检索结果-南通市图书馆

diving dynamics identification and motion prediction for marine crafts using field data

Journal of Ocean Engineering and Science 2024年第4期9卷 391-400页

作者： Yiming Zhong Caoyang Yu Yulin Bai Zheng Zeng Lian Lian School of Oceanography Shanghai Jiao Tong UniversityShanghai 200030China Key Laboratory of Polar Ecosystem and Climate Change Ministry of EducationShanghai Jiao Tong UniversityShanghai 200030China Shanghai Key Laboratory of Polar Life and Environment Sciences Shanghai Jiao Tong UniversityShanghai 200030China State Key Laboratory of Ocean Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Ensuring accurate parameter identification and diving motion prediction of marine crafts is essential for safe navigation,optimized operational efficiency,and the advancement of marine *** this,this paper proposes an instrumental variable-based least squares(IVLS)***,aiming to balance complexity with accuracy,a decoupled diving model is constructed,incorporating nonlinear actuator characteristics,inertia coefficients,and damping ***,a discrete parameter identification matrix is designed based on this dedicated model,and then a IVLS algorithm is innovatively derived to reject measurement ***,the stability of the proposed algorithm is validated from a probabilistic point of view,providing a solid theoretical ***,performance evaluation is conducted using four depth control datasets obtained from a piston-driven profiling float in Qiandao Lake,with desired depths of 30 m,40 m,50 m,and 60 *** on the diving dynamics identification results,the IVLS algorithm consistently shows superior performance when compared to recursive weighted least squares algorithm and least squares support vector machine algorithm across all depths,as evidenced by lower average absolute error(AVGAE),root mean square error(RMSE),and maximum absolute error values and higher determination coefficient(R2).Specifically,for desired depth of 60 m,the IVLS algorithm achieved an AVGAE of 0.553 m and RMSE of 0.655 m,significantly outperforming LSSVM with AVGAE and RMSE values of 8.782 m and 11.117 m,***,the IVLS algorithm demonstrates a remarkable generalization capability with R2 values consistently above 0.95,indicating its robustness in handling varied diving dynamics.

关键词： Marine craft Parameter identification Motion prediction Instrumental variable-based least-squares algorithm diving dynamics model

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：