About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
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Measurement & Control of High Temperature Processes
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| Presentation Title |
An Adaptive Control Strategy for Traveling Grate Pelletizing Processes Based on Fuzzy Logic and Rule-Based Systems |
| Author(s) |
XuLing Chen, ChengHao Xie, ZhenXiang Feng, XiaoHui Fan, XiaoXian Huang |
| On-Site Speaker (Planned) |
|
| Abstract Scope |
Maintaining thermal stability in the firing zone of traveling grate pelletizing processes (TGPPs) is essential to ensure pellet quality and energy efficiency. In practice, thermal stability is strongly affected by fluctuations in feed rate and grate speed. Their combined influence often causes a mismatch between heat input and thermal load, which conventional controllers cannot effectively handle. To address this issue, this paper proposes an adaptive control strategy that integrates fuzzy logic and rule-based systems. First, a switching mechanism selects the appropriate controller based on the real-time operating condition identified by an isolation forest model. During fluctuating conditions, a rule-based controller rapidly compensates for disturbances, driven by the grate speed-fan matching residual and the temperature trend. Under stable conditions, a fuzzy logic controller ensures precise fan regulation using temperature error and its rate of change. Simulation results demonstrate that the proposed adaptive strategy achieves superior thermal stability compared to conventional PID and fuzzy controllers, offering an effective solution for the intelligent automation of TGPPs. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Iron and Steel, Modeling and Simulation, Machine Learning |