摘要
针对PX氧化过程重要质量指标4-CBA含量的预测问题,采用带有装置因数的简化非线性动力学方程作为软测量模型,提出了基于无迹卡尔曼滤波的模型参数估计方法,与常规的非线性最小二乘方法相比,该方法无需进行线性化处理,不需要计算雅可比矩阵.最后用实测工业数据分别建立了3种不同的4-CBA含量的软测量模型,预测结果验证了所提方法的有效性.
A soft sensor model based on the simplified nonlinear dynamics equation with device factor is used to predict the 4-CBA concentration, which is an important quality index in PX oxidation processes. The parameters of the model are estimated using the unscented Kalman filtering method. Compared with the traditional nonlinear least squares method, the proposed method does not require linearization on calculation of the Jacobian matrix. Industrial data are applied to test three soft sensors for 4-CBA concentration prediction. The resalts show that the proposed method is effective.
出处
《信息与控制》
CSCD
北大核心
2014年第3期339-343,共5页
Information and Control
基金
国家自然科学基金资助项目(61203213
11202107)
关键词
无迹卡尔曼滤波
PX氧化过程
软测量
unscented Kalman filtering
PX oxidation process
soft sensor
