Mathematical models of biochemical reaction networks are important tools in systems
biology and systems medicine, eg, to analyze disease causes or to make predictions for the …

One purpose of the" Historical Perspectives" column is to look back at work done by
pioneers in control and related fields that has been neglected for many years but was later …

Air suspension is one of the heart of electrified chassis, which plays a key role in vehicle ride
comfort, driving stability and safety. In order to further improve the suspension performance …

The performance of model-based bioprocess optimizations depends on the accuracy of the
mathematical model. However, models of bioprocesses often have large uncertainty due to …

This paper considers the model predictive control of dynamic systems subject to stochastic
uncertainties due to parametric uncertainties and exogenous disturbance. The effects of …

In model‐based optimization in the presence of model‐plant mismatch, the set of model
parameter estimates which satisfy an identification objective may not result in an accurate …

The stochastic linear-quadratic regulator problem subject to Gaussian disturbances is well
known and usually addressed via a moment-based reformulation. Here, we leverage …

This work proposes model based approaches for on-line or off-line economic optimization of
batch reactors in the presence of model error (uncertainty). Polynomial Chaos Expansions …

Many advances in the development of nano and microchemical systems have occurred in
the last decade. These systems have significant associated identification and control …

This paper studies the model predictive control of dynamic systems subject to stochastic
parametric uncertainty due to plant/model mismatches and exogenous disturbance that …