Temperature Control of Abnormal Condition Integrated with Fuzzy Improved ELMAN Network and Q Learning for Raw Meal Calcination Process

@article{Qiao2018TemperatureCO,
  title={Temperature Control of Abnormal Condition Integrated with Fuzzy Improved ELMAN Network and Q Learning for Raw Meal Calcination Process},
  author={Jinghui Qiao and Ling Li and Tianyou Chai},
  journal={2018 37th Chinese Control Conference (CCC)},
  year={2018},
  pages={3496-3501}
}
Thus the pipe between preheater C5 and kiln rotary was blocked because the outlet temperature of preheater C5 is greater than the maximum value. To overcome above the problem, an abnormal condition controller integrated with fuzzy improved ELMAN network and Q learning has been proposed. The abnormal condition controller has been successfully applied to the actual industry process. Practical applications show that this abnormal condition controller has high potential in process control and can… CONTINUE READING

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