铝冶炼
铝
冶炼
航程(航空)
控制(管理)
估计员
工艺工程
材料科学
环境科学
计算机科学
冶金
工程类
数学
复合材料
统计
人工智能
作者
Jing Shi,Choon Jie Wong,Jie Bao,Maria Skyllas‐Kazacos,Barry J. Welch,Ali Khalid Jassim,Mustafa Mustafa,Konstantin Nikandrov,Mohamed M. Khairy
标识
DOI:10.1016/j.ifacol.2023.10.736
摘要
In an aluminum smelting cell, the alumina concentration plays a critical role in determining process stability and performance, thus it is always desirable to control the alumina concentration at a stable level within a reasonable range. However, the traditional logic-based alumina feed control strategies typically implement overfeed–basefeed–underfeed cycles to control the alumina concentration in a range, which causes significant variations in alumina concentration within the aluminum smelting cell, and risk transgression to perfluorocarbons (PFC) co-evolution. Different from the traditional methods, this paper presents an advanced cell monitoring and control approach which integrates a state estimator, model-based control and logic control to improve cell performances through tighter control of alumina concentration.
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