Due to the lack or high costs of measurement devices to monitor and control metabolites in
microbial cultivation processes, state estimators are often required. These estimators …

Microbial fermentation processes are most often described by nonlinear time-varying
dynamics, which require the implementation of nonlinear state estimators to infer …

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 …

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 …

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 …

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 …