This paper explores a fast and efficient method for identifying and modeling ship
maneuvering motion, and conducts a comprehensive experiment. Through the ship …

This paper explores a highly accurate identification modeling approach for the ship
maneuvering motion with fullscale trial. A multi-innovation gradient iterative (MIGI) approach …

This work explores an adaptive moment estimation locally weighted learning (AME-LWL)
method to develop a novel high-precision non-parametric modeling technology for ship …

A fast and accurate nonparametric modeling method based on local Gaussian process
regression (LGPR) is proposed for the identification modeling and prediction of ship …

This paper aims to study the nonparametric modeling and control of ship steering motion.
Firstly, the black box response model is derived based on the Nomoto model. Then, the …

The system identification of a ship dynamics model is crucial for the intelligent navigation
and design of the ship's controller. The fluid dynamic effect and the complicated geometry of …

This paper explores a novel nonparametric identification modeling technique for ship
maneuvering system. In order to solve the over-learning or under-learning problem which …

Nonparametric modeling is a commonly used data-driven method for modeling ship
maneuvering motion, and its performance depends on reliable training data. The training …

A robust and easy-to-operate method based on Gaussian process regression (GPR) is
proposed for nonparametric modeling of ship maneuvering in waves. The wave parameters …

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 …