Article(id=1263533682418135579, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263533678655881533, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-4653.2026.02.013, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1742313600000, receivedDateStr=2025-03-19, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1779179505209, onlineDateStr=2026-05-19, pubDate=1777046400000, pubDateStr=2026-04-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1779179505209, onlineIssueDateStr=2026-05-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1779179505209, creator=13701087609, updateTime=1779179505209, updator=13701087609, issue=Issue{id=1263533678655881533, tenantId=1146029695717560320, journalId=1240618002186551303, year='2026', volume='49', issue='2', pageStart='1', pageEnd='163', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1779179504312, creator=13701087609, updateTime=1779179563167, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1263533925629047616, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263533678655881533, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1263533925629047617, tenantId=1146029695717560320, journalId=1240618002186551303, issueId=1263533678655881533, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=112, endPage=118, ext={EN=ArticleExt(id=1263533682980172317, articleId=1263533682418135579, tenantId=1146029695717560320, journalId=1240618002186551303, language=EN, title=Ship motion modeling and simulation based on characteristic model, columnId=1240655021340160960, journalTitle=Navigation of China, columnName=Intelligent Shipping, runingTitle=null, highlight=null, articleAbstract=

Ship motion modeling is crucial for developing intelligent control technology. Traditional modeling methods, however, have drawbacks such as a large number of parameters and insufficient precision. To address these issues, this paper focuses on the latest intelligent research and training ship "Xin-Hong-Zhuan" of Dalian Maritime University. A ship motion characteristic model is constructed using the characteristic modeling method. First, the study begins with Kalman filtering to preprocess real-ship test data. Next, the nonlinear innovation recursive least squares method with a forgetting factor is used to identify the model's parameters. Finally, turning circle tests and zigzag maneuver tests are conducted to verify the model's effectiveness and accuracy. The results show that the model has an agreement of 89.7%, fewer parameters, and higher precision than the traditional Nomoto model. This research offers a theoretical reference for applying characteristic models in navigation and is significant for improving the precision of ship motion control.

, correspAuthors=Xianku Zhang, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Zexu Miao, Xianku Zhang, Daocheng Ma, Lin Qiao), CN=ArticleExt(id=1263533685362536991, articleId=1263533682418135579, tenantId=1146029695717560320, journalId=1240618002186551303, language=CN, title=基于特征模型的船舶运动建模与仿真, columnId=1240655021528904650, journalTitle=中国航海, columnName=智能航运, runingTitle=null, highlight=null, articleAbstract=

船舶运动建模对智能控制技术的发展具有重要意义,但传统建模方法存在参数多、精度不足等问题。针对这些问题,文章以大连海事大学最新的智能研究与实训两用船“新红专”为研究对象,采用特征模型建模法构建船舶运动特征模型。首先,运用Kalman滤波对实船试验数据进行预处理;其次,采用含遗忘因子的非线性新息最小二乘法进行特征模型参数辨识;最后,通过回转试验和Z形试验验证模型的有效性与准确性。结果表明,所建模型符合度为89.7%,相比传统Nomoto模型参数更少且精度更高。该研究为特征模型在航海领域的深化应用提供理论参考,对提升船舶运动控制精度具有重要意义。

, correspAuthors=张显库, authorNote=null, correspAuthorsNote=
*
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苗泽旭(2001—),男,博士研究生,研究方向为船舶运动控制。

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苗泽旭(2001—),男,博士研究生,研究方向为船舶运动控制。

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苗泽旭(2001—),男,博士研究生,研究方向为船舶运动控制。

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基于特征模型的船舶运动建模与仿真
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苗泽旭 , 张显库 * , 马道成 , 乔林
中国航海 | 智能航运 2026,49(2): 112-118
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中国航海 | 智能航运 2026, 49(2): 112-118
基于特征模型的船舶运动建模与仿真
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苗泽旭, 张显库* , 马道成, 乔林
作者信息
  • 大连海事大学 航海学院,辽宁 大连 116026
  • 苗泽旭(2001—),男,博士研究生,研究方向为船舶运动控制。

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Ship motion modeling and simulation based on characteristic model
Zexu Miao, Xianku Zhang* , Daocheng Ma, Lin Qiao
Affiliations
  • Navigation College, Dalian Maritime University, Dalian 116026, China
出版时间: 2026-04-25 doi: 10.3969/j.issn.1000-4653.2026.02.013
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船舶运动建模对智能控制技术的发展具有重要意义,但传统建模方法存在参数多、精度不足等问题。针对这些问题,文章以大连海事大学最新的智能研究与实训两用船“新红专”为研究对象,采用特征模型建模法构建船舶运动特征模型。首先,运用Kalman滤波对实船试验数据进行预处理;其次,采用含遗忘因子的非线性新息最小二乘法进行特征模型参数辨识;最后,通过回转试验和Z形试验验证模型的有效性与准确性。结果表明,所建模型符合度为89.7%,相比传统Nomoto模型参数更少且精度更高。该研究为特征模型在航海领域的深化应用提供理论参考,对提升船舶运动控制精度具有重要意义。

智能航运  /  船舶运动  /  特征模型  /  非线性新息  /  递归最小二乘法  /  卡尔曼滤波

Ship motion modeling is crucial for developing intelligent control technology. Traditional modeling methods, however, have drawbacks such as a large number of parameters and insufficient precision. To address these issues, this paper focuses on the latest intelligent research and training ship "Xin-Hong-Zhuan" of Dalian Maritime University. A ship motion characteristic model is constructed using the characteristic modeling method. First, the study begins with Kalman filtering to preprocess real-ship test data. Next, the nonlinear innovation recursive least squares method with a forgetting factor is used to identify the model's parameters. Finally, turning circle tests and zigzag maneuver tests are conducted to verify the model's effectiveness and accuracy. The results show that the model has an agreement of 89.7%, fewer parameters, and higher precision than the traditional Nomoto model. This research offers a theoretical reference for applying characteristic models in navigation and is significant for improving the precision of ship motion control.

intelligent shipping  /  ship motion  /  characteristic mathematical model  /  nonlinear innovation  /  recursive least squares  /  Kalman filter
苗泽旭, 张显库, 马道成, 乔林. 基于特征模型的船舶运动建模与仿真. 中国航海, 2026 , 49 (2) : 112 -118 . DOI: 10.3969/j.issn.1000-4653.2026.02.013
Zexu Miao, Xianku Zhang, Daocheng Ma, Lin Qiao. Ship motion modeling and simulation based on characteristic model[J]. Navigation of China, 2026 , 49 (2) : 112 -118 . DOI: 10.3969/j.issn.1000-4653.2026.02.013
  • 国家自然科学基金资助项目(52571396; 51679024)
  • 大连市重点领域创新团队支持计划资助项目(2020RT08)
2026年第49卷第2期
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doi: 10.3969/j.issn.1000-4653.2026.02.013
  • 接收时间:2025-03-19
  • 首发时间:2026-05-19
  • 出版时间:2026-04-25
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  • 收稿日期:2025-03-19
基金
国家自然科学基金资助项目(52571396; 51679024)
大连市重点领域创新团队支持计划资助项目(2020RT08)
作者信息
    大连海事大学 航海学院,辽宁 大连 116026

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2种不同金属材料的力学参数

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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
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小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
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