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 ...

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 ...

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 ...

How Governance-by-Design Frameworks Are Reshaping Responsible AI in Enterprise Systems As artificial intelligence cont ...

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

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 ...

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 ...

A technical paper titled “Data-driven power modeling and monitoring via hardware performance counter tracking” was published by researchers at ETH Zürich, Scuola Superiore Sant’Anna, RISE Research ...

You often hear entrepreneurs say, “We don’t know what we don’t know,” when talking about deficiencies in data gathering. But when you have data in silos, it’s more a case of “We don’t know what we DO ...