System identification of ship dynamic model based on Gaussian process regression with input noise
Y Xue, Y Liu, C Ji, G Xue, S Huang - Ocean Engineering, 2020 - Elsevier
As a critical step designing the ship controller and the maritime traffic simulator, the system
identification of a ship dynamic model from input-output data is a promising direction …
identification of a ship dynamic model from input-output data is a promising direction …
Online identification of a ship maneuvering model using a fast noisy input Gaussian process
The design of maritime traffic simulators, model-based controllers, and maritime
autonomous surface ships require accurate ship dynamic models. Using different …
autonomous surface ships require accurate ship dynamic models. Using different …
Identification modeling of ship maneuvering motion based on local Gaussian process regression
ZL Ouyang, G Chen, ZJ Zou - Ocean Engineering, 2023 - Elsevier
A fast and accurate nonparametric modeling method based on local Gaussian process
regression (LGPR) is proposed for the identification modeling and prediction of ship …
regression (LGPR) is proposed for the identification modeling and prediction of ship …
Non-parametric dynamic system identification of ships using multi-output Gaussian Processes
A novel application of non-parametric system identification algorithm for a surface ship has
been employ on this study with the aim of modelling ships dynamics with low quantity of …
been employ on this study with the aim of modelling ships dynamics with low quantity of …
Black-box modeling of ship maneuvering motion based on Gaussian process regression with wavelet threshold denoising
SY Liu, ZL Ouyang, G Chen, X Zhou, ZJ Zou - Ocean Engineering, 2023 - Elsevier
A system identification method based on Gaussian progress regression (GPR) combined
with wavelet threshold denoising (WT) is proposed for identifying the black-box model of …
with wavelet threshold denoising (WT) is proposed for identifying the black-box model of …
Real-time parameter identification of ship maneuvering response model based on nonlinear Gaussian Filter
S Wang, L Wang, N Im, W Zhang, X Li - Ocean Engineering, 2022 - Elsevier
In order to solve the problem of parameter identification of nonlinear ship motion model in
ship autonomous navigation control, a real-time parameter identification method based on …
ship autonomous navigation control, a real-time parameter identification method based on …
Nonparametric modeling of ship maneuvering motion based on Gaussian process regression optimized by genetic algorithm
ZL Ouyang, ZJ Zou - Ocean Engineering, 2021 - Elsevier
A novel method, Gaussian process regression optimized by genetic algorithm (GA-GPR), is
proposed for nonparametric modeling of ship maneuvering motion. A genetic algorithm with …
proposed for nonparametric modeling of ship maneuvering motion. A genetic algorithm with …
Adaptive hybrid-kernel function based Gaussian process regression for nonparametric modeling of ship maneuvering motion
ZL Ouyang, ZJ Zou, L Zou - Ocean Engineering, 2023 - Elsevier
A novel adaptive hybrid-kernel function based Gaussian process regression (AHKGPR) is
proposed for nonparametric modeling of ship maneuvering motion. With the aid of Gaussian …
proposed for nonparametric modeling of ship maneuvering motion. With the aid of Gaussian …
Data-driven model predictive control for ships with Gaussian process
Nonlinear and underactuated ship maneuvering model is the main difficulty in ship motion
control, and model predictive control (MPC) offers a great choice to handle this problem …
control, and model predictive control (MPC) offers a great choice to handle this problem …
Kernel-based support vector regression for nonparametric modeling of ship maneuvering motion
A nonparametric identification method based on ν ('nu')-support vector regression (ν-SVR) is
proposed to establish robust models of ship maneuvering motion in an easy-to-operate way …
proposed to establish robust models of ship maneuvering motion in an easy-to-operate way …