Rockwell Automation Pavilion8 Model Predictive Control (MPC) software now empowers engineers to design and execute step tests faster, safer and more accurately. Unlike manual step tests that must be ...
Researchers from Austria’s University of Natural Resources and Life Sciences Vienna have presented a novel, low-tech model predictive control (MPC) algorithm for the grid-friendly operation of heat ...
Widespread and significant operational efficiencies expected when autonomous real-time process monitoring is deployed at major chemical plant in Italy. Founded in 1969, Fluorsid S.p.A. is involved in ...
Distillation columns are extensively deployed in the chemical process industries when there is a need for separation of components that have different boiling points. Typically, a mixture of ...
Bruce Slusser from Avanceon highlights how AI improves model predictive control (MPC) systems by increasing predictive accuracy and enabling real-time optimization of complex processes. The ...
In this article, as in industry, advanced process control (APC) refers primarily to multi-variable control. Multivariable control means adjusting multiple single-loop controllers in unison, to meet ...
Model Predictive Control (MPC) has emerged as a versatile and robust strategy in modern control engineering, enabling controllers to predict future system behaviour and optimise performance over a ...
Model Predictive Control (MPC) has emerged as a pivotal strategy for optimising the performance of power electronic converters and motor drive systems. By utilising an explicit model of the controlled ...
Marco Nicotra joined the CU Boulder faculty in 2018. He completed a double degree program in 2012, receiving an MS in mechanical engineering from Politecnico di Milano and an MS in electromechanical ...
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