Researchers at Durham University have developed a new system that enables drones to fly in precisely coordinated swarm ...

Model Predictive Control (MPC) has emerged as a leading strategy in advanced process control, offering the ability to anticipate future process behaviour and manage constraints in dynamic systems.

Model Predictive Control (MPC) is a modern feedback law that generates the control signal by solving an optimal control problem at each sampling time. This approach is capable of maximizing a certain ...

Model predictive control (MPC) is a well-established technology for multivariable processes that was originally developed in the 1970s with the introduction of digital computer-based control systems.

This article presents the development of coordinated control of throttle, spark advance, and variable valve timing (VVT) in a model predictive control (MPC) framework for engine idle speed control ...

In a groundbreaking advancement for motor control, Model-Free Predictive Control (MFPC) technology has emerged as a revolutionary advancement. This innovative approach enables motors to operate ...

An international research team has tested a hybrid control technique combining adapted perturb and observe (APO) with model-predictive control to address complex partial shading in solar arrays ...

The findings show that a predictive control system powered by a learned “tactile forward model” allows robots to anticipate when an object is likely to slip, continuously analysing its planned ...

By Andrew Masuda, UCSB UC Santa Barbara professor James B. Rawlingshas been named the 2025 recipient of the Richard E. Bellman Control Heritage Award, the nation’s top recognition for career ...

Model-predictive control is a proven solution that: Responds predictively to dynamic conditions caused by constant load changes.