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 ...

Economic Model Predictive Control (EMPC) represents an evolution of traditional control strategies, where the primary objective is to directly optimise an economic cost function rather than merely ...

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 ...

The journey towards autonomous operations involves incremental steps, each bringing businesses closer to a state where systems can independently manage and optimize processes, ensuring sustained ...

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 ...

TotalEnergies' deployment of machine learning at its Port Arthur, Texas, refinery demonstrates how predictive AI can ...

Learn to apply control systems in automotive, energy, aerospace, robotics, and manufacturing sectors. Apply feedback control laws to stabilize systems and achieve performance goals. Control systems ...

As organizations modernize industrial systems, high-integrity functional safety strategies are now critical for reducing risk and ensuring compliance. This report delivers actionable insight into the ...