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 ...

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 ...

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

Quick diagnostic sprints deliver measurable results in weeks, not years, helping manufacturers prove AI value before ...

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 ...

There is no question that each generation of technology is different from the last. In this sense, many would think that ...

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 ...

According to MarketsandMarkets™, the data center access control market is expected to grow from USD 1.55 billion in 2025 to ...

The proposed system in Delhi will use hyperlocal sensors and dynamic source apportionment for targeted interventions.