Streamline Control and Snowflake deliver a unified data foundation that helps energy organizations modernize faster and ...

Data-driven control represents a paradigm shift in the design and implementation of controllers for both linear and nonlinear systems. Eschewing traditional reliance on first‐principles models, this ...

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 ...

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 ...

To govern AI safely and keep its speed advantage, enterprises must move from static, rule-based control systems to adaptive, AI-aware access governance.

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.

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

For today’s CISOs, the perimeter isn’t a firewall — it’s the data itself. Hybrid and multi-cloud architecture have created massive volumes of sensitive ...

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 ...