How organizations make use of their data from the back office to the production line to improve performance, reduce risk and ...

Tellarini discusses how ABB's approach balances cutting-edge digital solutions with pragmatic retrofit strategies, ensuring ...

Researchers from the University of Chinese Academy of Sciences and collaborating institutions have developed a novel ...

That’s the aim of predictive cyber resilience (PCR)—an emerging approach to security built on intelligence, automation and ...

As AI is embedded inside systems, teams must design APIs with governance, observability and scalability in mind.

The journey towards autonomous operations involves incremental steps, each bringing businesses closer to a state where systems can independently manage and optimize processes, ensuring sustained ...

It’s not very common that a robot the size of a paper clip is able to do ten flips in eleven seconds and keep on course within five centimeters, says Markus Waibel of Waibel Robotics in Zurich. But ...

Abstract: Model predictive control (MPC) has attracted considerable interest for its ability to generate optimal control strategies, yet its application to nonlinear systems is often constrained by ...

This document provides a detailed explanation of the MATLAB code that demonstrates the application of the Koopman operator theory for controlling a nonlinear system using Model Predictive Control (MPC ...

UC Santa Barbara professor James B. Rawlings has been named the 2025 recipient of the Richard E. Bellman Control Heritage Award, the nation’s top recognition for career contributions to automatic ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.