Global self-optimizing control of batch processes

TL;DR

This paper extends global self-optimizing control (gSOC) to batch processes, addressing nonlinearity and causality challenges, and proposes a novel shortcut method validated on a fed-batch reactor case study.

Contribution

The work develops a vectorized formulation of gSOC for batch processes, proving linearity of structural constraints and introducing an efficient shortcut solution method.

Findings

The proposed approach effectively manages nonlinearity and causality in batch processes.

A simple SOC scheme was successfully implemented on a fed-batch reactor.

The shortcut method yields transparent, sub-optimal solutions with practical robustness.

Abstract

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.