Subspace identification for data‐driven modeling and quality control of batch processes

B Corbett, P Mhaskar - AIChE Journal, 2016 - Wiley Online Library
In this work, we present a novel, data‐driven, quality modeling, and control approach for
batch processes. Specifically, we adapt subspace identification methods for use with batch …

Process systems engineering tools in the pharmaceutical industry

GM Troup, C Georgakis - Computers & Chemical Engineering, 2013 - Elsevier
The purpose of this paper is to provide a summary of the current state of the application of
process systems engineering tools in the pharmaceutical industry. In this paper, we present …

Data‐driven model predictive quality control of batch processes

S Aumi, B Corbett, T Clarke‐Pringle… - AIChE Journal, 2013 - Wiley Online Library
The problem of driving a batch process to a specified product quality using data‐driven
model predictive control (MPC) is described. To address the problem of unavailability of …

Latent variable model predictive control for trajectory tracking in batch processes: Alternative modeling approaches

M Golshan, JF MacGregor, P Mhaskar - Journal of Process Control, 2011 - Elsevier
Several Latent Variable Model (LVM) structures for modeling the time histories of batch
processes are investigated from the view point of their suitability for use in Latent Variable …

[HTML][HTML] A novel linear hybrid model predictive control design: application to a fed batch crystallization process

A McKay, D Ghosh, L Zhu, L Xi, P Mhaskar - Digital Chemical Engineering, 2022 - Elsevier
This paper addresses the problem of enabling the use of complex first principles model
information as part of a linear Model Predictive Control implementation for improved control …

[HTML][HTML] Uneven batch data alignment with application to the control of batch end-product quality

J Wan, O Marjanovic, B Lennox - ISA transactions, 2014 - Elsevier
Batch processes are commonly characterized by uneven trajectories due to the existence of
batch-to-batch variations. The batch end-product quality is usually measured at the end of …

Ensemble learning based latent variable model predictive control for batch trajectory tracking under concept drift

DH Jeong, JM Lee - Computers & Chemical Engineering, 2020 - Elsevier
Industrial batch processes are characterized by unsteady state, multiple lines, and iterative
operation. For tracking a reference trajectory varying batch-wisely, several latent variable …

Latent variable model predictive control for trajectory tracking in batch processes: internal model control interpretation and design methodology

H Yu, J Flores-Cerrillo - Industrial & Engineering Chemistry …, 2013 - ACS Publications
In this paper, a theoretical analysis of the latent variable model predictive control (LV-MPC)
algorithm, originally proposed by Flores-Cerrillo and MacGregor, 1 is presented. The …

Trajectory tracking and point stability of three-axis aero-dynamic pendulum with MPC strategy in disturbance environment

X Liu, J Xu, Y Liu - Assembly Automation, 2021 - emerald.com
Purpose The purpose of this research on the control of three-axis aero-dynamic pendulum
with disturbance is to facilitate the applications of equipment with similar pendulum structure …

Application of Weighted Latent Variable Model Predictive Control in Batch Process Temperature Control

F Al Thobiani, M Ammami, A Shamekh… - … on Automatic Control …, 2022 - ieeexplore.ieee.org
This paper presents a Weighted version of the Latent Variable Model Predictive Control
(WLV-MPC) to address the control solution instability of the original LV-MPC algorithm that is …