基于智能控制的船舶水动力导数敏感性分析方法

欧阳子路1，王鸿东*1,2，王检耀1,2，易宏1,2

1上海交通大学海洋工程国家重点实验室，上海 200240 2上海交通大学海洋智能装备与系统教育部重点实验室，上海200240

摘 要:［目的］为了获得用于智能控制的船舶运动简化数学模型，以Mariner 船为研究对象，提出结合标准操纵性试验与比例−积分−微分（ PID）航向控制试验的敏感性分析方法。［方法］将控制指标、操纵性指标及

整个时历过程典型运动状态变量平方损失进行复合分析，得到包含多维敏感性系数的数据集；引入K-means

机器学习算法对该数据集进行聚类分析，完成水动力导数敏感性强弱的自动划分，进而对模型进行简化，并对所提简化模型、前人简化模型和完整模型的航向控制与航迹控制进行仿真试验。［结果］试验结果验证了所提敏感性分析方法的有效性，显示所提模型具有更高的操控预报精度。［结论］研究表明所提方法对指导基于智能控制的船舶运动建模具有一定的意义。关键词：智能控制；水动力导数；敏感性分析；聚类分析

中图分类号: U664.82文献标志码:A DOI：10.19693/j.issn.1673-3185.01992

Sensitivity analysis method of ship hydrodynamic derivatives based on intelligent control OUYANG Zilu1, WANG Hongdong*1,2, WANG Jianyao1,2, YI Hong1,2

1 State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China 2 Key Laboratory of Marine Intelligent Equipment and System Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China

Abstract: ［Objectives ］ In order to obtain a simplified mathematical model of ship motion for intelligent control, this paper takes a Mariner-class vessel as the research object and proposes a sensitivity analysis method combining the standard maneuverability test and PID (proportion-integral-differential) heading control test.［Methods］ Compound analysis of the control index, maneuverability index and squared loss of typical motion state variables throughout the entire process is performed to obtain a dataset containing multi-dimensional sensitivity coefficients. A K-means machine learning algorithm is introduced to perform cluster analysis on the dataset. The sensitivity division of hydrodynamic derivatives is completed and the model is simplified.［Results ］ Contrastive simulation tests of heading control and track control are carried out among the simplified model, former simplified model and complete model, and the results show that the sensitivity analysis method proposed in this paper is effective and the model proposed in this paper has higher control prediction accuracy.［Conclusions ］ The method proposed in this paper has certain significance for guiding ship motion modeling for intelligent control.

Key words: intelligent control；hydrodynamic derivatives；sensitivity analysis；cluster analysis

收稿日期: 2020–06–07 修回日期: 2020–08–02 网络首发时间: 2021–06–15 11:45

基金项目:国家自然科学基金资助项目（51909162）；海洋工程国家重点实验室基金资助项目（GKZD010075）

作者简介: 欧阳子路，男，1996 年生，博士生。研究方向：船舶操纵性与运动建模技术。E-mail：ouyang_sjtu@sjtu.edu.cn王鸿东，男，1989年生，博士，副研究员，博士生导师。研究方向：基于海洋装备动力学特征的智能控制。E-mail：whd302@sjtu.edu.cn

*通信作者:王鸿东