Large commercial and institutional buildings face significant challenges in maintaining thermal comfort while minimizing ...

So, implementing more precise and reliable control strategies for robots is becoming increasingly important. To this end, a novel hybrid control methodology, composed of a ...

The purpose of this paper is to investigate the possible implementation of the Fast model predictive control (MPC) scheme for chemical systems. Due to the difficulties associated with complicated ...

Modern pumping systems and precision control valves are revolutionizing how power generation facilities manage their critical fluid systems, delivering substantial energy savings, reduced ...

In this article, we advance a compensation matrix based model predictive control (CMB-MPC) framework for the register control of roll-to-roll (R2R) printing systems to overcome the deficiencies of ...

This document explains the implementation of the Koopman Operator in conjunction with Model Predictive Control (MPC) . A nonlinear dynamic system is controlled by leveraging the linearity of the ...

DL-MPC (deep learning model predictive control) is a software toolkit developed based on the Python and TensorFlow frameworks, designed to enhance the performance of traditional Model Predictive ...

Combustion control is one such example. The recommendation is to upgrade to a DCS with advanced process control (APC) software for model predictive control (MPC) based on dynamic matrix control (DMC) ...

This study presents an advanced Model Predictive Control (MPC) technique designed to mitigate Circulating Current (CC) in HVDC systems equipped with Modular Multilevel Converters (MMC). This MPC ...

Nova Chemicals Corp. used a holistic, best-practices approach to help sustain and improve the performance of control system assets at its Joffre, Alta., ethylene plant.