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作者机构:Dalian Maritime Univ Naut Dynam Simulat & Control Lab Dalian 116026 Liaoning Peoples R China Univ Elect Sci & Technol China Sch Automat Engn Chengdu 611731 Sichuan Peoples R China
出 版 物:《OCEAN ENGINEERING》 (海洋工程)
年 卷 期:2022年第261卷
核心收录:
学科分类:07[理学] 0707[理学-海洋科学] 0824[工学-船舶与海洋工程] 0814[工学-土木工程]
基 金:National Natural Science Foundation of China [51779029, 61903092, 51939001] Fundamental Research Funds for the Central Universities, China Ministry of Industry and Information Technology, China Natural Science Foundation of Sichuan Province [2022NSFSC0891] China Postdoctoral Science Foundation [2022T150096]
主 题:Ship maneuvering motion Marine simulator Non-parametric modeling Locally weighted learning Moment estimation
摘 要:This work explores an adaptive moment estimation locally weighted learning (AME-LWL) method to develop a novel high-precision non-parametric modeling technology for ship maneuvering motion and conducts full-scale tests. First, a non-parametric learning framework is used to avoid unmodeled dynamics and parameter drift;second, Tikhonov method and multi-innovation adaptive moment estimation (AME) algorithm are proposed for local model adaptive learning;third, considering rudder and propeller joint effect for hydrodynamic forces, a multiple-input multiple-output (MIMO) continuous-time model is established to realize ship motion dynamic simulation under interferences. This scheme leads to a high-precision continuous-time non-parametric model that can be easily implemented, robust, less time-consuming and insensitive to initial parameters. In order to verify the properties of AME-LWL non-parametric model, Mariner vessel and Delta Linda tug two ship types were taken as objects for simulation experiments of comprehensive maneuvering tests, rudder-propeller coupling tests and wind interferences test. Finally, simulation results verify the effectiveness of the proposed scheme.