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OA

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.