Fed-batch fermentation is an important production technology in the biochemical industry.
Using fed-batch Saccharomyces cerevisiae fermentation as a prototypical example, we …

Batch processes are often characterized by inherent nonlinearity, multiplicity of operating
phases, and batch-to-batch variations, which poses great challenges for accurate and …

Traditional soft sensors may be ill-suited for batch processes because they cannot efficiently
handle process nonlinearity and/or time-varying changes as well as provide the prediction …

Bioreactors (fermenters) are the key unit operation in biopharmaceutical, brewing,
biochemical, biofuel, and waste treatment processes. The need for monitoring, control, and …

This article addresses the issue of outlier detection in industrial data using robust
multivariate techniques and soft sensing of clinker quality in cement industries. Feed-forward …

In process industry, the lack of sufficient labeled data often leads to poor performance of
traditional supervised soft sensors. Thus, a pseudo label estimation method based on label …

Just-in-time learning (JIT) has recently gained growing popularity for soft sensor
development of nonlinear processes. However, traditional JIT methods aim to pursue a …

Soft sensors have been widely used to estimate difficult-to-measure variables in the process
industry. However, the nonlinear nature and time-varying behavior of many processes pose …

This work presents a new method for adaptive soft sensor development by further exploiting
just-in-time modeling framework. In the presented method, referred to as online local …

The problem of optimal profiles tracking control under uncertainties for a nonlinear fed-batch
bioprocess is addressed in this paper. Based on the results reported by Pantano et al.[Ind …