Adaptive neural network filter for steel rolling

Rolling mill control systems which use measurements of the rolling force (gauge control) must compensate for eccentricity of the rolls. The proposed neural eccentricity filter provides this compensation without any information about the position of the rolls. This application requires fast online adaptation of the filter due to time-variant behavior of the process which is provided by a recursive least squares learning algorithm.<
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