Method and system for process control

• US 7,970,482 B2
• Filed: 08/09/2007
• Issued: 06/28/2011
• Est. Priority Date: 08/09/2007
• Status: Active Grant

• Current Assignee: Honeywell International Inc.
• Original Assignee: Honeywell International Inc.
• Inventors: MacArthur, J. Ward, Srinivasan, Ranganathan
• Primary Examiner(s): DeCady; Albert
• Assistant Examiner(s): Norton; Jennifer L
• Application Number:
  US11/836,289
• Publication Number:
  US 20090043546A1
• Time in Patent Office: 1,419 Days
• Field of Search: 700 28- 31, 700/21, 703/2, 703/4, 703/6
• US Class Current: 700/31
• CPC Class Codes: G05B 13/04 involving the use of models or simulators

Abstract

A method and system for process control using a model predictive controller. The control system can have one or more control devices operably coupled to a processing system for controlling a process of the processing system; a modeling tool to provide a non-linear model based at least in part on the process and to provide a plurality of linearized models based at least in part on the non-linear model, where the plurality of linearized models are linearized at different linearization rates; and a controller operably coupled to the modeling tool. The controller can select one of the plurality of linearized models based on a comparison of the plurality of linearized models with a reference model. The controller can send one or more control signals to at least one of the one or more control devices. The one or more control signals can be determined using the selected one of the plurality of linearized models.

Claims

1. A method of controlling a non-linear process, the method comprising:

providing a non-linear model based at least in part on the non-linear process;

providing a plurality of linearized models based at least in part on the non-linear model,

the plurality of linearized models being linearized at different linearization rates;

selecting one of the plurality of linearized models based at least in part on a comparison of the plurality of linearized models with a reference model; and

controlling the non-linear process by sending one or more control signals from a controller to at least one control device, wherein the one or more control signals are determined using the selected one of the plurality of linearized models.

2. The method of claim 1, wherein the reference model is a reference linearized model that has a linearization rate greater than the linearization rates of each of the plurality of linearized models.

3. The method of claim 1, wherein the reference model is a reference linearized model that is linearized at each step of the non-linear process.

4. The method of claim 1, wherein the comparison of the plurality of linearized models with the reference model is based at least in part on at least one of an accuracy of predicting an output parameter of the non-linear process and a computational load for linearizing each of the plurality of linearized models.

5. The method of claim 1, wherein the plurality of linearized models are generated by a control system operably coupled to the at least one control device integrated into the non-linear process.

6. The method of claim 5, wherein the control system utilizes Kalman filtering to linearize the non-linear model.

7. The method of claim 1, wherein the non-linear model and the plurality of linearized models are simulated based at least in part on an input profile.

8. The method of claim 7, wherein the input profile is associated with one or more input parameters of the non-linear process.

9. The method of claim 1, wherein the at least one control device is selected from the group consisting of a valve, a switch, a motor, a heating apparatus, a cooling apparatus, and any combinations thereof.

10. A control system for controlling processing systems, the control system comprising:

one or more control devices operably coupled to a processing system for controlling a process of the processing system;

a modeling tool to provide a non-linear model based at least in part on the process and to provide a plurality of linearized models based at least in part on the non-linear model, the plurality of linearized models being linearized at different linearization rates; and

a controller operably coupled to the modeling tool, wherein the controller selects one of the plurality of linearized models based on a comparison of the plurality of linearized models with a reference model, wherein the controller sends one or more control signals to at least one of the one or more control devices, and wherein the one or more control signals are determined using the selected one of the plurality of linearized models.

11. The control system of claim 10, wherein the reference model is the non-linear model or a reference linearized model having a linearization rate greater than the linearization rates of each of the plurality of linearized models.

12. The control system of claim 10, further comprising a user interface to present the comparison of the plurality of linearized models with the reference model, wherein the user interface receives the selected one of the plurality of linearized models in response to presenting the comparison of the plurality of linearized models with the reference model.

13. The control system of claim 10, wherein the comparison of the plurality of linearized models with the reference model is based at least in part on at least one of an accuracy of predicting an output parameter of the process and a computational load for linearizing each of the plurality of linearized models.

14. The control system of claim 10, wherein the modeling tool utilizes Kalman filtering to linearize the non-linear model.

15. The control system of claim 10, wherein at least one of the one or more control devices is selected from the group consisting of a valve, a switch, a motor, a heating apparatus, a cooling apparatus, a temperature sensor, a pressure sensor, and any combinations thereof.

16. The control system of claim 10, wherein the non-linear model and the plurality of linearized models are simulated based at least in part on an input profile.

17. The control system of claim 16, wherein the input profile is associated with one or more input parameters of the process.

18. The control system of claim 10, wherein the one or more control devices comprise one or more sensors that send operational parameters to the controller, and wherein one or more operational variables are generated by the controller based at least in part on the operational parameters.

19. A non-transitory computer-readable storage medium comprising non-transitory computer-readable program instructions for controlling a non-linear process, said program comprising:

program instructions for causing a computer to receive a non-linear model of the non-linear process from a modeling tool;

program instructions for causing said computer to receive a plurality of linearized models based at least in part on the non-linear model from the modeling tool, the plurality of linearized models being linearized at different linearization rates;

program instructions for providing a comparison of the plurality of linearized models with a reference model; and

program instructions for causing said computer to send one or more control signals to at least one control device operably coupled with a processing system performing the non-linear process, wherein the one or more control signals are determined using a selected one of the plurality of linearized models, and wherein the selection is based at least in part on the comparison of the plurality of linearized models with the reference model.

20. The storage medium of claim 19, further comprising program instructions for causing said computer to present on a user interface the comparison of the plurality of linearized models with the reference model, wherein the comparison of the plurality of linearized models with the reference model is based at least in part on at least one of an accuracy of predicting an output parameter of the non-linear process and a computational load for linearizing each of the plurality of linearized models.