基于模型参考和随机森林算法的船舶操纵运动辨识建模

采用模型参考和机器学习相结合的辨识建模结构对船舶操纵运动建模.首先，选择已公开模型作为参考模型；其次，使用相似准则把被辨识船舶速度转移到参考模型；最后，使用随机森林模型构建被辨识船舶加速度和参考模型加速度的映射关系.随机森林模型具有训练快、避免过拟合的优点.使用船模试验数据进行辨识建模和模型验证，并与MMG模型和BPNN进行对比.结果表明，该辨识方法具有较强的可行性、预报能力和泛化能力.
The modeling structure of model reference and machine learning was used for the ship maneuvering motion modeling. Firstly, the open model was selected as a reference model. Secondly, the similarity criterion was used to transfer the speed of the identified ship to the reference model. Finally, the random forest model was used to construct the mapping relationship between identified acceleration and reference model acceleration. The random forest model has the advantages of fast training and avoiding overfitting. The ship model test data was used for identification modeling and model verification, and compared with MMG model and BPNN. Results show that the proposed method has strong feasibility, prediction ability and generalization ability.