Journal
CHINA OCEAN ENGINEERING
Volume 32, Issue 3, Pages 288-300Publisher
CHINA OCEAN PRESS
DOI: 10.1007/s13344-018-0030-0
Keywords
multi-innovation gradient iterative (MIGI); locally weighted learning (LWL); identification; nonlinearship maneuvering; full-scale trial
Funding
- National High Technology Research and Development Program of China (863 Program) [2015AA016404]
- National Natural Science Foundation of China [51109020, 51179019, 51779029]
- Fundamental Research Program for Key Laboratory of the Education Department of Liaoning Province [LZ2015006]
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This paper explores a highly accurate identification modeling approach for the ship maneuvering motion with fullscale trial. A multi-innovation gradient iterative (MIGI) approach is proposed to optimize the distance metric of locally weighted learning (LWL), and a novel non-parametric modeling technique is developed for a nonlinear ship maneuvering system. This proposed method's advantages are as follows: first, it can avoid the unmodeled dynamics and multicollinearity inherent to the conventional parametric model; second, it eliminates the over-learning or underlearning and obtains the optimal distance metric; and third, the MIGI is not sensitive to the initial parameter value and requires less time during the training phase. These advantages result in a highly accurate mathematical modeling technique that can be conveniently implemented in applications. To verify the characteristics of this mathematical model, two examples are used as the model platforms to study the ship maneuvering.
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