基于递推非线性部分最小二乘模型的间歇过程批到批优化

针对间歇过程控制策略优化问题,提出一种基于递推非线性部分最小二乘(NLPLS)模型的批到批优化方法:首先采用非线性部分最小二乘方法建立软测量模型,根据过程的控制操作变量对最后的产品质量进行预测。然后基于该模型,计算出最优控制策略并在实际装置上实施。为了解决模型和对象失配并且存在未知扰动的问题,采用递推算法,在每个批次结束后根据新得到的数据和旧模型参数对原模型进行更新。然后,重新求解最优控制策略并在对象上实施。通常经过几个批次,控制策略将收敛到一个满意解。在一个间歇过程上进行仿真研究,同时与基于PLS模型的批到批优化算法进行对比,结果表明采用NLPLS模型取得了优于采用PLS模型的结果。

Batch-to-batch optimization of batch processes based on recursive nonlinear partial least squares model

A batch-to-batch optimization approach for batch processes based on batch wise updated nonlinear partial least squares(NLPLS) models was presented in this paper.Firstly,a NLPLS model was developed to predict the final product quality from the batch control profile. Mismatch between the model and the actual plant often exists due to low-quality training data or variations in process operating conditions. Thus the optimal control profile calculated from the NLPLS model may not be optimal when applied to the a...