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In the process of clinker calcination, the target value of the raw meal decomposition rate (RMDR) is different in the easy and difficult calcination stages because the boundary conditions of raw meal (i.e., raw meal flow, raw meal ingredients, and particle size) change frequently, where RMDR cannot be guaranteed to be within its desirable range. To solve this problem, an intelligent setting control method is proposed in this paper for a clinker calcination process. The proposed approach is realized by on-line adjustment of the setpoints of control loops in line with the changes of raw meal boundary conditions. This method consists of five modules, namely an RMDR target value setting model, a control loop pre-setting model, a feedback compensation model based on the fuzzy rules, a feedforward compensation model based on the fuzzy rules, and a soft measurement model for RMDR. Successful application to the clinker calcination process of the Jiuganghongda Cement Plant in China has been made, where the efficiency of the proposed method has been validated by the results of the practical application.

In raw meal calcination process, since boundary conditions of raw meal change frequently, the decomposition rate of raw meal (RMDR) cannot guarantee the desirable ranges. Therefore, C5 feeding tube was blocked and the load of rotary kiln will increase. To solve above problem, an intelligent switching control method is proposed to control the calciner temperature into their setpoints. This method for raw meal calcination process consists of four modules, namely a easy calcination controller, a difficult calcination controller, a abnormal condition controller, and a switching mechanism. The proposed approach can select right controller according to the change of the working conditions and has been successfully applied to the raw meal calcination process of Jiuganghongda Cement Plant in China and its efficiency has been validated by the practical application results.

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