基于偏相关性分析的MPC控制器模型失配检测

doi:10.11949/j.issn.0438-1157.20151883

化工学报 ›› 2016, Vol. 67 ›› Issue (3): 852-857.DOI: 10.11949/j.issn.0438-1157.20151883

基于偏相关性分析的MPC控制器模型失配检测

李秋美, 田学民, 尚林源

中国石油大学(华东)信息与控制工程学院, 山东青岛 266580

收稿日期:2015-12-11 修回日期:2015-12-25 出版日期:2016-03-05 发布日期:2016-01-12
通讯作者: 田学民
基金资助:
国家自然科学基金项目(61273160,61403418);中央高校基本科研业务费专项资金项目(15CX06063A)。

Detection of model-plant mismatch based on partial correlation analysis of MPC controllers

LI Qiumei, TIAN Xuemin, SHANG Linyuan

College of Information and Control Engineering, China University of Petroleum (East China), Qingdao 266580, Shandong, China

Received:2015-12-11 Revised:2015-12-25 Online:2016-03-05 Published:2016-01-12
Contact: 67
Supported by:
supported by the National Natural Science Foundation of China (61273160, 61403418) and the Fundamental Research Funds for the Central Universities (15CX06063A).

摘要/Abstract

摘要：

在实际中,模型失配是导致模型预测控制性能下降的关键因素。传统的相关性分析方法在分析某一通道的预测残差和操作变量之间的相关性时,会受到其他操作变量及干扰的影响,导致结果不可靠,无法准确定位失配。针对上述问题,现采用偏相关性分析方法。在滤除其他操作变量和干扰影响的前提下,分析各通道预测残差和操作变量之间的相关性,将模型失配问题转化为一定区间上偏相关系数的分布问题。通过观察各通道偏相关系数的分布图判断是否发生失配,并通过Shell塔实验验证该方法的有效性。

关键词: 模型失配, 模型预测控制, 相关性分析, 偏相关性分析, 实验验证

Abstract:

In practice, model-plant mismatch(MPM) is a key factor that results in performance deterioration in model predictive control(MPC). Traditional correlation analysis between the prediction residual and the manipulated variable of a channel is usually affected by other manipulated variables and disturbance. The result of this process is unreliable, thus unable to locate the MPM accurately. Based on the above problems, partial correlation analysis is used to calculate the correlation between the prediction residual and the manipulated variable of each channel, under the premise of removing the effect of other manipulated variables and disturbance. The MPM problem is converted to a distribution problem of partial correlation coefficients in a certain interval. Whether a channel is mismatched is judged by observing the distribution graph of partial correlation coefficients. The experimental validation on the Shell tower demonstrates the effectiveness of this method.

Key words: model-plant mismatch, model predictive control, correlation analysis, partial correlation analysis, experimental validation

中图分类号:

TP277

李秋美, 田学民, 尚林源. 基于偏相关性分析的MPC控制器模型失配检测[J]. 化工学报, 2016, 67(3): 852-857.

LI Qiumei, TIAN Xuemin, SHANG Linyuan. Detection of model-plant mismatch based on partial correlation analysis of MPC controllers[J]. CIESC Journal, 2016, 67(3): 852-857.

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基于偏相关性分析的MPC控制器模型失配检测

Detection of model-plant mismatch based on partial correlation analysis of MPC controllers

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