基于高斯过程回归的船舶动力学模型辨识  

Identification of ship dynamics model based on Gaussian process regression

作　　者：陈刚 王威[1] 霍聪[1] CHEN Gang;WANG Wei;HUO Cong(College of Naval Architecture and Ocean Engineering,Naval University of Engmeering,Wuhan 430033,China)

机构地区：[1]海军工程大学舰船与海洋学院,湖北武汉430033

出　　处：《舰船科学技术》2022年第19期1-5,共5页Ship Science and Technology

摘　　要：船舶动力学模型对于船舶的智能导航和控制器设计至关重要,基于高斯过程的非参数回归被用于船舶动力学模型辨识。它可以捕捉船舶运动中的强非线性和运动耦合,并处理不确定性和噪声的影响,辨识得到的模型能够在传感器信号丢失的情况下,提供未来一段时间内船舶加速度、速度和位置信息。KVLCC2船舶的试验数据用于验证所提方法的有效性,结果表明,高斯过程回归可以准确预测船舶状态,1000步的位置预测误差为0.599 m。Ship dynamics model is crucial for intelligent navigation and design of the ship’s controller,nonparametric regression based on Gaussian process regression is used for ship dynamics model identification.it can capture the strong nonlinearity and motion cou-pling in ship motion,and deal with the presence of uncertainty and noise.The identified model can provide ship acceleration,speed and position information for a period of time in the future when the sensor signal is lost.The experimental data of KVLCC2 ship are used to verify the validity of the proposed method,the results show that Gaussian process regression can provide accurate predictions of ship’s state,the position prediction error of 1000 steps is 0.599 m.

关 键 词：高斯过程回归 辨识 船舶动力学 

分 类 号：U675.91[交通运输工程—船舶及航道工程]