Patrick S Mccroskey

US Patent:

60567813, May 2, 2000

Filed:

Feb 6, 1998

Appl. No.:

9/020141

Inventors:

John M. Wassick - Midland MI
Patrick S. McCroskey - Midland MI
John J. McDonough - Midland MI
David K. Steckler - Midland MI

Assignee:

The Dow Chemical Company - Midland MI

International Classification:

G06G 748
G06G 758

US Classification:

703 12

Abstract:

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.

US Patent:

57400334, Apr 14, 1998

Filed:

Oct 13, 1992

Appl. No.:

7/959629

Inventors:

John M. Wassick - Midland MI
Patrick S. McCroskey - Midland MI
John J. McDonough - Midland MI
David K. Steckler - Midland MI

Assignee:

The Dow Chemical Company - Midland MI

International Classification:

G05B 1304

US Classification:

364149

Abstract:

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.