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Mathematical Problems in Engineering
Volume 2014, Article ID 218585, 9 pages
Research Article

Adaptive Filtering Backstepping for Ships Steering Control without Velocity Measurements and with Input Constraints

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

Received 26 November 2013; Revised 20 January 2014; Accepted 20 January 2014; Published 5 March 2014

Academic Editor: Ezzat G. Bakhoum

Copyright © 2014 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.


We consider the problem of course tracking for ships with uncertainties and unknown external disturbances, in the presence of input magnitude and rate saturation. The combination of approximation-based adaptive technique and radial basis function (RBF) neural network allows us to handle the unknown disturbances from the environment and uncertain ship dynamics. By employing the adaptive filtering backstepping, the full-state feedback controller is first derived. Then the output feedback controller is designed with the unmeasurable state estimated by using a high-gain observer. In order to cope with the input constraints, an auxiliary system is introduced to the output feedback controller, and the semiglobal uniform boundedness of the modified control solution is verified. Simulation results are presented for the course tracking of a cargo ship, which are demonstrative of the excellent performance of the proposed controller.