Rudder Roll Damping Autopilot Using Dual Extended Kalman Filter–Trained Neural Networks for Ships in Waves

作     者：Yuanyuan Wang Hung Duc Nguyen 

作者机构：National Center for Maritime Engineering and HydrodynamicsAustralian Maritime College University of Tasmania 

基　　金：a part of the project titled ’Intelligent Control for Surface Vessels Based on Kalman Filter Variants Trained Radial Basis Function Neural Networks’ partially funded by the Institutional Grants Scheme(TGRS 060515)of Tasmania Australia 

出 版 物：《Journal of Marine Science and Application》 (船舶与海洋工程学报（英文版）)

年 卷 期：2019年第18卷第4期

页      码：510-521页

摘      要：The roll motions of ships advancing in heavy seas have severe impacts on the safety of crews,vessels,and cargoes;thus,it must be *** study presents the design of a rudder roll damping autopilot by utilizing the dual extended Kalman filter(DEKF)trained radial basis function neural networks(RBFNN)for the surface *** autopilot system constitutes the roll reduction controller and the yaw motion controller implemented in *** analyzing the advantages of the DEKF-trained RBFNN control method theoretically,the ship’s nonlinear model with environmental disturbances was employed to verify the performance of the proposed stabilization *** sailing scenarios were conducted to investigate the motion responses of the ship in *** results demonstrate that the DEKF RBFNN based control system is efficient and practical in reducing roll motions and following the path for the ship sailing in waves only through rudder actions.

主 题 词：Rudder roll damping Autopilot Radial basis function Neural networks Dual extended Kalman filter training Intelligent control Path following Advancing in waves 

学科分类：08[工学] 082402[082402] 0824[工学-林业工程类] 082401[082401] 

核心收录：

D　O　I：10.1007/s11804-019-00111-8

馆 藏 号：203801530...