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 ...

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 ...

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 ...

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.

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

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 ...

Dr. Suruchi Kothari, BSc, MD, MRCGP, MSx: Health tech innovator reshaping clinical care. Driven by a tech-forward, patient-centric approach. Imagine a healthcare system where a patient's heart monitor ...