基于规则的自学习控制的柴油加氢优化

Optimization of Diesel Hydrogenation Refining by the Rule-based Self-learning Control

针对茂名石化炼油厂柴油生产流程和月生产数据,优化加氢装置生产方案。根据问题建立双线性数学模型,结合基于规则的自学习和二分查找训练算法,利用Matlab软件强大的编程、计算功能,提出了一种柴油生产预测优化方案,该方案可以辅助生产人员设计成本较低的柴油调合和加氢精制方案。

In this paper, based on the diesel-processing flow of a petrochemical refinery and a month producing data , the diesel hydrogenation refining project is optimized. A bi-linear programming model is presented. With the powerful computing Matlab programs and the rule-based self-learning binary search algorithm,a diesel-processing forcast method is given. This method may be a good assistant in the design of the diesel-processing and hydrogenation-refining schemes.