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基于神经网络稳定自适应的欠驱动水面船舶编队控制方法

刘杨 郭晨 刘正江 范云生

刘杨, 郭晨, 刘正江, 范云生. 基于神经网络稳定自适应的欠驱动水面船舶编队控制方法[J]. 交通运输工程学报, 2014, 14(3): 120-126.
引用本文: 刘杨, 郭晨, 刘正江, 范云生. 基于神经网络稳定自适应的欠驱动水面船舶编队控制方法[J]. 交通运输工程学报, 2014, 14(3): 120-126.
LIU Yang, GUO Chen, LIU Zheng-jiang, FAN Yun-sheng. Control method of underactuated surface ship formation based on stable adaptive neural network control law[J]. Journal of Traffic and Transportation Engineering, 2014, 14(3): 120-126.
Citation: LIU Yang, GUO Chen, LIU Zheng-jiang, FAN Yun-sheng. Control method of underactuated surface ship formation based on stable adaptive neural network control law[J]. Journal of Traffic and Transportation Engineering, 2014, 14(3): 120-126.

基于神经网络稳定自适应的欠驱动水面船舶编队控制方法

基金项目: 

国家自然科学基金项目 61074053

国家自然科学基金项目 61374114

交通运输部科技项目 2011329225390

中央高校基本科研业务费专项资金项 3132014321

详细信息
    作者简介:

    刘杨(1981-), 女, 吉林四平人, 大连交通大学讲师, 大连海事大学博士后, 从事船舶智能控制研究

  • 中图分类号: U661.33

Control method of underactuated surface ship formation based on stable adaptive neural network control law

More Information
  • 摘要: 考虑具有不确定动态和外界环境干扰的欠驱动水面船舶编队控制问题, 提出一种基于领导/跟随和目标跟踪机制的神经网络稳定自适应控制方法。基于目标跟踪误差设计了运动学跟踪控制器, 推导出跟踪误差的动力学方程, 并利用自适应神经网络估计动力学方程中的不确定项, 构造了神经网络稳定自适应动力学跟踪控制器。应用Lyapunov稳定性理论和串接系统稳定性定理设计了船舶控制器, 并计算了自适应律, 在线调整神经网络权值, 保证编队控制闭环系统跟踪误差一致最终有界。以3艘船舶组成的编队为例, 对控制方法进行了仿真验证。在曲率半径为3倍船长的圆形跟踪路径上, 转向角误差小于15°, 队形跟踪误差的F-范数小于1m;在直线跟踪路径上, 转向角误差小于1°, 队形跟踪误差F-范数小于0.1m。

     

  • 图  1  船舶编队航行轨迹

    Figure  1.  Trajectory of ship formation

    图  2  船舶跟踪误差曲线

    Figure  2.  Tracking error curves of ships

    图  3  基于比较控制器的船舶跟踪误差曲线

    Figure  3.  Tracking error curves of ships based on comparing controller

    表  1  船舶模型参数

    Table  1.   Ship model parameters

    下载: 导出CSV

    表  2  船舶的初始状态与队形参数

    Table  2.   Initial states and formation parameters of ships

    下载: 导出CSV

    表  3  控制参数

    Table  3.   Control parameters

    下载: 导出CSV

    表  4  船舶跟踪误差

    Table  4.   Tracking errors of ships

    下载: 导出CSV
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出版历程
  • 收稿日期:  2014-02-15
  • 刊出日期:  2014-06-25

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