That’s the aim of predictive cyber resilience (PCR)—an emerging approach to security built on intelligence, automation and ...

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

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 ...

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 ...

Once a tool for aerospace engineers, digital twins are now helping the food industry make proactive, data-driven decisions.

Troy Mahr, Director, Rockwell Automation, explains how achieving autonomous operations requires integrating industrial data and AI to eliminate silos ...

Heat pumps are quickly overtaking traditional heating systems in American homes, as they are more efficient and environmentally friendly. But without a proper control system, they could spike a ...

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 ...

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 ...

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 ...