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Course Control of Underactuated Ship Based on Nonlinear Robust Neural Network Backstepping Method
Joint Authors
Zhou, Jiajia
Yuan, Junjia
Meng, Hao
Zhu, Qidan
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-02-24
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
The problem of course control for underactuated surface ship is addressed in this paper.
Firstly, neural networks are adopted to determine the parameters of the unknown part of ideal virtual backstepping control, even the weight values of neural network are updated by adaptive technique.
Then uniform stability for the convergence of course tracking errors has been proven through Lyapunov stability theory.
Finally, simulation experiments are carried out to illustrate the effectiveness of proposed control method.
American Psychological Association (APA)
Yuan, Junjia& Meng, Hao& Zhu, Qidan& Zhou, Jiajia. 2016. Course Control of Underactuated Ship Based on Nonlinear Robust Neural Network Backstepping Method. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1099625
Modern Language Association (MLA)
Yuan, Junjia…[et al.]. Course Control of Underactuated Ship Based on Nonlinear Robust Neural Network Backstepping Method. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1099625
American Medical Association (AMA)
Yuan, Junjia& Meng, Hao& Zhu, Qidan& Zhou, Jiajia. Course Control of Underactuated Ship Based on Nonlinear Robust Neural Network Backstepping Method. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-11.
https://search.emarefa.net/detail/BIM-1099625
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099625