Model Predictive Control (MPC) has emerged as a pivotal strategy for optimising the performance of power electronic converters and motor drive systems. By utilising an explicit model of the controlled ...

A new technique able to forecast how changes to parameters will impact biomanufacturing processes could revolutionize drug production, save manufacturers time and money, and help increase access to ...

Dynamic optimisation and model predictive control (MPC) are at the forefront of modern process systems engineering, offering robust methodologies to address the challenges posed by time-varying ...

Distillation columns are extensively deployed in the chemical process industries when there is a need for separation of components that have different boiling points. Typically, a mixture of ...

Today’s ac servo systems are much different than those built even 10 years ago. Faster processors and higher resolution encoders are enabling manufacturers to implement amazing advances in tuning ...

Researchers from Tongji University and Shanghai Jiao Tong University have developed a socially aware prediction-to-control pipeline that lets ...

ARC. ARC refers to a combination of a proportional-integral-derivative (PID) controller, signal selectors and split ranges, ...

Predictive modelling involves using a model of a process, usually a computer model, to predict a likely outcome. Model predictive control (MPC) takes this further and uses a dynamic model to calculate ...

In this article, as in industry, advanced process control (APC) refers primarily to multi-variable control. Multivariable control means adjusting multiple single-loop controllers in unison, to meet ...