Stochastic Model Predictive Control (SMPC) for linear systems is an advanced control framework that blends systematic optimisation with probabilistic forecasting. By explicitly accounting for ...

Predictive control techniques, particularly Model Predictive Control (MPC), have emerged as a transformative solution in the management of irrigation canal systems. These methods allow for the ...

Applying model-predictive methods and a continuous process-control framework to a continuous tablet-manufacturing process. Currently, there is a high level of interest in the pharmaceutical industry ...

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 ...

The enhanced plant performance achieved at the 1,477-MW Morgantown Generating Station shows the value of model predictive control in conjunction with intelligent distributed control algorithms. This ...

To improve the dynamic response performance of a high-flow electro-hydraulic servo system, scholars have conducted considerable research on the synchronous and time-sharing controls of multiple valves ...

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 ...

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 ...

Fraunhofer ISE researchers are applying deep learning and digital twin modelling tools to optimize PV tracker control systems for use in farming and biodiversity projects. The goal is to be able to ...

Electrical machines consume nearly half of all the electrical power generated worldwide, making them one of the top contributors to carbon dioxide emissions. If we are to develop sustainable societies ...