Zai-sheng PAN, Xuan-hao ZHOU, Peng CHEN. Development and application of a neural network based coating weight control system for a hot-dip galvanizing line[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(7): 834-846.
DOI:
Zai-sheng PAN, Xuan-hao ZHOU, Peng CHEN. Development and application of a neural network based coating weight control system for a hot-dip galvanizing line[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(7): 834-846. DOI: 10.1631/FITEE.1601397.
Development and application of a neural network based coating weight control system for a hot-dip galvanizing line
The hot-dip galvanizing line (HDGL) is a typical order-driven discrete-event process in steelmaking. It has some complicated dynamic characteristics such as a large time-varying delay
strong nonlinearity
and unmeasured disturbance
all of which lead to the difficulty of an online coating weight controller design. We propose a novel neural network based control system to solve these problems. The proposed method has been successfully applied to a real production line at VaLin LY Steel Co.
Loudi
China. The industrial application results show the effectiveness and efficiency of the proposed method
including significant reductions in the variance of the coating weight and the transition time.
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