ABSTRACT

Demanding marine operations increase the complexity of manoeuvring. A highly accurate ship model promotes predicting ship motions and advancing control safety. It is crucial to identify the unknown hydrodynamic coefficients under environmental disturbance to establish accurate mathematical models. In this paper, the identification procedure for a 3 degree of freedom hydrodynamic model under disturbance is completed based on the support vector machine with multiple manoeuvres datasets. The algorithm is validated on the clean ship model and the results present good fitness with the reference. Experiments in different sea states are conducted to investigate the effects of the turbulence on the identification performance. Generalisation results show that the models identified in the gentle and moderate environments have less than 10% deviations and are considered allowable. The higher perturbations, the lower fidelity the identified model has. Models identified under disturbance could provide different levels of reliable support for the operation decision system.

摘要

苛刻的海上作业增加了操纵的复杂性。高度准确的船舶模型有助于预测船舶运动并提高控制安全性。识别环境扰动下未知的水动力系数对建立准确的数学模型至关重要。在本文中，基于具有多个机动数据集的支持向量机完成了扰动下的3自由度水动力模型的识别过程。该算法在清洁船模型上进行了验证，结果与参考具有良好的拟合度。在不同海况下进行实验以研究湍流对识别性能的影响。泛化结果表明，在温和和中等环境中识别的模型偏差小于 10%，被认为是可以接受的。扰动越高，识别模型的保真度越低。在扰动下识别的模型可以为运行决策系统提供不同级别的可靠支持。