Browse > Article
http://dx.doi.org/10.5394/KINPR.2006.30.4.259

Improved Adaptive Neural Network Autopilot for Track-keeping Control of Ships: Design and Simulation  

Nguyen, Phung-Hung (Graduate school, Korea Maritime University)
Jung, Yun-Chul (Div. of Navigation Systems Engineering, Korea Maritime University)
Publication Information
Journal of Navigation and Port Research / v.30, no.4, 2006 , pp. 259-265 More about this Journal
Abstract
This paper presents an improved adaptive neural network autopilot based on our previous study for track-keeping control of ships. The proposed optimal neural network controller can automatically adapt its learning rate and number of iterations. Firstly, the track-keeping control system of ships is described For the track-keeping control task, a way-point based guidance system is applied To improve the track-keeping ability, the off-track distance caused by external disturbances is considered in learning process of neural network controller. The simulations of track-keeping performance are presented under the influence of sea current and wind as well as measurement noise. The toolbox for track-keeping simulation on Mercator chart is also introduced.
Keywords
Adaptive neural network; Autopilot; Track-keeping; Ship control; Track-keeping simulation;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Brandt, R. D. and Lin, F. (1999), 'Adaptive interaction and its application to neural networks', Elsevier, Information Science 121 (pp. 201-215)   DOI   ScienceOn
2 Nguyen, P. H. and Jung, Y. C. (2006), 'An Adaptive Autopilot for Course-keeping and Track-keeping Control of Ships using Adaptive Neural Network (Part II: Simulation Study)', International Journal of Navigation and Port Research (KINPR), Vol.30, No.2 pp. 119-124, ISSN-1598-5725   과학기술학회마을   DOI   ScienceOn
3 Saikalis, G. and Lin, F. (2001), 'A Neural Network Controller by Adaptive Interaction', Proceedings of the American Control Conference, Arlington, pp. 1247-1252
4 Vukic, Z., Omerdic, E., Kuljaca, L. (1997), 'Fuzzy Autopilot for Ships Experiencing Shallow Water Effect in Manoeuvring', Manoeuvring and Control of Marine Craft, A proceedings volume from the IFAC Conference, Brijuni, Croatia, pp. 99-104 (Edited by Z. Vukic and G. N. Roberts)
5 Nguyen, P. H. and Jung, Y. C. (2005), 'An Adaptive Autopilot for Course-keeping and Track-keeping Control of Ships using Adaptive Neural Network (Part I: Theoretical Study)', International Journal of Navigation and Port Research (KINPR), Vol.29, No.9 pp. 771-776, ISSN-1598-5725   과학기술학회마을   DOI   ScienceOn
6 Fossen, T. I. (2002), 'Marine Control Systems: Guidance, Navigation and Control of Ships, Rigs and Underwater Vehicles', Marine Cybernetics, Trondheim, Norway. ISBN 82-92356-00-2
7 Vukic, Z., Omerdic, E., Kuljaca, L. (1998), 'Improved Fuzzy Autopilot for Track-keeping', Control Applications in Maritime Systems, A proceedings volume from the IFAC Conference, Fukuoka, Japan, pp. 123-128 (Edited by K. Kijima and T. I. Fossen)
8 Zhuo, Y. and Hearn, G. E. (2004), 'Specialized Learning for Ship Intelligent Track-keeping Using Neurofuzzy', Proceedings of IFAC-CAMS, Ancona, Italy, pp. 291-296, July, 7-9
9 Yoon, Y. J. and Jeon, S. H. (2005), 'Terrestrial Navigation' (in Korean), Korea Maritime University
10 Zhang, Y., Hearn, G. E. and Sen, P. (1997), 'Neural network approaches to a class of ship control problems (Part I & II)', Eleventh Ship Control Systems Symposium Vol. 1 (Edited by P. A. Wilson)
11 Velagic, J., Vukiz, Z., Omerdic, E. (2003), 'Adaptive Fuzzy Ship Autopilot for Track-keeping', Control Engineering Practice 11, pp. 433-443   DOI   ScienceOn
12 Fossen, T. I. (2005), GNC Toolbox for MATLAB (http://www.cesos.ntnu.no/mss/MarineGNC/index.htm. accessed 2005/Dec)
13 Rich Powlowicz (2005), M_Maps homepage (http://www2.ocgy.ubc.ca/~rich/map.html,accessed2005/Dec)