Method for measuring the control performance provided by an industrial process control system

• US 6,597,958 B1
• Filed: 03/22/2001
• Issued: 07/22/2003
• Est. Priority Date: 03/22/2001
• Status: Active Grant

• Current Assignee: ABB Automation GmbH (ABB Limited)
• Original Assignee: ABB Automation GmbH (ABB Limited)
• Inventors: Starr, Kevin D.
• Primary Examiner(s): Voeltz, Emanuel Todd
• Assistant Examiner(s): Barnes, Crystal J.
• Application Number:
  US09/815,205
• Time in Patent Office: 852 Days
• Field of Search: 700/29-31, 700/37, 700/39, 700/44, 700/52, 702/82, 703/2, 318/561
• US Class Current: 700/29
• CPC Class Codes: G05B 23/0243 model based detection method, e.g. first-principles knowledge model
• CPC Class Codes: G05B 23/027 Alarm generation, e.g. communication protocol; Forms of alarm
• CPC Class Codes: G05B 23/0294 Optimizing process, e.g. process efficiency, product quality

Abstract

A method for determining the measure of control provided to a process by a control system. The determines process model parameters for a simple and complex model of the process and uses those parameters along with the value of the process variable and the final control element position to predict the off control data. The method also uses the process model parameters to determine the optimal tuning and then forecasts the optimal process performance from the predicted off control data and the determined optimal tuning.

Claims

1. A method for measuring the control provided by a control system to a process, said system having a controller for controlling the position of a final control element to control a process variable and said method comprising the steps of:

(a) determining process model parameters for a simple model and a high order model of said process;

(b) gathering the value of said process variable and said final control element position;

(c) predicting off control data using said determined simple and high order models parameters and said gathered value of said process variable and said final control element position;

(d) determining the optimal tuning using said determined simple and high order models parameters; and

(e) forecasting the optimal process performance from said predicted off control data and said determined optimal tuning.

2. The method of claim 1 further comprising the step of performing a bump test to determine said simple and high order models parameters.

3. The method of claim 1 further comprising the step of setting a predetermined criteria for alarming based on said gathered value of said process variable and said final control element position, said predicted off control data, and said determined optimal tuning.

4. The method of claim 2 further comprising the step of setting a predetermined criteria for alarming based on said gathered value of said process variable and said final control element position, said predicted off control data, and said determined optimal tuning.

5. The method of claim 1 wherein said process is a batch process and said process variable value and said final control element position are gathered for statistically valid period of time.

6. The method of claim 1 wherein said process is a continuous process and said process variable value and said final control element position are gathered continuously.

7. The method of claim 1 wherein said determining of said process model parameters and said determining of said optimal tuning are performed when said predetermined criteria for alarming indicates that corrective action should be undertaken.

8. The method of claim 4 wherein said performing of said bump test and said determining of said optimal tuning are performed when said predetermined criteria for alarming indicates that corrective action should be undertaken.

9. A method for measuring the control provided by a control system to a process, said system having a controller for controlling the position of a final control element to control a process variable and said method comprising the steps of:

(a) performing a bump test on said process to determine process model parameters for a simple model and a high order model of said process;

(b) gathering the value of said process variable and said final control element position;

(c) predicting off control data using said simple and high order models parameters determined by performing said bump test and said gathered value of said process variable and said final control element position;

(d) determining the optimal tuning using said simple and high order models parameters determined by performing said bump test; and

(e) forecasting the optimal process performance from said predicted off control data and said determined optimal tuning.

10. The method of claim 9 further comprising the step of setting a predetermined criteria for alarming based on said gathered value of said process variable and said final control element position, said predicted off control data, and said determined optimal tuning.

11. The method of claim 9 wherein said process is a batch process and said process variable value and said final control element position are gathered for statistically valid period of time.

12. The method of claim 9 wherein said process is a continuous process and said process variable value and:

said final control element position are gathered continuously.

13. The method of claim 10 wherein said performing of said bump test and said determining of said optimal tuning are performed when said predetermined criteria for alarming indicates that corrective action should be undertaken.

14. The method of claim 13 wherein said performing of said bump test and said determining of said optimal tuning are automatically performed when said predetermined criteria for alarming indicates that corrective action should be undertaken.

15. The method of claim 13 wherein said corrective action is correction of a process problem or a hardware problem and said bump test and said determining of said optimal tuning are performed automatically after said process problem or said hardware problem is corrected.

16. A method for measuring the control provided by a control system to a process, said system having a controller for controlling the position of a final control element to control a process variable and said method comprising the steps of:

(a) determining process model parameters for a simple model and a high order model of said process;

(b) predicting off control data using said determined simple and high order models parameters and the value of said process variable and said final control element position;

(c) determining the optimal tuning using said determined simple and high order models parameters; and

(d) forecasting the optimal process performance from said predicted off control data and said determined optimal tuning.

17. The method of claim 16 further comprising the step of gathering said value of said process variable and said final control element position.