Robust regression for adaptive control of industrial weight fillers

F. Denaro, L. Consolini, Davide Buratti
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Abstract

In industrial weight-filling machines, containers are filled with the liquid stored in a tank by an electronically controlled valve. The weight is sensed through a load cell. We develop a learning algorithm that predicts the right closure time as a function of liquid pressure and temperature. The algorithm solves a non-convex robust regression problem and is based on a branch and bound approach in regressors space.
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工业填料自适应控制的鲁棒回归
在工业称重机中,容器通过电子控制阀将储存在罐中的液体填满。重量是通过称重传感器测得的。我们开发了一种学习算法,可以根据液体压力和温度来预测正确的关闭时间。该算法基于回归量空间中的分支定界方法,解决了非凸鲁棒回归问题。
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