留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于正弦函数处理新息的船舶模型参数辨识新算法

张显库 祝慧颖

张显库, 祝慧颖. 基于正弦函数处理新息的船舶模型参数辨识新算法[J]. 中国舰船研究, 2021, 0(X): 1–6 doi: 10.19693/j.issn.1673-3185.02122
引用本文: 张显库, 祝慧颖. 基于正弦函数处理新息的船舶模型参数辨识新算法[J]. 中国舰船研究, 2021, 0(X): 1–6 doi: 10.19693/j.issn.1673-3185.02122
ZHANG X Z, Zhu H Y. New identification algorithm for ship model parameters based on sinusoidal function processing innovation[J]. Chinese Journal of Ship Research, 2021, 0(X): 1–6 doi: 10.19693/j.issn.1673-3185.02122
Citation: ZHANG X Z, Zhu H Y. New identification algorithm for ship model parameters based on sinusoidal function processing innovation[J]. Chinese Journal of Ship Research, 2021, 0(X): 1–6 doi: 10.19693/j.issn.1673-3185.02122

基于正弦函数处理新息的船舶模型参数辨识新算法

doi: 10.19693/j.issn.1673-3185.02122
基金项目: 国家自然科学基金资助项目(51679024, 51909018);中央高校基本科研业务费资助项目(3132016315)
详细信息
    作者简介:

    张显库,男,1968年生,博士,教授,博士生导师。研究方向:船舶运动控制,鲁棒控制,计算机应用技术。E-mail:zhangxk@dlmu.edu.cn

    祝慧颖,女,1996年生,硕士生。研究方向:非线性新息辨识。E-mail:939496170@qq.com

    通信作者:

    张显库

  • 中图分类号: U661.73

New identification algorithm for ship model parameters based on sinusoidal function processing innovation

  • 摘要:   目的  针对船舶试验数据样本少,难以快速、准确辨识船舶模型参数的难题,  方法  基于最小二乘系统辨识算法,采用正弦函数处理新息,提出一种基于正弦函数非线性新息处理的船舶模型参数辨识算法。以“育鲲”船为例进行仿真实验,在只有26组辨识数据的情况下,对比最小二乘法和非线性新息改进最小二乘法的模型参数辨识效果。并利用“育鹏”船对该算法的有效性进行验证。  结果  仿真结果表明:与最小二乘法相比,非线性新息改进最小二乘法的模型参数辨识精度提升了15%左右。  结论  为小样本数据情况下的船舶模型参数辨识提供了参考。
  • 图  1  非线性新息辨识算法流程图

    Figure  1.  Flowchart of nonlinear innovation identification algorithm

    图  2  非线性的船舶运动数学模型

    Figure  2.  Nonlinear mathematical model of ship motion

    图  3  最小二乘法和非线性新息改进最小二乘法对“育鲲”船的辨识效果

    Figure  3.  Identification effect of LS method and nonlinear innovation improved LS method on Yukun ship

    图  4  最小二乘法和非线性新息改进最小二乘法对“育鹏”船的辨识效果

    Figure  4.  Identification effect of LS method and nonlinear innovation improved LS method on Yupeng ship

    表  1  “育鲲”船船舶参数

    Table  1.   Yukun ship particulars

    船舶装载状态数值
    船长/m116.0
    船宽/m18.0
    吃水/m5.4
    重心距中心距离/m−0.51
    方形系数0.56
    排水体积/m35 735.5
    航速/kn16.7
    舵叶面积/m211.46
    下载: 导出CSV

    表  2  “育鲲”船模型参数真值

    Table  2.   True value of Yukun ship model parameters

    参数真值
    K0.31
    T64.53
    $\alpha $14.22
    $\beta $22 444.52
    下载: 导出CSV

    表  3  “育鹏”船船舶参数

    Table  3.   Yupeng ship particulars

    船舶装载状态数值
    船长/m189.0
    船宽/m27.8
    吃水/m11.0
    重心距中心距离/m-1.8
    方形系数0.72
    排水体积/m342 293
    航速/kn17.3
    舵叶面积/m238
    下载: 导出CSV

    表  4  “育鹏”船模型参数真值

    Table  4.   True value of Yupeng ship model parameters

    参数真值
    K0.38
    T297.75
    α11.95
    β23 928.91
    下载: 导出CSV
  • [1] 丁锋. 系统辨识新论[M]. 北京: 科学出版社, 2013.

    DING F. System identification—new theory and methods[M]. Beijing: Science Press, 2013 (in Chinese).
    [2] 徐玲. 基于移动数据窗的传递函数多新息随机梯度辨识方法[J]. 控制与决策, 2017, 32(6): 1091–1096.

    XU L. Moving data window based multi-innovation identification stochastic gradient parameter identification method for transfer functions[J]. Control and Decision, 2017, 32(6): 1091–1096 (in Chinese).
    [3] 谢朔, 陈德山, 初秀民, 等. 改进多新息卡尔曼滤波法辨识船舶响应模型[J]. 哈尔滨工程大学学报, 2018, 39(2): 282–289.

    XIE S, CHEN D S, CHU X M, et al. Identification of ship response model based on improved multi-innovation extended Kalman filter[J]. Journal of Harbin Engineering University, 2018, 39(2): 282–289 (in Chinese).
    [4] 时振伟, 纪志成, 王艳. 多元系统耦合带遗忘因子有限数据窗递推最小二乘辨识方法[J]. 控制与决策, 2016, 31(10): 1765–1771.

    SHI Z W, JI Z C, WANG Y. Coupled finite-data-window RLS identification approach with forgetting factors for multi-variate systems[J]. Control and Decision, 2016, 31(10): 1765–1771 (in Chinese).
    [5] 孙功武, 谢基榕, 王俊轩. 基于动态遗忘因子递推最小二乘算法的船舶航向模型辨识[J]. 计算机应用, 2018, 38(3): 900–904. doi: 10.11772/j.issn.1001-9081.2017082041

    SUN G W, XIE J R, WANG J X. Ship course identification model based on recursive least squares algorithm with dynamic forgetting factor[J]. Journal of Computer Applications, 2018, 38(3): 900–904 (in Chinese). doi: 10.11772/j.issn.1001-9081.2017082041
    [6] 刘艳君, 尤俊瑶, 丁锋. 基于辅助模型正交匹配追踪的多输入系统迭代辨识算法[J]. 控制与决策, 2019, 34(4): 787–792.

    LIU Y J, YOU J Y, DING F. Iterative identification for multiple-input systems based on auxiliary model-orthogonal matching pursuit[J]. Control and Decision, 2019, 34(4): 787–792 (in Chinese).
    [7] 焦慧方, 陈希亮, 高敏, 等. 基于带遗忘因子交替广义最小二乘法的多变量耦合系统参数辨识[J]. 咸阳师范学院学报, 2018, 33(2): 49–53. doi: 10.3969/j.issn.1672-2914.2018.02.010

    JIAO H F, CHEN X L, GAO M, et al. A system parameter identification strategy for multivariable coupling system based on alternative generalized least squares method with forgetting factor[J]. Journal of Xianyang Normal University, 2018, 33(2): 49–53 (in Chinese). doi: 10.3969/j.issn.1672-2914.2018.02.010
    [8] 黄旭, 吴定会, 郑洋. 变遗忘因子多新息随机梯度算法双馈电机参数辨识[J]. 测控技术, 2019, 38(3): 116–120, 125.

    HUANG X, WU D H, ZHENG Y. Parameter identification for DFIG based on varying forgetting factor multi-innovation stochastic gradient identification algorithm[J]. Measurement & Control Technology, 2019, 38(3): 116–120, 125 (in Chinese).
    [9] 郑涵, 俞孟蕻, 袁伟. 基于反馈粒子滤波的船舶模型参数辨识[J]. 中国舰船研究, 2019, 14(3): 158–162, 178.

    ZHENG H, YU M H, YUAN W. Parameter identification of ship model based on feedback particle filter[J]. Chinese Journal of Ship Research, 2019, 14(3): 158–162, 178 (in Chinese).
    [10] ZHANG X K, ZHANG G Q. Design of ship course-keeping autopilot using a sine function-based nonlinear feedback technique[J]. The Journal of Navigation, 2016, 69(2): 246–256. doi: 10.1017/S0373463315000612
    [11] ZHANG X K, ZHANG Q, REN H X, et al. Linear reduction of backstepping algorithm based on nonlinear decoration for ship course-keeping control system[J]. Ocean Engineering, 2018, 147: 1–8. doi: 10.1016/j.oceaneng.2017.10.017
    [12] 张显库, 金一丞. 控制系统建模与数字仿真[M]. 2版. 大连: 大连海事大学出版社, 2013.

    ZHANG X K, JIN Y C. Control system modeling and digital simulation[M]. 2nd ed. Dalian: Dalian Maritime University Press, 2013 (in Chinese).
    [13] 张显库. 船舶运动简捷鲁棒控制[M]. 北京: 科学出版社, 2012.

    ZHANG X K. Ship motion concise robust control[M]. Beijing: Science Press, 2012 (in Chinese).
    [14] 贾新乐, 张显库. 船舶运动智能控制与H鲁棒控制[M]. 大连: 大连海事大学出版社, 2002.

    JIA X L, ZHANG X K. Intelligent control and robust control for ships[M]. Dalian: Dalian Maritime University Press, 2002 (in Chinese).
  • 加载中
图(4) / 表(4)
计量
  • 文章访问数:  49
  • HTML全文浏览量:  26
  • PDF下载量:  7
  • 被引次数: 0
出版历程
  • 收稿日期:  2020-09-22
  • 修回日期:  2020-10-29
  • 网络出版日期:  2021-07-02

目录

    /

    返回文章
    返回