焦炉是具有大时滞、强非线性、多变量耦合、变参数的复杂对象。直行温度受多种因素的影响，传统的控制方法难以满足焦炉加热控制的要求。提出了间歇加热控制与加热煤气流量调节相结合的控制原理，利用模糊控制、神经网络等智能控制方法建立了焦炉加热的智能控制策略和模型。该控制策略采用一前馈、二反馈和智能控制相结合。根据焦化机理建立焦炉供热量前馈模型，并提出结焦指数CI反馈模型控制焦炉的炼焦过程。基于线性回归和RBF神经网络构建火道软测量模型，为控制建立温度反馈环节。智能控制方法用于调节停止加热时间和加热煤气流量。最后研究开发了焦炉加热的复合智能控制系统。实际运行结果表明：该系统能够实现焦炉加热的智能控制，稳定了焦炉生产，有效地提高了焦炭质量和降低了能耗，具有很好的实用价值。
Coke oven is a complex object with the characteristics of long timedelay, strong nonlinearity, multivariable coupling and parameters changeability. The mean flue temperature is affected by many factors and traditional control method is not satisfactory.A control principle of combining the intermittent heating control with heating gas flow adjustment was proposed and the intelligent control methods, namely fuzzy control and neural network, were adopted to establish intelligent control strategy and model of coke oven heating, which combines two feedback control, one feedforward control and intelligent control. According to coking mechanism,a feedforward model was built for heat supply, and carbonization index CI feedback model was proposed to control coking.A flue temperature soft measurement model based on linear regression and RBF neural network was built to establish temperature feedback control. Intelligent control methods were used to control heating time and heating gas flow. Finally a compound intelligent control system of coke oven was developed. The practical operation indicated that the system can realize intelligent control of coke oven, stabilize production, improve effectively coke quality and decrease energy consumption.
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