Multivariable control method and system without detailed prediction model

• US 6,760,631 B1
• Filed: 10/04/2000
• Issued: 07/06/2004
• Est. Priority Date: 10/04/2000
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Poe, William A., Smith, Paul Burnham, Berkowitz, Peter N.
• Primary Examiner(s): PATEL, RAMESH B
• Application Number:
  US09/677,856
• Time in Patent Office: 1,371 Days
• Field of Search: 700/28-31, 700/34, 700/46, 700/52, 700/53, 700/67, 700/68, 700/73, 700/74, 700/33, 700/37, 700/41-45, 700/82, 318/561, 318/609-610
• US Class Current: 700/28
• CPC Class Codes: G05B 13/024 in which a parameter or coefficient is automatically adjusted to optimise the performance

Abstract

A multivariable control method and system suitable for manipulating process variables based on observed changes in controlled objectives without extensive data analysis or involved model development. The method includes operating the process at an initial set of process variables and an initial set of controlled objectives, monitoring the set of process variables and the set of controlled objectives while continuously operating the process, adjusting one or more members of the set of process variables based upon a non-linear optimization with respect to a desired set of controlled objectives, and utilizing the monitored set of process variables and the monitored set of controlled objectives in the non-linear optimization.

Claims

1. A multivariable control method for controlling a process, the process being characterized by a first set of process variables and a first set of controlled objectives, comprising the steps of:

operating the process at an initial set of process variables and an initial set of controlled objectives;

monitoring the first set of process variables and the first set of controlled objectives while continuously operating the process;

monitoring an effect that changes in the first set of process variables have on the first set of controlled objectives, wherein a monitored set of process variables is generated from the changes in the first set of process variables, and a monitored set of controlled objectives is generated from the effect that changes in the first set of variables have on the first set of controlled objectives; and

adjusting one or more members of the monitored set of process variables based upon a non-linear optimization with respect to a desired set of controlled objectives, utilizing the monitored set of process variables and the monitored set of controlled objectives in the non-linear optimization, wherein said adjusting one or more members of the monitored set of process variables includes changing at least one of the members of the monitored set of process variables, and the monitored set is a modified version of the initial set of process variables input to a device.

2. A method in accordance with claim 1 wherein said step of monitoring the first set of process variables comprises the step of determining the changes in the first set of process variables and monitoring the changes.

3. A method in accordance with claim 2 wherein said step of utilizing the monitored set of process variables comprises the step of utilizing the changes in the first set of process variables in the non-linear optimization.

4. A method in accordance with claim 1 wherein said step of monitoring the first set of process variables further comprises the step of determining rates of change of the first set of process variables and monitoring the rates of change.

5. A method in accordance with claim 4 wherein said step of utilizing the monitored set of process variables further comprises the step of utilizing the rates of change in the first set of process variables in the non-linear optimization.

6. A method in accordance with claim 1 wherein the process produces a quantity of a product and the first set of controlled objectives excludes the quantity of the product.

7. A method in accordance with claim 1 wherein said step of monitoring the first set of controlled objectives comprises the step of determining changes in the first set of controlled objectives and monitoring the changes.

8. A method in accordance with claim 7 wherein the step of utilizing the monitored set of controlled objectives comprises the step of utilizing the changes in the first set of controlled objectives in the non-linear optimization.

9. A method in accordance with claim 1 wherein said step of monitoring the first set of controlled objectives further comprises the step of determining rates of change in the first set of controlled objectives and monitoring the rates of changes.

10. A method in accordance with claim 9 wherein the step of utilizing the monitored set of controlled objectives comprises the step of utilizing the rates of change in the first set of controlled objectives in the non-linear optimization.

11. A method in accordance with claim 1 wherein said step of adjusting one or more members of the monitored set of process variables based upon a non-linear optimization comprises the steps of:

utilizing a processor configured to execute a non-linear optimization problem solver program; and

utilizing the problem solver program to calculate future sets of process variables that will result in the process maintaining the desired set of controlled objectives during operation.

12. A multivariable control system for controlling a production process characterized by a first set of process variables and a first set of controlled objectives, said system comprising:

a process device configured to produce material characterized by a desired set of controlled objectives, the desired set of controlled objectives comprising a specified color quality, a specified texture quality, and a specified density quality; and

a processor configured to control said process device by adjusting the first set of process variables based upon a non-linear optimization with respect to the desired set of controlled objectives, the first set of process variables comprising values of an internal temperature of said process device, values of amounts of different color materials input to said process device, and values of a flow rate of material input to said process device, wherein the first set of process variables that are adjusted are a modified version of an initial set of process variables input to said process device.

13. A system in accordance with claim 12 wherein said system further configured to begin operation utilizing the initial set of process variables and an initial set of controlled objectives.

14. A system in accordance with claim 12 wherein said system further configured to:

monitor the first set of process variables and the first set of controlled objectives while continuously operating the process device;

generate a monitored set of process variables from a change in the first set of process variables;

generate a monitored set of controlled objectives from an effect that the change in the first set of process variables has on the first set of controlled objectives; and

utilize the monitored set of process variables and the monitored set of controlled objectives in the non-linear optimization.

15. A system in accordance with claim 14 wherein said system further configured to determine and monitor at least one of the change in the first set of process variables and a rate of change in the first set of process variables, said system further configured to utilize at least one of the change in the first set of process variables and the rate of change in the first set of process variables in the non-linear optimization.

16. A system in accordance with claim 14 wherein said system further configured to determine and monitor at least one of a change in qualitative values of the first set of controlled objectives and a rate of change in the qualitative values of the first set of controlled objectives, said system further configured to utilize at least one of the change in the qualitative values of the first set of controlled objectives and the rate of change in the qualitative values of the first set of controlled objectives in the non-linear optimization.

17. A system in accordance with claim 12 wherein said processor further configured to execute a non-linear optimization problem solver program, said non-linear optimization problem solver program configured to calculate future sets of process variables that will result in the process device maintaining desired qualities of a plastic produced.

18. A multivariable control system for controlling a production process characterized by a first set of process variables and a first set of controlled objectives, said system comprising:

a process device configured to produce a product characterized by the first set of controlled objectives; and

a processor configured to control said process device by adjusting the first set of process variables based upon a non-linear optimization with respect to the first set of controlled objectives, wherein the first set of process variables that are adjusted are a modified version of an initial set of process variables input to said process device.

19. A system in accordance with claim 18 wherein said system further configured to begin operation utilizing the initial set of process variables and an initial set of controlled objectives.

20. A system in accordance with claim 18 wherein said system further configured to:

monitor the first set of process variables and the first set of controlled objectives while continuously operating the process device;

generate a monitored set of process variables from a change in the first set of process variables;

generate a monitored set of controlled objectives from an effect that the change in the first set of process variables has on the first set of controlled objectives; and

utilize the monitored set of process variables and the monitored set of controlled objectives in the non-linear optimization.

21. A system in accordance with claim 20 wherein said system further configured to determine and monitor at least one of the change in the first set of process variables and rates of change in the first set of process variables, said system further configured to utilize at least one of the change in the first set of process variables and the rates of change in the first set of process variables in the non-linear optimization.

22. A system in accordance with claim 20 wherein said system further configured to determine and monitor at least one of a change in the first set of controlled objectives and rates of change in the first set of controlled objectives, said system further configured to utilize at least one of the change in the first set of controlled objectives and the rates of change in the first set of controlled objectives in the non-linear optimization.

23. A system in accordance with claim 18 wherein said processor further configured to execute a non-linear optimization problem solver program.

24. A system in accordance with claim 23 wherein said non-linear optimization problem solver program configured to calculate future sets of process variables that will result in the process device maintaining a desired set of controlled objectives.