Stability Monitoring of Batch Processes with Iterative Learning Control

In recent years, the iterative learning control (ILC) is widely used in batch processes to improve the quality of the products. Stability is a preoccupation of batch processes when the ILC is applied. Focusing on the stability monitoring of batch processes with ILC, a method based on innerwise matri...

Full description

Saved in:
Bibliographic Details
Main Authors: Yan Wang, Junwei Sun, Taishan Lou, Lexiang Wang
Format: Article
Language:English
Published: Wiley 2017-01-01
Series:Advances in Mathematical Physics
Online Access:http://dx.doi.org/10.1155/2017/5912651
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850167141713575936
author Yan Wang
Junwei Sun
Taishan Lou
Lexiang Wang
author_facet Yan Wang
Junwei Sun
Taishan Lou
Lexiang Wang
author_sort Yan Wang
collection DOAJ
description In recent years, the iterative learning control (ILC) is widely used in batch processes to improve the quality of the products. Stability is a preoccupation of batch processes when the ILC is applied. Focusing on the stability monitoring of batch processes with ILC, a method based on innerwise matrix with considering the uncertainty of the model and disturbance was proposed. First, the batch process with ILC was derived as a two-dimensional autoregressive and moving average (2D-ARMA) model. Then two kinds of stability indices are constructed based on the innerwise matrix through the identification of the 2D-ARMA. Finally, the statistical process control (SPC) chart was adopted to monitor those stability indices. Numerical results are presented to demonstrate the effectiveness of the proposed method.
format Article
id doaj-art-db7a9c1237cf4ccfa81b667898b098de
institution OA Journals
issn 1687-9120
1687-9139
language English
publishDate 2017-01-01
publisher Wiley
record_format Article
series Advances in Mathematical Physics
spelling doaj-art-db7a9c1237cf4ccfa81b667898b098de2025-08-20T02:21:16ZengWileyAdvances in Mathematical Physics1687-91201687-91392017-01-01201710.1155/2017/59126515912651Stability Monitoring of Batch Processes with Iterative Learning ControlYan Wang0Junwei Sun1Taishan Lou2Lexiang Wang3College of Electronic and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaCollege of Electronic and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaCollege of Electronic and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaCollege of Electronic and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaIn recent years, the iterative learning control (ILC) is widely used in batch processes to improve the quality of the products. Stability is a preoccupation of batch processes when the ILC is applied. Focusing on the stability monitoring of batch processes with ILC, a method based on innerwise matrix with considering the uncertainty of the model and disturbance was proposed. First, the batch process with ILC was derived as a two-dimensional autoregressive and moving average (2D-ARMA) model. Then two kinds of stability indices are constructed based on the innerwise matrix through the identification of the 2D-ARMA. Finally, the statistical process control (SPC) chart was adopted to monitor those stability indices. Numerical results are presented to demonstrate the effectiveness of the proposed method.http://dx.doi.org/10.1155/2017/5912651
spellingShingle Yan Wang
Junwei Sun
Taishan Lou
Lexiang Wang
Stability Monitoring of Batch Processes with Iterative Learning Control
Advances in Mathematical Physics
title Stability Monitoring of Batch Processes with Iterative Learning Control
title_full Stability Monitoring of Batch Processes with Iterative Learning Control
title_fullStr Stability Monitoring of Batch Processes with Iterative Learning Control
title_full_unstemmed Stability Monitoring of Batch Processes with Iterative Learning Control
title_short Stability Monitoring of Batch Processes with Iterative Learning Control
title_sort stability monitoring of batch processes with iterative learning control
url http://dx.doi.org/10.1155/2017/5912651
work_keys_str_mv AT yanwang stabilitymonitoringofbatchprocesseswithiterativelearningcontrol
AT junweisun stabilitymonitoringofbatchprocesseswithiterativelearningcontrol
AT taishanlou stabilitymonitoringofbatchprocesseswithiterativelearningcontrol
AT lexiangwang stabilitymonitoringofbatchprocesseswithiterativelearningcontrol