A study on development of ATCS for automated transfer crane using neural network predictive PID controller

The ATC (automated transfer crane) control system is required for high speed and rapid transportation. Therefore, when the container is transferred from the initial coordinate to the final coordinate, the container paths should be built in terms of the least time and without sway. Therefore, we calculated the anti-collision path for avoiding collision in its movement to the final coordinate in this paper. And we constructed the NNPPID (neural network predictive PID) controller to control the precise navigation. The proposed predictive control system is composed of the neural network predictor, TDOFPID (two degree of freedom PID) controller, neural network self-tuner which yields parameters of TDOFPID. We analyzed crane system through simulation, and proved excellent of control performance over the conventional controllers.