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Mathematical Problems in Engineering
Volume 2013, Article ID 530162, 9 pages
Research Article

Adaptive Neural Network Control with Backstepping for Surface Ships with Input Dead-Zone

College of Automation, Harbin Engineering University, 150001 Harbin, China

Received 17 June 2013; Revised 27 August 2013; Accepted 28 August 2013

Academic Editor: Jyh-Horng Chou

Copyright © 2013 Guoqing Xia et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper addresses the problem of adaptive neural network controller with backstepping technique for fully actuated surface vessels with input dead-zone. The combination of approximation-based adaptive technique and neural network system is used for approximating the nonlinear function of the ship plant. Through backstepping and Lyapunov theory synthesis, an indirect adaptive network controller is derived for dynamic positioning ships without dead-zone property. In order to improve the control effect, a dead-zone compensator is derived using fuzzy logic technique to handle the dead-zone nonlinearity. The main advantage of the proposed controller is that it can be designed without explicit knowledge about the ship motion model, and dead-zone nonlinearity is well compensated. A set of simulations is carried out to verify the performance of the proposed controller.