A Tuveri, HE Holck, CSM Nakama, J Matias… - IFAC-PapersOnLine, 2022 - Elsevier
Microbial fermentation processes are most often described by nonlinear time-varying dynamics, which require the implementation of nonlinear state estimators to infer …
M Elsheikh, R Hille, A Tatulea-Codrean… - Computers & Chemical …, 2021 - Elsevier
Advanced control and monitoring of bioprocesses are dependent on accurate state and parameter information. At the same time, bioprocesses are well known for their time-varying …
Bioprocess modeling has become a useful tool for prediction of the process future with the aim to deduce operating decisions (eg transfer or feeds). Due to variabilities, which often …
NPG Salau, JO Trierweiler, AR Secchi - Computer aided chemical …, 2012 - Elsevier
Nowadays many advanced control tools are available to improve industrial processes (eg virtual analyzers, state estimators, predictive and multivariable controllers, etc.). Particularly …
State estimation is a crucial part of the monitoring and/or control of all chemical processes. Among various approaches for this problem, moving horizon estimation (MHE) has the …
J Bae, Y Kim, JM Lee - Computers & Chemical Engineering, 2021 - Elsevier
Due to the model-plant mismatch in practical applications of a nonlinear model, it is necessary to estimate both states and model parameters online. However, when the number …
The moving horizon estimator (MHE) formulation utilizes a window of measurements to compute the estimates of the states in that particular window. This approach leads to …
R Alexander, S Dinh, G Schultz, MPA Ribeiro… - Computers & Chemical …, 2023 - Elsevier
In this work, extended Kalman filter (EKF) and moving horizon estimation (MHE)-based approaches are introduced and applied to a Galacto-oligosaccharides (GOS) bioprocess …
State estimation is a fundamental part of monitoring, control, and real-time optimization in continuous pharmaceutical manufacturing. For nonlinear dynamic systems with hard …