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http://dx.doi.org/10.6109/jkiice.2013.17.12.2775

Brachistochrone Minimum-Time Trajectory Control Using Neural Networks  

Choi, Young-Kiu (Department of Electrical Engineering, Pusan National University)
Park, Jin-Hyun (Dept. of Mechatronics Eng., Kyeognam National Univ. of Science and Technology)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.17, no.12, 2013 , pp. 2775-2784 More about this Journal
Abstract
A bead is intended to reach a specified target point in the minimum-time when it travels along a certain curve on a vertical plane with the gravity. This is called the brachistochrone problem. Its minimum-time control input may be found using the calculus of variation. However, the accuracy of its minimum-time control input is not high since the solution of the control input 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. For various final target points, we have found that the proposed method is superior to the conventional ones through the computer simulations.
Keywords
Brachistochrone problem; minimum-time control; neural network;
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Times Cited By KSCI : 1  (Citation Analysis)
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