A study on design of anti-sway controller for ATC using Neural Network Predictive control

Recently, an ATC(Automated Transfer Crane) control system is required rapid transportation to get highest productivity with low cost. Therefore, the container paths should be built in terms of the least time and least sway when container is transferred from the initial coordinate to the finial coordinate. So in this paper, we proposed improved navigation method to reduce transfer time and sway with anti-collision path for avoiding collision in its movement to the finial coordinate. And we constructed the NNPPID(Neural Network Predictive PID) controller to control the precise move and speedy navigation. The proposed predictive control system is composed of the Neural Network Predictor, TDOFPID(Two Degree of Freedom PID) controller, and Neural Network self-tuner. We analyzed ATC system and showed some computer simulations to prove excellence of the proposed controller than other conventional controllers.