基于KPLS模型的间歇过程产品质量控制

doi:10.3969/j.issn.0438-1157.2013.04.029

化工学报 ›› 2013, Vol. 64 ›› Issue (4): 1332-1339.DOI: 10.3969/j.issn.0438-1157.2013.04.029

基于KPLS模型的间歇过程产品质量控制

贾润达^1,2, 毛志忠^1,2, 王福利^1,2

1. 东北大学信息科学与工程学院,辽宁沈阳 110004;
2. 流程工业综合自动化国家重点实验室,辽宁沈阳 110004

收稿日期:2012-07-30 修回日期:2012-10-11 出版日期:2013-04-05 发布日期:2013-04-05
通讯作者: 贾润达
作者简介:贾润达(1981—),男,博士,讲师。
基金资助:
国家高技术研究发展计划项目(2011AA060204);国家自然科学基金项目(61203103);中央高校基本科研业务费项目(N110304006)。

KPLS model based product quality control for batch processes

JIA Runda^1,2, MAO Zhizhong^1,2, WANG Fuli^1,2

1. School of Information Science and Engineering, Northeastern University, Shenyang 110004, Liaoning, China;
2. State Key Laboratory of Synthetic Automation for Process Industries, Northeastern University, Shenyang 110004, Liaoning, China

Received:2012-07-30 Revised:2012-10-11 Online:2013-04-05 Published:2013-04-05
Supported by:
supported by the High-tech Research and Development Program of China(2011AA060204),the National Natural Science Foundation of China(61203103) and the Fundamental Research Funds for the Central Universities(N110304006).

摘要/Abstract

摘要： 针对间歇过程所具有的非线性特性,提出了一种基于核偏最小二乘(KPLS)模型的最终产品质量控制策略。利用初始条件、批次展开后的过程数据以及最终产品质量建立了间歇过程的KPLS模型;采用基于主成分分析(PCA)映射的预估方法对未知的过程数据进行补充,实现了最终产品质量的在线预测。为了解决最终产品质量的控制,利用T2统计量确定KPLS模型的适用范围,并作为约束引入产品质量控制问题,提高控制策略的可行性;采用粒子群优化(PSO)算法实现了优化问题的高效求解。仿真结果表明,与基于偏最小二乘(PLS)模型的控制策略相比,所提出的方法具有更高的预测精度,且能有效解决产品质量控制中出现的各种问题。

关键词: 间歇过程, 质量控制, 核偏最小二乘, 主成分分析, 优化

Abstract: To deal with the nonlinear characteristics of batch processes, a final product quality control strategy based on kernel partial least squares(KPLS) was proposed.KPLS model of batch process was calibrated with initial conditions, batch-wise unfolding of process data and final product quality.An estimate method based on principal component analysis(PCA) mapping was used to supplement the unknown process data, and online prediction of product quality was achieved.To cope with the final product quality control, T2 statistic was used to determine the field that KPLS model was applicable, and the model was introduced into product quality control problem as constraint to enhance the feasibility of the control strategy.Particle swarm optimization(PSO) algorithm was used to solve the optimization problem efficiently.Simulation results showed that comparing with partial least squares(PLS) model based control strategy, higher prediction accuracy was obtained with the proposed method, and various problems in product quality control could be effectively solved.

Key words: batch process, quality control, kernel partial least squares (KPLS), principal component analysis(PCA), optimization

中图分类号:

TP273

贾润达, 毛志忠, 王福利. 基于KPLS模型的间歇过程产品质量控制[J]. 化工学报, 2013, 64(4): 1332-1339.

JIA Runda, MAO Zhizhong, WANG Fuli. KPLS model based product quality control for batch processes[J]. CIESC Journal, 2013, 64(4): 1332-1339.

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基于KPLS模型的间歇过程产品质量控制

KPLS model based product quality control for batch processes

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