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Multi-innovation auto-constructed least squares identification for 4 DOF ship manoeuvring modelling with full-scale
Guoqing Zhang1, Xianku Zhang1, Hongshuai Pang2
1Navigation College, Dalian Maritime University, 1 Linghai Road, Dalian 116026, Liaoning, 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.
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