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 ...

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 ...

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 ...

Model Predictive Control (MPC) is a modern feedback law that generates the control signal by solving an optimal control problem at each sampling time. This approach is capable of maximizing a certain ...

More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems. It aims to strike a balance between traditional ...

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 ...

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 ...

The air conditioner compressor motor driver as shown in Fig.1 utilizes advanced model-free predictive control technology, ensuring efficient and stable operation under varying load conditions.

Image of digital twin control, in which real plasma is controlled by virtual plasma reproduced on a computer. In this research, we developed a digital twin control system that can estimate optimal ...

The operating profiles of traditional generators has changed to manage the variability of renewable resources. Several critical processes were not engineered to manage these highly variable operating ...