摘要
构建船舶航行运动学模型,分析船舶航海过程中的关键参数以及控制参量,通过数据挖掘采集船舶航线自动控制参量和关键数据,采用自适应信息融合方法融合关键数据中的特征。获取特征性路径条件后,采用大数据蚁群优化算法,优化特征性路径条件和自动控制参量,实现船舶航线自动优化控制。结果表明,该技术具备可靠的船舶航线挖掘性能,可获取最佳的航海线路控制结果,保障船舶在不同航海环境中避开全部障碍物安全航行,且船舶行驶姿态的控制矢量误差低于7.5°。
Build the ship navigation kinematics model,analyze the key parameters and control parameters in the process of ship navigation,collect the automatic control parameters and key data of ship navigation route through data mining,fuse the features in the key data through adaptive information fusion method,obtain the characteristic path conditions,and adopt the big data ant colony optimization algorithm.The characteristic path conditions and automatic control parameters are optimized to realize the automatic optimal control of ship navigation route.The test results show that the technology has reliable ship navigation line excavation performance,can obtain the best navigation line control results,ensure the ship to avoid all obstacles and navigate safely in different navigation environments,and the control vector error of ship driving attitude is less than 7.5°.
作者
郭兴华
李伟
刘芳武
胡慧慧
GUO Xing-hua;LI Wei;LIU Fang-wu;HU Hui-hui(Technology College of Shiping,Jiangsu Shipping College,Nantong 226010,China)
出处
《舰船科学技术》
北大核心
2022年第4期132-135,共4页
Ship Science and Technology
基金
江苏航运职业技术学院项目(HYKY/2021B01)
2021年江苏航运职业技术学院青年骨干教师项目
江苏省教育厅项目(18KJD580002)。
