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An Automatic Travel Control of a Container Crane using Neural Network Predictive PID Control Technique  

Suh Jin-Ho (Department of Electrical Engineering, Dong-A University)
Lee Jin-Woo (Department of Electrical Engineering, Dong-A University)
Lee Young-Jin (Dept. of Electrical Instrument and Control, Korea Aviation Polytechnic College)
Lee Kwon-Soon (Department of Electrical Engineering, Dong-A University)
Publication Information
International Journal of Precision Engineering and Manufacturing / v.7, no.1, 2006 , pp. 35-41 More about this Journal
Abstract
In this paper, we develop anti-sway control in proposed techniques for an ATC system. The developed algorithm is to build the optimal path of container motion and to calculate an anti-collision path for collision avoidance in its movement to the finial coordinate. Moreover, in order to show the effectiveness in this research, we compared NNP PID controller to be tuning parameters of controller using NN with 2-DOF PID controller. The experimental results jar an ATC simulator show that the proposed control scheme guarantees performances, trolley position, sway angle, and settling time in NNP PID controller than other controller. As a result, the application of NNP PID controller is analyzed to have robustness about disturbance which is wind of fixed pattern in the yard.
Keywords
Automated transfer crane(ATC); Neural network(NN); Anti-sway control; NN self-tuner; Predictive control;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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