), 2007, 1734–1744.
  2. [2] S. Li, X. Wang, and L. Zhang, Finite-time output feedbacktracking control for autonomous underwater vehicles, IEEEJournal of Oceanic Engineering, 40(3), 2015, 727–751.
  3. [3] C.F. De Paula, An improved analytical PID controller designfor non-monotonic phase LTI systems, IEEE Transactions onControl Systems and Technology, 20(5), 2012, 1328–1333.
  4. [4] A. Zhu and S.X. Yang, Tracking control of a mobile robotwith stability analysis, International Journal of Robotics andAutomation, 28(4), 2013, 340–348.
  5. [5] B. Sun, D. Zhu, and S.X. Yang, Real-time hybrid designof tracking control and obstacle avoidance for underactuatedunderwater vehicles, Journal of Intelligent & Fuzzy Systems,2015, DOI: 10.3233/IFS-151799.
  6. [6] J. Xu, M. Wang, and L. Qian, Dynamical sliding modecontrol for the trajectory tracking of underactuated unmannedunderwater vehicles, Ocean Engineering, 105(1), 2015, 54–63.
  7. [7] G. Antonelli and S. Chiaverini, Fuzzy redundancy resolutionand motion coordination for underwater vehicle-manipulatorsystems, IEEE Transactions on Fuzzy Systems, 11(1) 2003,109–120.
  8. [8] R.J. Wai, Fuzzy sliding-mode control using adaptive tuningtechnique, IEEE Transactions on Industrial Electronics, 54(1),2007, 586–594.
  9. [9] C. Luo and S.X. Yang, A bio-inspired neural network for real-time concurrent map building and complete coverage robotnavigation in unknown environment, IEEE Transactions onNeural Network, 19(7), 2008, 1279–1298.
  10. [10] A. Zhu and S.X. Yang, An improved approach to dynamictask assignment of non-holonomic multi-robots, InternationalJournal of Robotics and Automation, 26(4), 2011, 362–368.
  11. [11] A. Bagheri, T. Karimi, and N. Amanifard, Tracking perfor-mance control of a cable communicated underwater vehicleusing adaptive neural network controllers, Applied Soft Com-puting, 10(3), 2010, 908–918.
  12. [12] X. Cao, D. Zhu, and S.X. Yang, Multi-AUV target searchbased on bioinspired neurodynamics model in 3-D underwaterenvironments, IEEE Transactions on Neural Networks andLearning Systems, 2015, DOI: 10.1109/TNNLS.2015.2482501.
  13. [13] C.Z. Pan, X.Z. Lai, S.X. Yang, and M. Wu, A bioinspired neuraldynamics-based approach to tracking control of autonomoussurface vehicles subject to unknown ocean currents, NeuralComputing and Applications, 26(8), 2015, 1929–1938.
  14. [14] C.Z. Pan, X.Z. Lai, S.X. Yang, and M. Wu, A biologicallyinspired approach to tracking control of underactuated surfacevessels subject to unknown dynamics, Expert System withApplications, 42(4), 2015, 2153–2161.
  15. [15] S.X. Yang, A. Zhu, M.Q.H. Meng, and G. Yuan, A bioinspiredneurodynamics based approach to tracking control of mobilerobots, IEEE Transactions on Industrial Electronics, 59(8),2012, 3211–3220.
  16. [16] T.I. Fossen, Handbook of marine craft hydrodynamics andmotion control, Chichester, John Wiley & Sons, 2011.
  17. [17] Y.L. Zhang, S.A. Velinsky, and X. Feng, On the trackingcontrol of differentially steered wheeled mobile robots, Journalof Dynamic Systems, Measurement and Control, 119(3), 1997,455–461.358
  18. [18] A. Tahirovic and G. Magani, Passivity-based model predictivecontrol for mobile robot navigation planning in rough terrains,2010 IEEE/RSJ Int. Conf. on Intelligence Robots and Systems(IROS), Taipei, Taiwan, 2010, 307–312.
  19. [19] S.Y. Yu, X. Li, and H. Chen, Nonlinear model predictivecontrol for path following problems, International Journal ofRobot and Nonlinear Control, 25(8), 2015, 1168–1182.
  20. [20] F. Kuhne, W.F. Lages, and J.M.G. da Silva Jr., Model predic-tive control of a mobile robot using linearization, Proceedings ofMechatronics and Robotics, Aachen, Germany, 2004, 525–530.

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