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http://dx.doi.org/10.6109/jkiice.2013.17.1.117

Minimum-Time Trajectory Control of Ships Using Neural Networks  

Choi, Young-Kiu (부산대학교 공과대학 전기공학과)
Park, Jin-Hyun (경남과학기술대학교 메카트로닉스공학과)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.17, no.1, 2013 , pp. 117-126 More about this Journal
Abstract
A ship is intended to reach a specified target point in the minimum-time when it travels with a constant speed through a region of strong currents and its heading angle is the control variable. This is called the Zermelo's navigation problem. Its approximate solution for the minimum-time control may be found using the calculus of variation. However, the accuracy of its approximate solution is not high since the solution is based on a table form of inverse relations for some complicated nonlinear equations. To enhance the accuracy, this paper employs the neural network to represent the inverse relation of the complicated nonlinear equations. The accurate minimum-time control is possible with the interpolation property of the neural network. Through the computer simulation study we have found that the proposed method is superior to the conventional ones.
Keywords
Zermelo navigation problem; minimum-time control; neural network;
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