基于粒子滤波联合估计的气相聚乙烯质量指标在线估计

Polymer properties on-line estimation for gas-phase polyethylene based on particle filtering joint estimation

针对气相聚乙烯生产中各种复杂的工况造成在线估计精度下降的现象,基于乙烯聚合机理并利用特征建模方法建立了聚乙烯质量指标预测模型,结合扩展卡尔曼滤波,提出了粒子滤波联合估计方法,即将状态和修正系数组成增广状态向量,实现对质量指标预测模型的在线滤波修正,并分析了基于粒子滤波估计的收敛性。所提方法在中石化某气相聚乙烯装置的长周期运行结果证实了所提方法的可行性和有效性,为实施聚乙烯装置的先进控制奠定了基础。

Due to the lack of suitable on-line polymer property measurements,the control of multi-grade product quality in industrial polymerization reactors is difficult.In this article,a predictive model of polymer properties is deduced for industrial polyethylene process by combining the first principle model and the feature modeling scheme.Combining the extended Kalman filtering,a method of design the particle filtering joint estimation is proposed to update the estimation of polymer properties based on the off-line lab analysis data in this article.The application results of the proposed method to an industrial gas-phase polyethylene plant have verified its effectiveness and feasibility.With the proposed method,multi-grade polymer properties of industrial gas-phase polyethylene process can be on-line estimated and make it possible for achieving the advanced on-line multi-grade product quality control.