A learning fuzzy system for looper control in rolling mills

In this paper, several issues of looper control in rolling mills are discussed and a fuzzy logic control is proposed to address the enumerated issues. The proposed system incorporated fast tuning algorithms for both off-line and online learning of membership functions and singleton values. Also, it is relatively simple to design and implement. The effectiveness of the proposed system is verified by the simulations results. It is shown that the proposed system is more robust to parameter uncertainties and noises, when compared with conventional PID control.