Journal of Applied Science and Engineering

Published by Tamkang University Press

1.30

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2.10

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Qiang Zhang This email address is being protected from spambots. You need JavaScript enabled to view it.1,2, Yancai Hu1 , Aiqin Wang1 and Na Jiang1

1Navigation College, Shandong Jiaotong University, Weihai, P.R. China
2Navigation College, Dalian Maritime University, Dalian, P.R. China


 

Received: September 5, 2016
Accepted: February 12, 2017
Publication Date: September 1, 2017

Download Citation: ||https://doi.org/10.6180/jase.2017.20.2.03  

ABSTRACT


Based on the dynamic surface control (DSC) and neural networks (NNs), an adaptive control algorithm with Nussbaum gain is proposed for the nonlinear ship course-keeping control system. This approach solves the uncertainties of the ship course-keeping control system, reduces the effect of the external disturbances, simplifies the control laws and overcomes the problem of ‘explosion of complexity’ inherent in the backstepping method. Furthermore, the Nussbaum function introduced into controller solves the problems of direction-unknown control gains, and avoids the singular problem of controller. The results of simulation show that the proposed control algorithm is effective.


Keywords: Ship Course-keeping, Uncertain Parameters, Dynamic Surface Control, Neural Networks, Nussbaum Gain


REFERENCES


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