High precision control for linear motor-based container transfer system with cogging force and friction

摘要

In this paper, we will introduce concerning a control strategy that is the multi-step prediction control of linear motor-based container transport system for high precision using dynamically-constructed recurrent fuzzy neural networks (DR-FNNs). Linear motor-based container transport system (LMCTS) is horizontal transfer system for the yard automation, which has been proposed to take the place of automated guided vehicle in the maritime container terminal. LMCTS is considered as that the system is changed its model suddenly and variously by loading and unloading container. The proposed control system is used two DR-FNNs for multi-step prediction. Consequently, the system has an ability to adapt for a huge rolling friction, cogging force, force ripple, and sudden changes of itself by loading and unloading.