Advanced Marine Craft Model Identification via Multi-Kernel Weighted Least Square Support Vector Machine and Characteristic Model Techniques
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Published:2023-05-22
Issue:5
Volume:11
Page:1091
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ISSN:2077-1312
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Container-title:Journal of Marine Science and Engineering
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language:en
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Short-container-title:JMSE
Author:
Pei Tianqi1, Yu Caoyang1ORCID, Zhong Yiming1, Cao Junjun1ORCID, Lian Lian12
Affiliation:
1. School of Oceanography, Shanghai Jiao Tong University, Shanghai 200030, China 2. State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Abstract
This paper combines the piecewise Cubic Hermite (CH) interpolation algorithm and the weighted least square support vector machine (WLS-SVM) to improve identification accuracy for marine crafts built based on the characteristic model. The characteristic model is first used to describe the heading dynamics of marine crafts and is a superior model to the traditional response model in both accuracy and complexity. Especially in order to improve identification accuracy, a CH-based data preprocessing strategy is utilized to densify and smooth data for further accurate identification. Subsequently, the combination of the linear kernel function and the Gaussian kernel function is introduced in the conventional WLS-SVM method, which renders global and local performance improvements compared with the conventional WLS-SVM method. Finally, informative maneuvers composed of Zigzag and Sine are carried out to test the performance of the improved identification method. Compared to the conventional LS-SVM method based on the response model, the root mean square error of the proposed CH-MK-WLS-SVM method based on the characteristic model is reduced by an order of magnitude in the presence of sensor noise.
Funder
National Natural Science Foundation of China Natural Science Foundation of Shanghai Oceanic Interdisciplinary Program of Shanghai Jiao Tong University Shanghai Underwater Robot Engineering Technology Innovation Center
Subject
Ocean Engineering,Water Science and Technology,Civil and Structural Engineering
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