Design a Ship Autopilot using Neural Network
Ship autopilots play an important role in insurance of safe navigation and efficient transportation as else. For their successful design and development, many control techniques were and are being developed. In this paper, the application of artificial neural network (ANN) is investigated to design an autopilot for a surface ship. Feed forward multilayered architecture of ANN is used for approximation of the inverse model of the ship. The designed autopilot acts like an optimal one because of using a cost function for generation of ANN training data. The performance of designed autopilot is evaluated in still water and different wave frequencies. The stability and robustness of the designed system is proved through simulation, carried out in Matlab. The results show that the proposed autopilot can efficiently be used to control the course of a ship in a range of parameter variation.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/647915695
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Supplemental Notes:
- Abstract used with permission from the Society of Naval Architects and Marine Engineers (SNAME).
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Authors:
- Tung, Le Thanh
- Publication Date: 2017-8
Language
- English
Media Info
- Media Type: Web
- Pagination: pp 192-196
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Serial:
- Journal of Ship Production and Design
- Volume: 33
- Issue Number: 3
- Publisher: Society of Naval Architects and Marine Engineers
- ISSN: 2158-2866
- EISSN: 2158-2874
- Serial URL: https://onepetro.org/jspd
Subject/Index Terms
- TRT Terms: Automatic pilot (Ships); Automatic vessel control; Maneuvering; Neural networks; Ship operations; Ship pilotage; Voyage management systems
- Identifier Terms: MATLAB (Computer program)
- Subject Areas: Marine Transportation; Operations and Traffic Management; Safety and Human Factors;
Filing Info
- Accession Number: 01642127
- Record Type: Publication
- Files: TRIS
- Created Date: Jul 27 2017 10:05AM