Global self-optimizing control of batch processes

Fuente: arXiv
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Autori principali: Zhou, Chenchen, Su, Hongxin, Tang, Xinhui, Cao, Yi, Yang, Shuang-hua
Natura: Preprint
Pubblicazione: 2026
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author Zhou, Chenchen
Su, Hongxin
Tang, Xinhui
Cao, Yi
Yang, Shuang-hua
author_facet Zhou, Chenchen
Su, Hongxin
Tang, Xinhui
Cao, Yi
Yang, Shuang-hua
contents This work considers to achieve near-optimal operation for a class of batch processes by employing self-optimizing control (SOC). Comparing with a continuous one, a batch process exhibits stronger nonlinearity with dynamics because of the non-steady operation condition. This necessitates a global version of SOC to achieve satisfactory performance. Meanwhile, it also makes the existing global SOC (gSOC) not directly applicable to batch processes due to the causality amongst variables. Therefore, it is necessary to extend the original gSOC to batch processes. In addition to the nonconvexity challenge of the original gSOC problem, the new extension for batch processes has to face even more challenges. Particularly, the causality due to dynamics of batch processes brings in structural constraints on controlled variables (CVs), making a CV selection problem even more difficult. To address these challenges, the gSOC problem is recast in a vectorized formulation and it is proved that the structural constraints considered are linear in the vectorized formulation. Moreover, a novel shortcut method is proposed to efficiently find sub-optimal but more transparent solutions for this problem. The effectiveness of the new approach is validated through a case study of a fed-batch reactor, where CVs are constructed through a combination matrix with a repetitive structure, resulting in a simple SOC scheme. This simplicity facilitates the implementation of the SOC approach and enhances its practical applicability and robustness.
format Preprint
id arxiv_https___arxiv_org_abs_2605_06495
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Global self-optimizing control of batch processes
Zhou, Chenchen
Su, Hongxin
Tang, Xinhui
Cao, Yi
Yang, Shuang-hua
Optimization and Control
Systems and Control
This work considers to achieve near-optimal operation for a class of batch processes by employing self-optimizing control (SOC). Comparing with a continuous one, a batch process exhibits stronger nonlinearity with dynamics because of the non-steady operation condition. This necessitates a global version of SOC to achieve satisfactory performance. Meanwhile, it also makes the existing global SOC (gSOC) not directly applicable to batch processes due to the causality amongst variables. Therefore, it is necessary to extend the original gSOC to batch processes. In addition to the nonconvexity challenge of the original gSOC problem, the new extension for batch processes has to face even more challenges. Particularly, the causality due to dynamics of batch processes brings in structural constraints on controlled variables (CVs), making a CV selection problem even more difficult. To address these challenges, the gSOC problem is recast in a vectorized formulation and it is proved that the structural constraints considered are linear in the vectorized formulation. Moreover, a novel shortcut method is proposed to efficiently find sub-optimal but more transparent solutions for this problem. The effectiveness of the new approach is validated through a case study of a fed-batch reactor, where CVs are constructed through a combination matrix with a repetitive structure, resulting in a simple SOC scheme. This simplicity facilitates the implementation of the SOC approach and enhances its practical applicability and robustness.
title Global self-optimizing control of batch processes
topic Optimization and Control
Systems and Control
url https://arxiv.org/abs/2605.06495