集美大学学报（自然科学版）2026，Vol.31Issue(4)：435-448,14.DOI:10.19715/j.jmuzr.2026.04.05
基于改进野马算法的船舶二阶非线性响应型模型参数辨识
Parameter Identification of Ship Maneuvering Response Models Based on an Improved Wild Horse Optimization Algorithm
摘要
Abstract
Aiming at the problems of low identification accuracy,poor generalization of identification re-sults,and complex identification process existing in the parameter identification research of the existing ship second-order nonlinear response model,this paper proposes a parameter identification method based on the im-proved wild horse optimization(IWHO)algorithm.The parameter identification process is optimized by emplo-ying the IWHO algorithm.A Tent inertial weight based on the hunger games mechanism is integrated to regulate global exploration and local exploitation capabilities.Refraction mirror learning strategy and operator perturba-tion are incorporated to accelerate convergence and prevent stagnation in local optima,a method for identifying parameters of a ship's second-order nonlinear response model is constructed,thereby improving the identifica-tion efficiency and accuracy of ship response model parameters.The Mariner ship model is taken as the re-search object.The IWHO is applied for parameter identification of the ship's second-order nonlinear response model,which is compared with the existing extended Kalman filter(EKF)algorithm to verify the superiority of the proposed algorithm in this scenario.The research results show that the parameters of the ship maneuvering response model identified based on the IWHO can control the root mean square error(RMSE)of the rudder angle at approximately 1°,and the correlation coefficient of the position coordinates approaches 1,which is su-perior to those of the wild horse optimization(WHO)algorithm and the EKF algorithm.关键词
参数辨识/响应型模型/船舶运动建模/改进野马算法Key words
unmanned parameter identification/response model/ship motion modeling/improved wild horse optimizer(IWHO)分类
交通工程引用本文复制引用
顾民,甄荣,王树武,张钊..基于改进野马算法的船舶二阶非线性响应型模型参数辨识[J].集美大学学报（自然科学版）,2026,31(4):435-448,14.基金项目
国家自然科学基金项目(52001134) （52001134）
福建省自然科学基金项目(2024J01102) （2024J01102）
