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

Suh Jin Ho (동아대학교 전기공학과 국가지정연구실)
Lee Jin Woo (동아대학교 전기공학과 국가지정연구실)
Lee Young Jin (항공기능대학 전기계측공학과)
Lee Kwon Soon (동아대학교 전기전자컴퓨터공학부)
Publication Information
Journal of the Korean Society for Precision Engineering / v.22, no.1, 2005 , pp. 61-72 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 for 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. Accordingly, the proposed algorithm in this study can be readily used for industrial applications
Keywords
Automated transfer crane; Neural network predictive; Anti-sway control; Collision avoidance path; NN self-tuner; ATC; NNP;
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