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Journal of Applied Mathematics
Volume 2014, Article ID 347589, 15 pages
Research Article

Research on Roll Stabilizing Based on Energy Optimization for Autonomous Surface Vehicle

1College of Automation, Harbin Engineering University, Harbin 150001, China
2College of Information, Inner Mongolia University of Technology, Hohhot 010051, China
3Beijing Institute of Control Engineering, China Academy of Space Technology, Beijing 100190, China

Received 11 May 2014; Revised 9 August 2014; Accepted 11 August 2014; Published 1 September 2014

Academic Editor: Engang Tian

Copyright © 2014 Hongjian Wang 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.


Considering the case of ASV (autonomous surface vehicle) navigating with low speed near water surface, a new method for design of roll motion controller is proposed in order to restrain wave disturbance effectively and improve roll stabilizing performance. Control system design is based on GPC (general predictive control) theory and working principle of zero-speed fin stabilizer. Coupling horizontal motion model of ASV is decoupled, and an equivalent transfer function of roll motion is obtained and transformed into a discrete difference equation through inverse Laplace transformation and Euler approximation. Finally, predictive model of GPC, namely, the difference equation of roll motion, is given. GPC algorithm of ASV roll motion is derived from performance index based on roll stabilizing performance and energy consumption used for driving fin stabilizer. In allusion to time-variant parameters in roll motion model, recursive least square method is adopted for parameter estimation. Simulation results of ASV roll motion control show better stabilizing performance and minimized energy consumption improved by self-adaptive GPC.