Dynamic controller utilizing a hybrid model

• US 8,036,763 B2
• Filed: 01/09/2009
• Issued: 10/11/2011
• Est. Priority Date: 09/13/2006
• Status: Active Grant

• Current Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Original Assignee: Rockwell Automation Technologies Incorporated (Allen-Bradley Co., Inc.)
• Inventors: Boe, Eugene, Piche, Stephen W., Martin, Gregory D.
• Primary Examiner(s): Decady; Albert
• Assistant Examiner(s): Lee; Douglas S
• Application Number:
  US12/351,456
• Publication Number:
  US 20090177291A1
• Time in Patent Office: 1,005 Days
• Field of Search: 700/29, 700/37, 700/39, 700/44, 703/2, 703/16, 703/23
• US Class Current: 700/44
• CPC Class Codes: G05B 13/042 in which a parameter or coefficient is automatically adjusted to optimise the performance
• CPC Class Codes: G05B 13/048 using a predictor
• CPC Class Codes: G05B 17/02 electric

Abstract

A system and method for predicting operation of a plant or process receive an input value from the plant or process. An integrity of a non-linear model corresponding to a local input space of the input value may be determined. The non-linear model may include an empirical representation of the plant or process. If the integrity is above a first threshold, non-linear model may be used to provide a first output value. However, if the integrity is below the first threshold, a linearized first principles model may be used to provide a second output value. The linearized first principles model may include an analytic representation of the plant or process. Additionally, the analytic representation of the plant or process may be independent of the empirical representation of the plant or process. The first output value and/or the second output value may be usable to manage the plant or process.

Claims

1. A process control system, comprising:

a non-linear model comprising an empirical representation of a plant or process, wherein the non-linear model is configured to receive an input value and generate a first output value using the empirical representation of the plant or process; and

a linearized first principles model comprising an analytic representation of the plant or process, wherein the linearized first principles model is configured to receive the input value and generate a second output value using the analytic representation of the plant or process;

wherein the first output value and/or the second output value is usable to control the plant or process.

2. The process control system of claim 1, comprising a domain analyzer operable to determine whether the input value falls within a region where the non-linear model has an integrity that is less than a first threshold.

3. The process control system of claim 2, comprising a controller configured to use the non-linear model when the integrity is above the first threshold and to use the linearized first principles model when the integrity is below the first threshold.

4. The process control system of claim 3, wherein the domain analyzer is configured to determine whether the input value falls within a region where the non-linear model has an integrity that is less than a second threshold, wherein the second threshold is lower than the first threshold.

5. The process control system of claim 4, wherein the controller is configured to use the non-linear model when the integrity is above the first threshold, to use a first principles model when the integrity is above the second threshold and below the first threshold, and to use the linearized first principles model when the integrity is below the second threshold.

6. The process control system of claim 1, wherein the non-linear model comprises a steady-state model.

7. The process control system of claim 1, wherein the non-linear model comprises a neural network or a support vector machine.

8. The process control system of claim 1, wherein the linearized first principles model comprises a local linearization of a first principles model local to the input value.

9. The process control system of claim 1, wherein the linearized first principles model comprises a global linearization of a first principles model.

10. A method for controlling a plant or process, comprising:

receiving an input value from the plant or process;

determining an integrity of a non-linear model comprising an empirical representation of the plant or process;

using the non-linear model to provide a first output value when the integrity is above a first threshold;

using a linearized first principles model comprising an analytic representation of the plant or process to provide a second output value when the integrity is below the first threshold; and

controlling the plant or process using the first output value and/or the second output value.

11. The method of claim 10, comprising:

using the non-linear model when the integrity is above the first threshold and a second threshold which is lower than the first threshold;

using a first principles model when the integrity is above the second threshold; and

using the linearized first principles model when the integrity is below the second threshold.

12. The method of claim 10, wherein the integrity of the non-linear model corresponds to a local input space of the input value.

13. The method of claim 10, wherein the linearized first principles model comprises a local linearization of a first principles model local to the input value.

14. The method of claim 10, wherein the linearized first principles model comprises a global linearization of a first principles model.

15. The method of claim 14, wherein the global linearization is based on the range of previous input values.

16. A non-transitory memory medium comprising program instructions for controlling a plant or process, wherein the program instructions are executable by a processor to:

receive an input value from the plant or process;

determine an integrity of a non-linear model comprising an empirical representation of the plant or process;

use the non-linear model to provide a first output value when the integrity is above a first threshold;

use a linearized first principles model comprising an analytic representation of the plant or process to provide a second output value when the integrity is below the first threshold; and

control the plant or process using the first output value and/or the second output value.

17. The memory medium of claim 16, wherein the program instructions are executable to:

use the non-linear model when the integrity is above the first threshold and a second threshold which is lower than the first threshold;

use a first principles model when the integrity is above the second threshold; and

use the linearized first principles model when the integrity is below the second threshold.

18. The memory medium of claim 16, wherein the integrity of the non-linear model corresponds to a local input space of the input value.

19. The memory medium of claim 16, wherein the linearized first principles model comprises a local linearization of a first principles model local to the input value.

20. The memory medium of claim 16, wherein the linearized first principles model comprises a global linearization of a first principles model.