On Neural Network Identification for Low-Speed Ship Maneuvering Model

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.Comment: 13 pages, 7 figures, submitted to Journal of Marine Science and Technology for peer-revie

A comparison of ship manoeuvrability models to approximate ship navigation trajectories

It is essential to describe a ship’s manoeuvrability for various applications, e.g. optimal control of unmanned\ua0surface vehicles (USVs). In this study, the capability of two recognised manoeuvrability models to predict\ua0ships’ trajectories is investigated based on both simulation and open-water experiment test data. The\ua0parameters of these models are estimated by a statistical learning method. The goodness of the two\ua0estimated models for describing a merchant ship’s manoeuvrability is first studied using her\ua0manoeuvring simulation data. Then, experimental manoeuvring tests to use a USV in open water with\ua0wind and drifting effects are used to check the conventional model identification procedures. Finally,\ua0some modifications and adjustments are proposed to improve the conventional procedures. It shows\ua0that the proposed procedures can accurately derive the ship’s manoeuvrability based on experimental data

A study on the implementation of nonlinear Kalman filter applying MMG model

Many technologies need to be established to realize autonomous ships. In particular, accurate state estimation in real time is one of the most important technologies. In the ship and ocean engineering fields, there have been many studies on state estimation using nonlinear Kalman filters. Several methods have been proposed for nonlinear Kalman filters. However, there is insufficient verification on the selection of which filter should be applied among them. Therefore, this study aims to validate the filter selection to provide a guideline for filter selection. The effects of modeling error, observation noise, and type of maneuvers on the estimation accuracy of the unscented Kalman filter (UKF) and ensemble Kalman filter (EnKF) used in this study were investigated. In addition, it was verified whether filtering could be performed in real time. The results show that modeling error significantly impacts the estimation accuracy of the UKF and EnKF. However, the observation noise and types of maneuvers did not have an impact like the modeling error. Thus, we obtained the guideline that UKF and EnKF should be used differently depending on the required computation time. We also obtained that keeping the modeling error sufficiently small is essential to improving the estimation accuracy.The version of record of this article, first published in Journal of Marine Science and Technology (Japan), is available online at Publisher’s website: https://doi.org/10.1007/s00773-023-00953-

Prevention of extreme roll motion through measurements of ship's motion responses

PhD ThesisExploring the operational links between a sea state and a ship’s heading and speed provides the opportunity to continuously monitor dynamic stability behaviour; and hence to avoid significant changes of stability in adverse weather. Significant changes of stability at sea can lead to dangerous transient situations and eventually stability failure. Despite its importance, the current intact stability (IS) criteria do not evaluate or consider the dynamics of the motion responses of a vessel in a wave environment. In this thesis, the full six degrees of freedom motion responses of two models have been tested in irregular waves under intact vessel conditions. The general modelling approach for a mathematical model was based on numerical simulations at different speeds, sea conditions and angle of heading relative to the waves. In the second model, a physical model was tested in a towing tank under similar simulated environmental conditions to that employed for the first model. The investigation was limited to the effects of encountered frequency components and the associated magnitude of energy of the ship’s motion responses. An analysis of heave, pitch and roll motion confirmed the vulnerability of the model to certain wave-excited frequency ranges. This particular range of frequency results in an adverse effect on the amplitude of the responses, and these were closely related to the natural mode frequencies and related coupling effects. It was confirmed that the roll motion maintains its highest oscillation amplitude at around the natural frequency in all sea conditions regardless of ship heading angles. It was also observed that spectral analysis of the heave and pitch responses revealed the wave peak frequency. Roll is magnified when the peak frequency of the waves approaches the natural roll frequency, therefore keeping them sufficiently apart avoids potentially large motion responses. It was concluded that peak frequency and associated magnitude are the two important inherent characteristics of motion responses. Detection of the most influential parameters of encountered waves through measurements of heave and pitch responses could be utilised to provide a method to limit the large motion of a ship at sea. The measurement of waves whilst a ship is underway is a major challenge, whereas ship motion, which is relatively easily measured, is a good indirect reflection of the encountered wave characteristics and which can be measured, stored and analysed using Prevention of extreme roll motion through measurements of ship’s motion responses iv on-board equipment. Motion responses are considered as continuous signals with a time-dependent spectral content, and signal processing is a suitable technique for detection, estimation and analysis of recorded time-varying signals. The method is fast enough to be considered as an on-board real-time monitoring of dynamic stability. Signal processing techniques are used in the detection and estimation of the influential parameters of a wave environment through the analysis of motion responses. The variables of the system were detected by spectral analysis of the heave and pitch motions. These variables are the peak wave frequencies and associated magnitudes which can cause a large roll motion when reasonably close to the ship’s natural roll frequency. The instantaneous frequency (IF) present in the signal is revealed through spectral analysis of short-time Fourier transforms (STFT) in less than a minute. The IF is a parameter of practical importance which can be used in real-time on-board decision making processes to enable the vessel to take actions in order to avoid large roll motions

Rigid Body Ship Dynamics

It is common today that operational data is recorded onboard ships within the Internet of Ships (IoS) paradigm. This enables the possibility to build ship digital twins as digital copies of the real ships. Predicting the ship’s motions with ship dynamics could be an important sub-component of these ship digital twins.A model for the ship’s dynamics can be identified based on observations of the ship’s motions. The identified model will have model uncertainty due to imperfections and idealizations made in physical model formulations as well as uncertainty from errors in the measurement data, which can be very pronounced when using full scale operational data. It is easier to develop accurate models with low model uncertainty using data obtained in a controlled laboratory environment where the measurement errors are much lower, especially in calm water conditions. The prediction model should be able to describe scenarios that a ship has never encountered before, which is possible if much of the underlying physics has been identified. Grey-box modelling is a technique which combines operational data with physical principles to achieve this. The objective of this thesis is to develop system identification methods for grey box models with good generalization of the model scale rigid body ship dynamics in calm waters. A model development procedure is proposed to handle the model uncertainty through the selection of candidate models based on a hold-out evaluation procedure. The measurement noise is handled by an iterative preprocessor, which uses an extended Kalman filter (EKF) and a Rauch Tung Striebel (RTS) smoother that uses an initially estimated predictor model from semi-empirical formulas. It is demonstrated that the ship’s roll motion with high accuracy can be described using a quadratic damping model. For the more complex manoeuvring models, multicollinearity is a large problem where the appropriate complexity needs to be selected with the bias-variance trade-off between underfitting or overfitting the data. Hold-out turning circle tests were predicted with high accuracy for the wPCC and KVLCC2 test case ships with models from the proposed development procedure and parameter estimation method.The proposed methods can produce prediction models with high generalization given that a suitable model structure has been selected from the candidate models and an appropriate split in the hold-out evaluation of the model development process has been applied

Numerical simulation of focusing wave interaction with FPSO-like structure using FNPT-NS Solver

The paper presents the numerical results for the focusing wave interacting with a FPSO-like structure using the FNPT-NS solver. The case configuration is defined by CCP-WSI blind test in ISOPE 2018. The incident waves are uni-directional focusing waves with different spectrum bandwidths and wave heights. The structure is fixed and subjected to different heading. The numerical model used in present work is a hybrid model combining a fully nonlinear potential theory (FNPT) and a Navier-Stokes （ NS ） theory using a domain-decomposition approach. The Quasi Arbitrary Lagrangian Eulerian method is used to solve the FNPT in a large domain covering the entire wave basin with the same size as the experiments. For the later, the OpenFOAM (interDyMFoam) is utilized to achieve the solution near the structures, where the viscous effect may be important. In addition, the wave generation and the convergence of the hybrid model are discussed in detail