Modern control system design is increasingly embracing data-driven methodologies, which bypass the traditional necessity for precise process models by utilising experimental input–output data. This ...

Collaboration brings together refrigeration engineering expertise and industrial AI to optimize performance, energy ...

In the modelic control paradigm, the first step is to establish a dynamic model through system identification. This model offers a continuous but inaccurate description of state transition information ...

Vast Data expands AI Operating System with global control plane, zero-trust agent framework and deeper Nvidia integration - ...

AI can be added to legacy motion control systems in three phases with minimal disruption: data collection via edge gateways, non-interfering anomaly detection and supervisory control integration.

During Machine Design’s Motion Systems Takeover Week (Oct. 20–24, 2025), we explored how the fusion of mechanical motion and data-driven control is reshaping high-precision applications across ...

A research team has developed a novel method for estimating the predictability of complex dynamical systems. Their work, "Time-lagged recurrence: A data-driven method to estimate the predictability of ...

Modern warfare demands seamless coordination and interoperability among multinational forces for effective partnerships. Logistics, often referred to as the lifeblood of military operations, is a ...

The surge in adoption of renewable energy driven by carbon neutrality policies has created operational challenges for large thermal power plants. These plants must now accommodate rapid load ...