On-line adaptive model predictive control in a process control system

• US 20070078529A1
• Filed: 09/30/2005
• Published: 04/05/2007
• Est. Priority Date: 09/30/2005
• Status: Active Grant

• Current Assignee: Fisher-Rosemount Systems Incorporated (Emerson Electric Company)
• Original Assignee: Fisher-Rosemount Systems Incorporated (Emerson Electric Company)
• Inventors: Thiele, Dirk, Wojsznis, Wilhelm
• Granted Patent: US 7,451,004 B2
• Time in Patent Office: Days
• US Class Current: 700/29
• CPC Class Codes: G05B 13/048 using a predictor

Abstract

A method of creating and using an adaptive DMC type or other MPC controller includes using a model switching technique to periodically determine a process model, such as a parameterized process model, for a process loop on-line during operation of the process. The method then uses the process model to generate an MPC control model and creates and downloads an MPC controller algorithm to an MPC controller based on the new control model while the MPC controller is operating on-line. This technique, which is generally applicable to single-loop MPC controllers and is particularly useful in MPC controllers with a control horizon of one or two, enables an MPC controller to be adapted during the normal operation of the process, so as to change the process model on which the MPC controller is based to thereby account for process changes. The adaptive MPC controller is not computationally expensive and can therefore be easily implemented within a distributed controller of a process control system, while providing the same or in some cases better control than a PID controller, especially in dead time dominant process loops, and in process loops that are subject to process model mismatch within the process time to steady state.

Claims

1. A process controller for controlling a process, the process controller comprising:

a dynamic matrix control controller having a controller algorithm that uses a gain vector to produce a control signal based on an input signal, the control signal being developed for controlling a process variable;

a process model estimation unit coupled to the process to collect process data during the on-line operation of the process and that determines a process model representing the operation of the process from the collected process data; and

a controller adaptation unit that uses the process model to calculate a new gain vector for use in the dynamic matrix controller algorithm and that adapts the controller algorithm of the dynamic matrix controller to use the new gain vector, wherein the controller adaptation unit adapts the controller to use the new gain vector while the controller is operating online to control the process.

2. The process controller of claim 1, wherein the dynamic matrix control controller is a model predictive control (MPC) controller.

3. The process controller of claim 2, wherein the MPC controller is a single-loop controller.

4. The process controller of claim 3, wherein the MPC controller includes one or more feedback paths and one or more feedforward paths.

5. The process controller of claim 4, wherein the control algorithm uses a control horizon at least ten times shorter than a prediction horizon.

6. The process controller of claim 4, wherein the control algorithm uses a control horizon equal to two scans.

7. The process controller of claim 4, wherein the control algorithm uses a control horizon equal to one scan.

8. The process controller of claim 2, wherein control algorithm includes a penalty on move variable that is altered during operation of the MPC controller.

9. The process controller of claim 2, wherein the MPC controller includes a set point target vector filter having a set point target vector filter parameter, and wherein the set point target vector filter parameter is altered during operation of the MPC controller.

10. The process controller of claim 2, wherein the process model is a first order plus dead time process model.

11. The process controller of claim 2, wherein the process model is a parametric process model.

12. The process controller of claim 2, wherein the controller adaptation unit determines a prediction horizon for the control algorithm based on the process model.

13. The process controller of claim 2, wherein the controller adaptation unit determines an execution time for the MPC controller based on the process model.

14. The process controller of claim 2, wherein the controller adaptation unit determines a time to steady state from the process model and determines a combination of a prediction horizon for the control algorithm and an execution time for the MPC controller based on the time to steady state.

15. The process controller of claim 2, wherein the controller adaptation unit determines a value for a penalty on move variable used in the controller algorithm based on the process model.

16. The process controller of claim 15, wherein the process model defines a process dead time and the controller adaptation unit determines the value of the penalty on move variable based on the process dead time.