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 ...

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 ...

Let's discuss why AI-powered data management is becoming essential in industrial automation and how organizations can build it successfully.

Vast Data expands AI Operating System with global control plane, zero-trust agent framework and deeper Nvidia integration - ...

In the race to net-zero emissions, real-time data is the unsung hero. Event-driven systems—powered by technologies like Apache Kafka—are transforming how industries manage energy, optimize resources ...

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 finance and operations leaders can take back control of their telecom spending by using a data-driven approach ...

Atal Bansal is the Founder and CEO at Chetu, a global U.S.-based custom software solutions and support services provider. For centuries, quality control inspection has been time-consuming and ...

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 ...