首页 | 本学科首页   官方微博 | 高级检索  
     


Multi-innovation auto-constructed least squares identification for 4 DOF ship manoeuvring modelling with full-scale trial data
Affiliation:1. School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;2. CCCC Fourth Harbor Engineering Institute Co., Ltd., Guangzhou 510230, China;3. Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China;4. State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Abstract:This research is concerned with the problem of 4 degrees of freedom (DOF) ship manoeuvring identification modelling with the full-scale trial data. To avoid the multi-innovation matrix inversion in the conventional multi-innovation least squares (MILS) algorithm, a new transformed multi-innovation least squares (TMILS) algorithm is first developed by virtue of the coupling identification concept. And much effort is made to guarantee the uniformly ultimate convergence. Furthermore, the auto-constructed TMILS scheme is derived for the ship manoeuvring motion identification by combination with a statistic index. Comparing with the existing results, the proposed scheme has the significant computational advantage and is able to estimate the model structure. The illustrative examples demonstrate the effectiveness of the proposed algorithm, especially including the identification application with full-scale trial data.
Keywords:Ship modelling  Multi-innovation identification  4 degrees of freedom motions  Full-scale trial
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号