초록 ▼

A model predictive controller for a process control system which includes a real-time executive sequencer and an interactive modeler. The interactive modeler includes both a process model and an independent disturbance model. The process model represents the dynamic behavior of the physical process,

A model predictive controller for a process control system which includes a real-time executive sequencer and an interactive modeler. The interactive modeler includes both a process model and an independent disturbance model. The process model represents the dynamic behavior of the physical process, while the disturbance model represents current and future deviations from the process model. The interactive modeler estimates current process states from the process model and input data received from the executive sequencer. The executive sequencer then projects a set of future process parameter values, which are sought to be controlled, over a predetermined control horizon. The interactive modeler then solves a set of equations as to how the physical process will react to control changes in order to determine an optimized set of control changes. As a result, the process control system will be able to accurately track a predetermined set-point profile in the most effective and cost efficient manner.

대표청구항 ▼

[ What is claimed is:] [1.] A method of executing real-time control of an apparatus, comprising the steps of:receiving input signals which represent measured parameter values from a plurality of sensors in said apparatus;periodically transmitting a time-recorded set of said measured parameter values

[ What is claimed is:] [1.] A method of executing real-time control of an apparatus, comprising the steps of:receiving input signals which represent measured parameter values from a plurality of sensors in said apparatus;periodically transmitting a time-recorded set of said measured parameter values to an interactive modeler which includesa nonlinear process model having an on-line version for use in said real-time execution of control wherein said on-line version is derived from dynamic behavior in said process,an independent disturbance model having an on-line version for use in said real-time execution of control wherein said on-line version provides an error model for predicting future model error,an integrated model building function for use in building a future version of said process model and a future version of said disturbance model, andan integrated adaptive function for selectively enabling change of the process model on-line version and, alternatively, the disturbance model on-line version into a respective future version and for enabling said respective future version to replace the respective on-line version at a user-specified moment and thereby effect a new respective said on-line version wherein said change is enabled while said interactive modeler is in on-line use in said real-time execution of control;estimating the current state of at least one unmeasured process parameter in said interactive modeler from said process model;projecting a desired set of desired directly controlled parameter values and at least one desired indirectly controlled parameter value over a predetermined control horizon;periodically estimating how said apparatus will react to proposed changes to the value of at least one manipulated parameter over said control horizon, and determining a set of current and future manipulated parameter values which will minimize deviations from said desired set; andcausing a process control device in said apparatus to implement said manipulated parameter values.