• 中国科技核心期刊
  • JST收录期刊
XUE Nai-yao, LIU Kun, WANG Dong-jiao, YE Jia-wei. Anti-saturation Control Design for Remote Operated Vehicle Considering Model Error[J]. Journal of Unmanned Undersea Systems, 2021, 29(3): 272-277. doi: 10.11993/j.issn.2096-3920.2021.03.004
Citation: XUE Nai-yao, LIU Kun, WANG Dong-jiao, YE Jia-wei. Anti-saturation Control Design for Remote Operated Vehicle Considering Model Error[J]. Journal of Unmanned Undersea Systems, 2021, 29(3): 272-277. doi: 10.11993/j.issn.2096-3920.2021.03.004

Anti-saturation Control Design for Remote Operated Vehicle Considering Model Error

doi: 10.11993/j.issn.2096-3920.2021.03.004
  • Received Date: 2019-12-09
  • Rev Recd Date: 2020-06-29
  • Publish Date: 2021-06-30
  • To investigate the trajectory-tracking problems of a new open-frame remote operated vehicle(ROV), a new variable gain anti-saturation auxiliary system is proposed, which is based on the radial basis function neural network sliding mode control law and considers thrust constraints. The stability of the control law was proved using the Lyapunov stability theory. A simulation was built using MATLAB Simulink, and modeling errors, ocean current disturbances, and cable action force are considered during the trajectory-tracking study, which is similar to the actual working environment of a ROV. The results show that after incorporating the anti-saturation system, the thrust saturation duration of the propulsion system decreased by 27% during the ROV track tracking, the cumulative tracking error of each degree of freedom decreased, and the tracking error of the roll and heave degrees decreased significantly, demonstrating the reliability of the new control law.

     

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  • [1]
    王啸. 基于自适应鲁棒算法的开架ROV悬停姿态控制研究[D]. 青岛: 中国海洋大学, 2014.
    [2]
    Fernandes D D, Donha D C. Optimal Control System for a Semi-Autonomous Underwater Vehicle[J]. IFAC Proceedings Volumes, 2009, 42(18): 255-260.
    [3]
    Fernandes D D, Sorensen A J, Pettersen K Y, et al. Output Feedback Motion Control System for Observation Class ROVs Based on a High-gain State Observer: Theoretical and Experimental Results[J]. Control Engineering Practice, 2015, 39: 90-102.
    [4]
    朱琦. 作业型水下机器人姿态控制方法研究[D]. 杭州: 浙江大学, 2018.
    [5]
    Chu Z, Xiang X, Zhu D, et al. Adaptive Fuzzy Sliding Mode Diving Control for Autonomous Underwater Vehicle with Input Constraint[J]. International Journal of Fuzzy Systems, 2018, 20(5): 1460-1469.
    [6]
    刘金琨. RBF神经网络自适应控制Matlab 仿真[M]. 北京: 清华大学出版社, 2014: 57-60.
    [7]
    夏俊. 基于RBF神经网络的无人水面舰艇自适应控制[J]. 机械制造与自动化, 2019, 48(3): 185-188.
    [8]
    Fossen T I. Handbook of Marine Craft Hydrodynamics and Motion Control[M]. USA: John Wiley & Sons, Inc., 2011.
    [9]
    Huo X, Ge T, Wang X, et al. Horizontal Path-following Control for Deep-sea Work-class ROVs Based on a Fuzzy Logic System[J]. Ships and Offshore Structures, 2018, 13(6): 637-648.
    [10]
    Chen M, Ge S S, Ren B, et al. Adaptive Tracking Control of Uncertain MIMO Nonlinear Systems with Input Constraints[J]. Automatica, 2011, 47(3): 452-465.
    [11]
    徐诗婧. 开架式ROV水动力特性与运动仿真研究[D]. 哈尔滨: 哈尔滨工程大学, 2018.
    [12]
    薛乃耀, 王冬姣, 叶家玮, 等. 开架式水下机器人操纵性水动力系数计算[J]. 广东造船, 2020, 39(1): 25-28.

    Xue Nai-yao, Wang Dong-jiao, Ye Jia-wei, et al. Maneuverability Coefficients Calculation of an Open-frame Underwater Remote Operated Vehicle[J]. Guangdong Ship-building, 2020, 39(1): 25-28.
    [13]
    Salgado-Jimnez T, García-Valdovinos L G, Delgado- Ramírez G. Control of ROVs Using a Model-free 2nd- Order Sliding Mode Approach[EB/OL]. Sliding Mode Control. (2011-04-11)[2019-09-18]. https://www.intechopen. com/books/sliding-mode-control/control-of-rovs-using-a-model-free-2nd-order-sliding-mode-approach.
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