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Eindhoven University of TechnologyMASTER Model predictive control of a glass melting furnaceWassink, C.H.P. Award date: 1998Link to publicationDisclaimer This document contains a student thesis (bachelor\'s
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Define the system dynamics including the state-space model and the prediction horizon.
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Model predictive control (MPC) is an advanced control strategy that utilizes a dynamic model of the system to predict future behavior and optimize control actions by solving an optimization problem at each time step.
Those who are required to file model predictive control reports include organizations and entities that implement this control approach in their operations, typically in industries such as manufacturing, energy, and process control.
To fill out model predictive control forms, one should provide relevant details about the system being controlled, the predictive models used, the optimization algorithms applied, and data on performance metrics and compliance with operational objectives.
The purpose of model predictive control is to enhance the performance and efficiency of a control system by anticipating future events and making proactive control decisions that optimize process outcomes.
Information typically required in reports on model predictive control includes system models, control strategies, performance metrics, and any deviations from expected operational standards.
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