Nonparametric identification of nonlinear ship roll motion by using the motion response in irregular waves

Hou, Xian-Rui; Zou, Zao-Jian; Liu, C.

doi:10.1016/j.apor.2018.02.004

Cited by 20 publications

(5 citation statements)

References 22 publications

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“…Ship motion control is an important field that combines navigation science and technology. Its ultimate purpose is to improve the level of ship automation and intelligence, and to ensure the safety, economy and comfort of a ship’s navigation [ 1 , 2 , 3 ]. Meanwhile, with the continuous development of technology and the extension of the field of ship application, the model of a traditional ship is developing towards miniaturization, speediness and intellectualization, and a new surface carrier has been developed—Unmanned Surface Vehicle (USV) [ 4 , 5 , 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Modeling and Identification for Vector Propulsion of an Unmanned Surface Vehicle: Three Degrees of Freedom Model and Response Model

Wang

Fan

et al. 2018

Sensors

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This paper presents a complete scheme for research on the three degrees of freedom model and response model of the vector propulsion of an unmanned surface vehicle. The object of this paper is “Lanxin”, an unmanned surface vehicle (7.02 m × 2.6 m), which is equipped with a single vector propulsion device. First, the “Lanxin” unmanned surface vehicle and the related field experiments (turning test and zig-zag test) are introduced and experimental data are collected through various sensors. Then, the thrust of the vector thruster is estimated by the empirical formula method. Third, using the hypothesis and simplification, the three degrees of freedom model and the response model of USV are deduced and established, respectively. Fourth, the parameters of the models (three degrees of freedom model, response model and thruster servo model) are obtained by system identification, and we compare the simulated turning test and zig-zag test with the actual data to verify the accuracy of the identification results. Finally, the biggest advantage of this paper is that it combines theory with practice. Based on identified response model, simulation and practical course keeping experiments are carried out to further verify feasibility and correctness of modeling and identification.

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Section: Introductionmentioning

confidence: 99%

Modeling and Identification for Vector Propulsion of an Unmanned Surface Vehicle: Three Degrees of Freedom Model and Response Model

Wang

Fan

et al. 2018

Sensors

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“…To identify hydrodynamics models, numerical calculation [14], model tests [15], and system identification [16] are three popular methods. Yet, it is difficult to achieve the tradeoff between cost and accuracy in the numerical calculation and model tests.…”

Section: Introductionmentioning

confidence: 99%

Advanced Marine Craft Model Identification via Multi-Kernel Weighted Least Square Support Vector Machine and Characteristic Model Techniques

Pei

Zhong

et al. 2023

JMSE

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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.

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“…These motions can lead a bad influence on the seaboard operations, like the safe navigation of the ship, the take-off and landing of carrier-based aircraft, the ship replenishment activities, etc. [1][2][3] . In that case, using the inertial measurement to measure ship motion and achieve 5 to 10 seconds of ship-motion prediction, has great significance for enhancing seaboard operational safety, improving ship motion control effects and ship combat effectiveness 4 .…”

Section: Introductionmentioning

confidence: 99%

A ship-motion prediction algorithm based on modified covariance method and neural networks

Ding¹

2022

International Conference on Computer Application and Information Security (ICCAIS 2021)

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In order to provide accurate ship-motion prediction for safe seaboard operations, this paper presents a new ship-motion prediction algorithm based on modified covariance (MCOV) method and neural networks. This algorithm firstly uses the MCOV method to analysis spectrums of the ship motion. And then, major spectrums of the ship motion are used to find the ship motion model by using the Neural Network (NN). Simulation results show that this method can present a confidence performs on ship-motion prediction.

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Nonparametric identification of nonlinear ship roll motion by using the motion response in irregular waves

Cited by 20 publications

References 22 publications

Modeling and Identification for Vector Propulsion of an Unmanned Surface Vehicle: Three Degrees of Freedom Model and Response Model

Modeling and Identification for Vector Propulsion of an Unmanned Surface Vehicle: Three Degrees of Freedom Model and Response Model

Advanced Marine Craft Model Identification via Multi-Kernel Weighted Least Square Support Vector Machine and Characteristic Model Techniques

A ship-motion prediction algorithm based on modified covariance method and neural networks

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