• Chinese Journal of Ship Research
  • Vol. 20, Issue 1, 309 (2025)
Xiang YE1, Chao CHEN1, Jian Xiong JIA2, and Hang CHEN2
Author Affiliations
  • 1School of Naval Architecture and Maritime, Zhejiang Ocean University, Zhoushan 316022, China
  • 2Zhejiang Branch of China Classification Society, Ningbo 430060, China
  • show less
    DOI: 10.19693/j.issn.1673-3185.03609 Cite this Article
    Xiang YE, Chao CHEN, Jian Xiong JIA, Hang CHEN. Adaptive neural control for marine autonomous surface ships in cross-water scenarios[J]. Chinese Journal of Ship Research, 2025, 20(1): 309 Copy Citation Text show less
    References

    [2] J YE, C X LI, W S WEN et al. Deep learning in maritime autonomous surface ships: current development and challenges. Journal of Marine Science and Application, 22, 584-601(2023).

    [3] L WANG, Q WU, J L LIU et al. State-of-the-art research on motion control of maritime autonomous surface ships. Journal of Marine Science and Engineering, 7, 438-470(2019).

    [6] S B LI, T T MA, X Y LUO et al. Adaptive fuzzy output regulation for unmanned surface vehicles with prescribed performance. International Journal of Control, Automation and Systems, 18, 405-414(2020).

    [7] G B ZHU, Y MA, Z X LI et al. Adaptive neural output feedback control for MSVs with predefined performance. IEEE Transactions on Vehicular Technology, 70, 2994-3006(2021).

    [8] G B ZHU, J L DU, Y G KAO. Robust adaptive neural trajectory tracking control of surface vessels under input and output constraints. Journal of the Franklin Institute, 357, 8591-8610(2020).

    [9] Z L TANG, K P TEE, W HE. Tangent barrier Lyapunov functions for the control of output-constrained nonlinear systems. IFAC Proceedings Volumes, 46, 449-455(2013).

    [12] C P BECHLIOULIS, G A ROVITHAKIS. Robust adaptive control of feedback linearizable MIMO nonlinear systems with prescribed performance. IEEE Transactions on Automatic Control, 53, 2090-2099(2008).

    [14] IHLE I F, SKJETNE R, FOSSEN T I. Output feedback control f maneuvering systems using observer backstepping[C]Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control Automation Intelligent Control, 2005. Limassol, Cyprus: IEEE, 2005: 1512–1517.

    [15] M M POLYCARPOU. Stable adaptive neural control scheme for nonlinear systems. IEEE Transactions on Automatic Control, 41, 447-451(1996).

    [16] H DENG, M KRSTIĆ. Stochastic nonlinear stabilization—I: a backstepping design. Systems & Control Letters, 32, 143-150(1997).

    [17] G B ZHU, Y MA, Z X LI et al. Dynamic event-triggered adaptive neural output feedback control for MSVs using composite learning. IEEE Transactions on Intelligent Transportation Systems, 24, 787-800(2023).

    [19] C P BECHLIOULIS, G A ROVITHAKIS. Adaptive control with guaranteed transient and steady state tracking error bounds for strict feedback systems. Automatica, 45, 532-538(2009).

    [20] R SKJETNE, Ø SMOGELI, T I FOSSEN. Modeling, identification, and adaptive maneuvering of CyberShip II: a complete design with experiments. IFAC Proceedings Volumes, 37, 203-208(2004).

    Xiang YE, Chao CHEN, Jian Xiong JIA, Hang CHEN. Adaptive neural control for marine autonomous surface ships in cross-water scenarios[J]. Chinese Journal of Ship Research, 2025, 20(1): 309
    Download Citation