Volume 18 Issue 3
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YU R Z, YUAN J P, LI J Y. Adaptive control of large transport ship based on grasshopper optimization algorithm[J]. Chinese Journal of Ship Research, 2023, 18(3): 66–74. DOI: 10.19693/j.issn.1673-3185.02782
Citation: YU R Z, YUAN J P, LI J Y. Adaptive control of large transport ship based on grasshopper optimization algorithm[J]. Chinese Journal of Ship Research, 2023, 18(3): 66–74. DOI: 10.19693/j.issn.1673-3185.02782
shu

Adaptive control of large transport ship based on grasshopper optimization algorithm

  • 1.

    College of Electronics and Information Engineering, Guangdong Ocean University, Zhanjiang 524088, China

  • 2.

    College of Ocean Engineering, Guangdong Ocean University, Zhanjiang 524088, China

  • 3.

    Wuhan Second Ship Design and Research Institute, Wuhan 430205, China

More Information
  • Received Date: January 18, 2022
  • Revised Date: May 05, 2022
  • Official website online publication date: May 16, 2022
© 2023 The Authors. Published by Editorial Office of Chinese Journal of Ship Research. Creative Commons License
This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Graphical Abstract
    • Abstract
  •   Objectives  The maritime navigation environment is random, complex and changeable, and intelligent autonomous navigation is an important trend in the development of large ocean-going transport ships, for which a new adaptive control method is proposed.
      Methods  First, the linear quadratic regulator (LQR) control method is integrated with the first-order dynamic integral sliding mode control method based on the grasshopper optimization algorithm (GOA). A nonlinear passive estimator with real-time monitoring of wave disturbance forces is then combined to separate the high and low-frequency motion signals of the ship. Finally, the simulation results of the proposed method are compared with those of the LQR control method and first-order dynamic integral sliding mode control method.
      Results  The results show that the new control method has better transient and steady-state tracking performance, and is able to overcome the effects of random waves under different sea conditions with strong robustness.
      Conclusions  The new control method has such abilities as self-adjustment in complex environments, fast control response, high precision and less redundant steering, enabling it to greatly improve the navigation efficiency, safety and stability of large transport ships.
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    • References (21)
  • [1]
    张显库, 韩旭. 船舶运输安全保障下的智能船舶运动控制策略[J]. 中国舰船研究, 2019, 14(增刊 1): 1–6. doi: 10.19693/j.issn.1673-3185.01634

    ZHANG X K, HAN X. The motion control strategy for intelligent ships based on ship transportation safeguard[J]. Chinese Journal of Ship Research, 2019, 14(Supp 1): 1–6 (in Chinese). doi: 10.19693/j.issn.1673-3185.01634
    [2]
    金仲佳, 司朝善, 邱耿耀, 等. 基于FDLQR的喷流舵船舶航向横摇控制研究[J]. 舰船科学技术, 2020, 42(15): 74–81.

    JIN Z J, SI C S, QIU G Y, et al. Research on course and roll control of ship using jet rudder based on FDLQR[J]. Ship Science and Technology, 2020, 42(15): 74–81 (in Chinese).
    [3]
    BORKOWSKI P. Adaptive system for steering a ship along the desired route[J]. Mathematics, 2018, 6(10): 196. doi: 10.3390/math6100196
    [4]
    李明聪, 郭晨, 袁毅. 无人运输船舶的直线航迹反步自适应滑模控制[J]. 系统仿真学报, 2018, 30(11): 4448–4453, 4461. doi: 10.16182/j.issn1004731x.joss.201811047

    LI M C, GUO C, YUAN Y. Adaptive backstepping sliding mode control for straight line track of unmanned transport ship[J]. Journal of System Simulation, 2018, 30(11): 4448–4453, 4461 (in Chinese). doi: 10.16182/j.issn1004731x.joss.201811047
    [5]
    LEE S D, YOU S S, XU X, et al. Active control synthesis of nonlinear pitch-roll motions for marine vessels[J]. Ocean Engineering, 2021, 221: 108537. doi: 10.1016/j.oceaneng.2020.108537
    [6]
    尉明军, 王长青, 徐骋. 基于改进LQR的航向静不稳定飞行器控制方法研究[J]. 控制与信息技术, 2019(4): 85–90.

    WEI M J, WANG C Q, XU C. Research on heading statically unstable aircraft control method based on improved LQR[J]. Control and Information Technology, 2019(4): 85–90 (in Chinese).
    [7]
    MIRJALILI S. Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems[J]. Neural Computing and Applications, 2016, 27(4): 1053–1073. doi: 10.1007/s00521-015-1920-1
    [8]
    MIRJALILI S. The ant lion optimizer[J]. Advances in Engineering Software, 2015, 83: 80–98. doi: 10.1016/j.advengsoft.2015.01.010
    [9]
    郝晓弘, 宋吉祥, 周强, 等. 混合策略改进的鲸鱼优化算法[J]. 计算机应用研究, 2020, 37(12): 3622–3626, 3655. doi: 10.19734/j.issn.1001-3695.2019.09.0528

    HAO X H, SONG J X, ZHOU Q, et al. Improved whale optimization algorithm based on hybrid strategy[J]. Application Research of Computers, 2020, 37(12): 3622–3626, 3655 (in Chinese). doi: 10.19734/j.issn.1001-3695.2019.09.0528
    [10]
    SAREMI S, MIRJALILI S, LEWIS A. Grasshopper optimisation algorithm: theory and application[J]. Advances in Engineering Software, 2017, 105: 30–47. doi: 10.1016/j.advengsoft.2017.01.004
    [11]
    MIRJALILI S Z, MIRJALILI S, SAREMI S, et al. Grasshopper optimization algorithm for multi-objective optimization problems[J]. Applied Intelligence, 2018, 48(4): 805–820. doi: 10.1007/s10489-017-1019-8
    [12]
    程泽新, 李东生, 高杨. 基于蝗虫算法的无人机三维航迹规划[J]. 飞行力学, 2019, 37(2): 46–50, 55. doi: 10.13645/j.cnki.f.d.20190118.006

    CHENG Z X, LI D S, GAO Y. UAV three-dimensional path planning based on the grasshopper algorithm[J]. Flight Dynamics, 2019, 37(2): 46–50, 55 (in Chinese). doi: 10.13645/j.cnki.f.d.20190118.006
    [13]
    武颖, 杨胜强, 李文辉, 等. 基于滑模反演的欠驱动水面无人艇航向控制[J]. 科学技术与工程, 2018, 18(1): 47–53. doi: 10.3969/j.issn.1671-1815.2018.01.009

    WU Y, YANG S Q, LI W H, et al. Heading control of an underactuated unmanned surface vehicle based on sliding mode and backstepping[J]. Science Technology and Engineering, 2018, 18(1): 47–53 (in Chinese). doi: 10.3969/j.issn.1671-1815.2018.01.009
    [14]
    茹志鹃. MMG分离建模在舰船操纵性仿真软件开发过程的应用[J]. 舰船科学技术, 2020, 42(22): 172–174.

    RU Z J. Application of MMG separation modeling in the development process of ship maneuverability simulation software[J]. Ship Science and Technology, 2020, 42(22): 172–174 (in Chinese).
    [15]
    SAELID S, JENSSEN N, BALCHEN J. Design and analysis of a dynamic positioning system based on Kalman filtering and optimal control[J]. IEEE Transactions on Automatic Control, 1983, 28(3): 331–339. doi: 10.1109/TAC.1983.1103225
    [16]
    沈智鹏, 代昌盛, 张宁. 欠驱动船舶自适应迭代滑模轨迹跟踪控制[J]. 交通运输工程学报, 2017, 17(6): 125–134. doi: 10.3969/j.issn.1671-1637.2017.06.014

    SHEN Z P, DAI C S, ZHANG N. Trajectory tracking control of underactuated ship based on adaptive iterative sliding mode[J]. Journal of Traffic and Transportation Engineering, 2017, 17(6): 125–134 (in Chinese). doi: 10.3969/j.issn.1671-1637.2017.06.014
    [17]
    FOSSEN T I. Handbook of marine craft hydrodynamics and Motion Control[M]. Hoboken: Wiley, 2011.
    [18]
    刘金琨. 滑模变结构控制MATLAB仿真[M]. 2版. 北京: 清华大学出版社, 2012.

    LIU J K. Sliding mode control design and MATLAB simulation[M]. 2nd ed. Beijing: Tsinghua University Press, 2012 (in Chinese).
    [19]
    赵然, 郭志川, 朱小勇. 一种基于Levy飞行的改进蝗虫优化算法[J]. 计算机与现代化, 2020(1): 104–110. doi: 10.3969/j.issn.1006-2475.2020.01.020

    ZHAO R, GUO Z C, ZHU X Y. An improved grasshopper optimization algorithm based on levy flight[J]. Computer and Modernization, 2020(1): 104–110 (in Chinese). doi: 10.3969/j.issn.1006-2475.2020.01.020
    [20]
    VesselFinder. COSCO SHANGHAI[EB/OL]. (2014-11-13) [2022-12-19]. https://www.vesselfinder.com/ship-photos/75862.
    [21]
    秦梓荷, 林壮, 李平, 等. 基于LOS导航的欠驱动船舶滑模控制[J]. 中南大学学报(自然科学版), 2016, 47(10): 3605–3611.

    QIN Z H, LIN Z, LI P, et al. Sliding-mode control of underactuated ship based on LOS guidance[J]. Journal of Central South University (Science and Technology), 2016, 47(10): 3605–3611 (in Chinese).
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