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Model Predictive Control (MPC) has emerged as a pivotal strategy for optimising the performance of power electronic converters and motor drive systems.
Model Predictive Control and Tuning Methods Publication Trend The graph below shows the total number of publications each year in Model Predictive Control and Tuning Methods.
“Challenging problems, like enabling predictive maintenance or dynamic control, are better addressed with machine learning than classical control.” Illustrating her point is the model predictive ...
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 ...
The most common automated multivariable control technology in use today is model-predictive control (MPC). Prominent characteristics of MPC include the use of detailed process models, embedded ...
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 ...
Researchers at Durham University have developed a new system that enables drones to fly in precisely coordinated swarm ...
In this article, a model predictive self-tuning regulator (MP-STR) with adaptive variable functioning (AVF) is designed for fuel injection feedback control. Proper control of wall-wetting effects in ...
The Rockwell Automation Pavilion8 Model Predictive Control application helps manufacturers achieve precision in a dynamic market, reducing product variability, while increasing yield and lowering ...
Outbreaks of dollar spot can be challenging and costly to control. Traditional fungicide control methods involve calendar-based applications made regardless of disease incidence. Researchers at ...
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 ...
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