Modularized model predictive control for industrial plants
Abstract:
A method for generating a dynamic model of an industrial plant having: a plurality of physical processes that are dependent such that an outcome of at least one first process is fed into at least one second process; a plurality of low-level controllers, each controller acting upon at least one physical process such that at least one process variable of the at least one physical process is controlled to match a set-point of the low-level controller; and a plurality of sensors, each sensor measuring at least one process variable of one of the physical processes, and/or of the plant as a whole, the set-points of the low-level controllers and current values of the process variables measured by the sensors being the inputs of the model, and predicted future values of the process variables that are likely to result from applying the set-points to the low-level controllers being the outputs.
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