Title

IMPROVING IRON MAKING PROCESSES WITH MULTIVARIABLE PREDICTIVE CONTROL TECHNOLOGY

IMPROVING IRON MAKING PROCESSES WITH MULTIVARIABLE PREDICTIVE CONTROL TECHNOLOGY

Authorship

Lee, Garry; Freeman, Neil

Lee, Garry

I am this author

Freeman, Neil

I am this author

DOI

10.5151/2594-357x-0107

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Abstract

High performance control of an interactive process such as a sinter plant relies on ability to: honor safety and operational constraints; reduce the standard deviations of variables that need to be controlled (e.g. product quantity, quality); de-bottlenecking the process; and, maximize profitability or lower cost (e.g. energy savings, improve hot metal content). These objectives may be prioritized in this order, but can vary and are very difficult to achieve optimally through conventional control. Multivariable predictive control is a control technique that has been successfully applied throughout the hydrocarbon processing industries to provide high performance control since the early 1970’s. This technique is now starting to be used within the metals and mining industries with similar results. A multivariable predictive controller solution, along with its extensive inferential sensor and built-in optimizer, provides online closed loop control and optimization for many interactive metal and mining processes to lower the energy cost, increase throughput, and optimize product quality and yield. This paper, through an example for sinter plant process control, discusses how the technology can applied to the high energy intensity process of Iron and steel making.

High performance control of an interactive process such as a sinter plant relies on ability to: honor safety and operational constraints; reduce the standard deviations of variables that need to be controlled (e.g. product quantity, quality); de-bottlenecking the process; and, maximize profitability or lower cost (e.g. energy savings, improve hot metal content). These objectives may be prioritized in this order, but can vary and are very difficult to achieve optimally through conventional control. Multivariable predictive control is a control technique that has been successfully applied throughout the hydrocarbon processing industries to provide high performance control since the early 1970’s. This technique is now starting to be used within the metals and mining industries with similar results. A multivariable predictive controller solution, along with its extensive inferential sensor and built-in optimizer, provides online closed loop control and optimization for many interactive metal and mining processes to lower the energy cost, increase throughput, and optimize product quality and yield. This paper, through an example for sinter plant process control, discusses how the technology can applied to the high energy intensity process of Iron and steel making.

Keywords

Multivariable control; Predictive control; Sintering; Pelletizing.

Multivariable control; Predictive control; Sintering; Pelletizing.