Stability monitoring of batch processes with iterative learning control
type: Item
instance of: scholarly article
title: Stability monitoring of batch processes with iterative learning control
zbMATH Open document ID: 1401.93160
DOI: 10.1155/2017/5912651
author: Yan Wang
author: Junwei Sun
author: Lexiang Wang
author: Tai-Shan Lou
published in: Advances in Mathematical Physics
publication date: 2018-10-23T00:00:00Z
review text: Summary: 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 is 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 is adopted to monitor those stability indices. Numerical results are presented to demonstrate the effectiveness of the proposed method.
Mathematics Subject Classification ID: 93D05
Mathematics Subject Classification ID: 93C83
zbMATH DE Number: 6962646
zbMATH Keywords: iterative learning control
zbMATH Keywords: stability monitoring
zbMATH Keywords: batch processes
Wikidata QID: Q59142452
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2017/5912651
OpenAlex ID: W2584755352
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description: scientific article; zbMATH DE number 6962646