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

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 ...

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 ...

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.

(A) 3D model of the manipulator structure, consisting of 3 continuum segments. The manipulator operates in the plane. (B) Close-up view of the revolute joint between adjacent disks. (C) Diagram ...

Data is one of organizations' most potent assets in an era of growing competition and artificial intelligence (AI) mandates. However, effectively managing and using it requires balancing strict ...

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 ...