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Unscented Kalman Filter trained neural networks based rudder roll stabilization system for ship in waves

Citation

Wang, Yuanyuan and Chai, S and Khan, FI and Nguyen, HD, Unscented Kalman Filter trained neural networks based rudder roll stabilization system for ship in waves, Applied Ocean Research, 168 pp. 26-38. ISSN 0141-1187 (2017) [Refereed Article]

Copyright Statement

Copyright 2017 Elsevier Ltd.

DOI: doi:10.1016/j.apor.2017.08.007

Abstract

The large roll motion of ships sailing in the seaway is undesirable because it may lead to the seasickness of crew and unsafety of vessels and cargoes, thus it needs to be reduced. The aim of this study is to design a rudder roll stabilization system based on Radial Basis Function Neural Network (RBFNN) control algorithm for ship advancing in the seaway only through rudder actions. In the proposed stabilization system, the course keeping controller and the roll damping controller were accomplished by utilizing modified Unscented Kalman Filter (UKF) training algorithm, and implemented in parallel to maintain the orientation and reduce roll motion simultaneously. The nonlinear mathematical model, which includes manoeuvring characteristics and wave disturbances, was adopted to analyse ship’s responses. Various sailing states and the external wave disturbances were considered to validate the performance and robustness of the proposed roll stabilizer. The results indicate that the designed control system per-forms better than the Back Propagation (BP) neural networks based control system and conventional Proportional-Derivative (PD) based control system in terms of reducing roll motion for ship in waves.

Item Details

Item Type:Refereed Article
Keywords:rudder roll stabilization system, neural networks, unscented Kalman filter training, trajectory tracking
Research Division:Engineering
Research Group:Maritime Engineering
Research Field:Marine Engineering
Objective Division:Manufacturing
Objective Group:Transport Equipment
Objective Field:Automotive Equipment
Author:Wang, Yuanyuan (Mr Yuanyuan Wang)
Author:Chai, S (Associate Professor Shuhong Chai)
Author:Khan, FI (Professor Faisal Khan)
Author:Nguyen, HD (Dr Hung Nguyen)
ID Code:121445
Year Published:2017
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2017-09-28
Last Modified:2017-11-13
Downloads:0

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