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Robust Control for Ship Course-Keeping Based on Support Vector Machines: Particle Swarm Optimization and L2-Gain

[+] Author Affiliations
Weilin Luo, Carlos Guedes Soares

Technical University of Lisbon, Lisbon, Portugal

Bin Fu

Fuzhou University, Fujian, China

Zaojian Zou

Shanghai Jiao Tong University, Shanghai, China

Paper No. OMAE2013-11076, pp. V005T06A070; 7 pages
doi:10.1115/OMAE2013-11076
From:
  • ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering
  • Volume 5: Ocean Engineering
  • Nantes, France, June 9–14, 2013
  • Conference Sponsors: Ocean, Offshore and Arctic Engineering Division
  • ISBN: 978-0-7918-5539-3
  • Copyright © 2013 by ASME

abstract

To achieve a robust autopilot for ship course-keeping, a controller based on support vector machines (SVM) and L2-gain is proposed. A cascaded plant consists of a nonlinear ship response model and the rudder actuator dynamics. Uncertainties including modeling errors and external disturbances are taken into account in the response model. SVM is applied to identify the complicated nonlinear dynamics including the modeling errors, while L2-gain design is used to suppress the uncertain disturbances. To obtain the optimized structural parameters in SVM, particle swarm optimization (PSO) method is incorporated. Stability analysis and simulation results demonstrate the validity of the proposed control scheme.

Copyright © 2013 by ASME

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