A real-time embedded control system for electro-fused magnesia furnace (Q1953748)
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scientific article; zbMATH DE number 6172162
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | A real-time embedded control system for electro-fused magnesia furnace |
scientific article; zbMATH DE number 6172162 |
Statements
A real-time embedded control system for electro-fused magnesia furnace (English)
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10 June 2013
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Summary: Since smelting process of electro-fused magnesia furnace is a complicated process which has characteristics like complex operation conditions, strong nonlinearities, and strong couplings, traditional linear controller cannot control it very well. An advanced intelligent control strategy is a good solution to this kind of industrial process. However, advanced intelligent control strategy always involves huge programming task and hard debugging and maintaining problems. In this paper, a real-time embedded control system is proposed for the process control of electro-fused magnesia furnace based on intelligent control strategy and model-based design technology. As for hardware, an embedded controller based on an industrial Single Board Computer (SBC) is developed to meet industrial field environment demands. As for software, a Linux system based on Real-Time Application Interface (RTAI) is used as the real-time kernel of the controller to improve its real-time performance. The embedded software platform is also modified to support generating embedded code automatically from Simulink/Stateflow models. Based on the proposed embedded control system, the intelligent embedded control software of electro-fused magnesium furnace can be directly generated from Simulink/Stateflow models. To validate the effectiveness of the proposed embedded control system, Hardware-In-the-Loop (HIL) and industrial field experiments are both implemented. Experiments results show that the embedded control system works very well in both laboratory and industry environments.
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advanced intelligent control strategy
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real-time control
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model-based design
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0.6539417505264282
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0.6535282135009766
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