Manoeuvring simulation of catamaran by using implicit models based on support vector machines

Luo, Weilin; Moreira, L.; Soares, C. Guedes

doi:10.1016/j.oceaneng.2014.03.008

Cited by 39 publications

(11 citation statements)

References 18 publications

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“…It was only introduced for ship motion modelling in the 1960s, and it became more developed recently [2][3][4][5][6][7][8]. It is also possible to develop methods based on artificial intelligence techniques [9,10], but they do not include explicit information on the physics of the process and thus the methods that identify the parameters of mathematical models are often preferred as these models can easily be used to simulate the ship trajectories [11,12].…”

Section: Introductionmentioning

confidence: 99%

Robust Parameter Estimation of an Empirical Manoeuvring Model Using Free-Running Model Tests

Costa

Soares

2021

JMSE

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The work presents the identification and validation of the hydrodynamic coefficients for the surge, sway, and yaw motion. This is performed in two ways: using simulated data and free-running test data. The identification and validation with the simulation data are carried out using a 25° turning test and a 20°−20° zigzag manoeuvring test. For the free-running test data, two zigzag manoeuvres are used: 30°−30° zigzag for identification and 20°−20° zigzag for validation. A nonlinear manoeuvring model is proposed based on the standard Euler equations, and the hydrodynamic coefficients are computed using empirical equations. To obtain robust results, the truncated singular value decomposition is employed to diminish the multicollinearity and the parameter uncertainties due to noise. The validation is carried out by comparing the result of the measured values with the predictions obtained using the manoeuvring models. Finally, a sensitivity analysis for the simulation data is performed to understand the influence of the parameters in the manoeuvres.

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Section: Introductionmentioning

confidence: 99%

Robust Parameter Estimation of an Empirical Manoeuvring Model Using Free-Running Model Tests

Costa

Soares

2021

JMSE

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“…Many studies have been conducted on SI for ship maneuvers using black-box models, such as support vector machine [24][25][26][27], random forest [28], and neural networks (NNs) [29][30][31][32][33][34][35]. In particular, an NN can approximate various functions using a set of the appropriate number of parameters, as shown in the universal approximation theorem (UAT) [36][37][38], and the gradient can easily be calculated using the backpropagation (BP) method [39].…”

Section: Introductionmentioning

confidence: 99%

On Neural Network Identification for Low-Speed Ship Maneuvering Model

Wakita,

Maki,

Naoya

et al. 2021

Preprint

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Several studies on ship maneuvering models have been conducted using captive model tests or computational fluid dynamics (CFD) and physical models, such as the maneuvering modeling group (MMG) model. A new system identification method for generating a low-speed maneuvering model using recurrent neural networks (RNNs) and free running model tests is proposed in this study. We especially focus on a low-speed maneuver such as the final phase in berthing to achieve automatic berthing control. Accurate dynamic modeling with minimum modeling error is highly desired to establish a model-based control system. We propose a new loss function that reduces the effect of the noise included in the training data. Besides, we revealed the following facts -an RNN that ignores the memory before a certain time improved the prediction accuracy compared with the "standard" RNN, and the random maneuver test was effective in obtaining an accurate berthing maneuver model. In addition, several low-speed free running model tests were performed for the scale model of the M.V. Esso Osaka. As a result, this paper showed that the proposed method using a neural network model could accurately represent low-speed maneuvering motions.

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“…System identification is a mature technique for building mathematical models of dynamical systems from measured data [16]. Now it has been widely used for estimation the hydrodynamics coefficients for marine vessels [8,[17][18][19][20][21][22][23]. Least Square (LS) is one of the most widely used methods.…”

Section: Introductionmentioning

confidence: 99%

Comparing generic and vectorial nonlinear manoeuvring models and parameter estimation using optimal truncated least square support vector machine

Hassani

Soares

2020

Applied Ocean Research

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Manoeuvring simulation of catamaran by using implicit models based on support vector machines

Cited by 39 publications

References 18 publications

Robust Parameter Estimation of an Empirical Manoeuvring Model Using Free-Running Model Tests

Robust Parameter Estimation of an Empirical Manoeuvring Model Using Free-Running Model Tests

On Neural Network Identification for Low-Speed Ship Maneuvering Model

Comparing generic and vectorial nonlinear manoeuvring models and parameter estimation using optimal truncated least square support vector machine

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