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《第37届中国控制会议论文集(C)》2018年
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Temperature Control of Abnormal Condition Integrated with Fuzzy Improved ELMAN Network and Q Learning for Raw Meal Calcination Process

Jinghui Qiao  Ling Li  Tianyou Chai  
【摘要】:In raw meal calcination process, there are three conditions, that is easy calcination condition, difficult calcination condition,and abnormal condition, and abnormal condition often happen because of varying material properties. 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 be applied to the other complex industries.

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