In this paper, a fine-tuning method of the parameters in the MMG model for the real-scale ship is proposed. In the proposed method, all of the arbitrarily indicated target parameters of the MMG model are tuned simultaneously in the framework of SI using time series data of real-sale ship maneuvering motion data to steadily improve the accuracy of the MMG model. Parameter tuning is formulated as a minimization problem of the deviation of the maneuvering motion simulated with given parameters and the real-scale ship trials, and the global solution is explored using CMA-ES. By constraining the exploration ranges to the neighborhood of the previously determined parameter values, the proposed method limits the output in a realistic range. The proposed method is applied to the tuning of 12 parameters for a container ship with five different widths of the exploration range. The results show that, in all cases, the accuracy of the maneuvering simulation is improved by applying the tuned parameters to the MMG model, and the validity of the proposed parameter fine-tuning method is confirmed.

翻译：本文提出了一种针对实尺度船舶的MMG模型参数微调方法。在该方法中，利用实船操纵运动的时间序列数据，在系统辨识框架下同时对MMG模型中所有任意指定的目标参数进行调优，以稳步提升模型精度。参数调优被形式化为一个最小化问题，目标为缩小给定参数模拟的操纵运动与实船试验之间的偏差，并采用协方差矩阵自适应进化策略探索全局最优解。通过将探索范围约束在先前确定参数值的邻域内，所提方法确保输出结果处于合理区间。将该方法应用于某集装箱船12个参数的调优，并测试了五种不同宽度的探索范围。结果表明，在所有情形下，将调优后的参数应用于MMG模型均能提升操纵模拟精度，验证了所提参数微调方法的有效性。