Parametric Identification of Ship's Maneuvering Motion Based on Improved Least Square Method

Abstract

In order to solve the problem of parameter identification of ship's Maneuvering Motion, a fast convergent iterative least squares algorithm is presented considering nonlinear and non-stationary characteristics of ship motion in time domain. The speed and precision of parameter identification have been improved using this algorithm. Firstly, the models of ship's first-order and second- order nonlinear response motion were established and made discrete. Then, parameters identification were made using new least squares algorithm which was improved by using iterative learning and introducing p-type learning rate. And the convergence of the algorithm was also analyzed. A Z-Type simulation experiment of first and second order non-linear model of a certain type of ship was conducted using the numerical methods above. At last, the results were compared with the experimental data from the free running model test carried out in Hamburg, Germany pool (HSVA). The experimental results demonstrate that the algorithm is feasible and effective.