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Development and application of a neural network based coating weight control system for a hot-dip galvanizing line 被引量:1
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作者 Zai-sheng PAN Xuan-hao ZHOU Peng CHEN 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2018年第7期834-846,共13页
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 unmeasur... 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 Va Lin 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. 展开更多
关键词 Neural network Hot-dip galvanizing line (HDGL) coating weight control
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