Process control and optimization technique using immunological concepts

• US 20080125881A1
• Filed: 08/02/2006
• Published: 05/29/2008
• Est. Priority Date: 08/02/2006
• Status: Active Grant

• Current Assignee: Emerson Process Management Power & Water Solutions Incorporated (Emerson Electric Company)
• Original Assignee: Emerson Process Management Power & Water Solutions Incorporated (Emerson Electric Company)
• Inventors: Williams, Jeffery J., Wojdan, Konrad, Swirski, Konrad, Grott, Jeffrey J., Chomiak, Tomasz
• Granted Patent: US 7,856,280 B2
• Time in Patent Office: Days
• US Class Current: 700/31
• CPC Class Codes: G05B 13/021 in which a variable is automatically adjusted to optimise the performance
• CPC Class Codes: G05B 13/024 in which a parameter or coefficient is automatically adjusted to optimise the performance
• CPC Class Codes: G05B 13/041 in which a variable is automatically adjusted to optimise the performance
• CPC Class Codes: G06N 3/126 Evolutionary algorithms, e.g. genetic algorithms or genetic programming
• CPC Class Codes: Y02E 40/70 Smart grids as climate change mitigation technology in the energy generation sector
• CPC Class Codes: Y04S 10/50 Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

An integrated optimization and control technique performs process control and optimization using stochastic optimization similar to the manner in which biological immune systems work, and thus without the use of historical process models that must be created prior to placing the control and optimization routine in operation within a plant. In particular, an integrated optimization and control technique collects various indications of process control states during the on-line operation of the process, and stores these process control states within a memory. During steady-state operation of the process, the integrated optimization and control technique attempts to optimize the process operation by developing a series of sets of process control inputs to be provided to the process, wherein the series of process control inputs may be developed from the stored process control states using an objective function that defines a particular optimality criteria to be used in optimizing the operation of the process. Moreover, the integrated optimization and control technique may respond to a significant change in the current process state by determining a new set of process control inputs to be provide to the process based on one or more of the stored process control states. In this case, the optimization and control technique compares the disturbance inputs of the current process control operating condition, after one or more of these disturbance inputs experiences a significant change, to the disturbance inputs of at least some of the stored process control states to determine the one or more of the stored process control states that is/are closest to the new process operating condition. The integrated optimization and control technique then develops the new set of control inputs to be delivered to the process based on the control inputs associated with the one or more stored process control states determined to be closest to the new process operating condition.

Claims

1. A process control system for controlling a process, comprising:

a controller adapted to use a set of target control signal values to produce one or more process control signals for use in controlling one or more field devices within the process; and

an optimizer communicatively coupled to the controller and adapted to develop the set of target control signal values, the optimizer including;

a memory for storing a plurality of process control states,

an optimization unit communicatively coupled to the memory and adapted to use the stored plurality of process control states to develop a series of the target control signal values for use by the controller during steady-state operation of the process to drive the process towards an optimal process operating condition,

a change detection unit responsive to one or more process inputs to detect a change in a current process state condition, and

a response unit that responds to a detected change in the current process state condition by selecting one or more of the stored plurality of process control states and using the selected one or more of the stored plurality of process control states to produce a new set of target control signal values for use by the controller in responding to the change in the current process state condition.

2. The process control system of claim 1, wherein each of the process control states is defined by a set of process inputs and a set of process outputs that result from the set of process inputs.

3. The process control system of claim 2, wherein the set of process outputs for a particular process control state includes indications of measured process variables that result from application of the set of process inputs of the particular process control state to the process.

4. The process control system of claim 3, wherein each indication of a measured process variable for the particular process control state is an indication of a steady state process variable that results from application of the set of process inputs of the particular process control state to the process.

5. The process control system of claim 2, wherein the set of process inputs for a particular process control state includes control inputs and disturbance inputs.

6. The process control system of claim 5, wherein the disturbance inputs include disturbance inputs measured or determined off-line from operation of the process.

7. The process control system of claim 1, wherein the optimizer includes a model creation unit that creates one or more models of the process from one or more of the stored process control states.

8. The process control system of claim 1, wherein the optimization unit includes an objective function and uses the objective function to determine a comparative optimality of two or more process control states to develop the set of target control signals that drive the process towards an optimal process operating condition.

9. The process control system of claim 8, wherein the objective function is user-definable.

10. The process control system of claim 1, further including a process control state manager, which operates to control the number of process control states stored in the memory.

11. The process control system of claim 10, wherein the process control state manager is adapted to remove one or more of the stored process control states based on the length of time that the one or more of the process control states has been stored in the memory.

12. The process control system of claim 10, wherein the process control state manager is adapted to remove one or more of the stored process control states based on an indication of the usage of the one or more of the process control states by the optimization unit or the response unit.

13. The process control system of claim 1, wherein the set of target control signals includes signals indicative of one or more of the process control signals to be output by the controller at some point in the future.

14. The process control system of claim 1, wherein the controller is a proportional-integral-derivative controller.

15. The process control system of claim 1, wherein the controller implements a plurality of single loop control routines and wherein the set of target control signal values includes a target control signal value for each of the single loop control routines.

16. The process control system of claim 1, wherein controller implements a multiple-input/multiple-output control routine and wherein the set of target control signal values includes a target control signal value for each of the inputs or outputs of the multiple-input/multiple-output control routine.

17. The process control system of claim 1, wherein the response unit compares the detected changed process state condition to at least some of the process control states stored in the memory and selects the one or more of the stored plurality of process control states based on the comparison.

18. The process control system of claim 1, wherein the change detection unit detects a change in a disturbance variable associated with the process to detect a change in the current process state condition.

19. A method of controlling a process, comprising:

determining values for a set of process input and output variables at multiple times during ongoing operation of the process to determine a multiplicity of process control states;

storing an indication of each of the multiplicity of process control states; and

when the process is not experiencing a significant change in one or more process disturbances, optimizing the operation of the process by periodically providing new control inputs to the process, the new control inputs configured to move the process to a more optimal process control state; and

when the process experiences a significant change in one or more process disturbances, determining a set of control inputs to be provided to the process based on one or more of the stored indications of the multiplicity of process control states and controlling the process using the set of control inputs to move the process towards a more optimal process control state in response to the significant change in the one or more process disturbances.

20. The method of claim 19, wherein determining a set of control inputs to be provided to the process based on one or more of the stored indications of the multiplicity of process control states includes comparing the process control state of the process after the significant change in the one or more process disturbances to the stored indications of the multiplicity of process control states and selecting the one or more of the stored indications of the multiplicity of process control states based on the comparison.

21. The method of claim 20, wherein each of the indications of each of the multiplicity of process control states includes a set of process inputs and a set of process outputs that result from the set of process inputs being applied to the process.

22. The method of claim 21, wherein the set of process outputs include indications of measured steady state process variables that result from application of the set of process inputs.

23. The method of claim 21, wherein the set of process inputs includes at least one control input and at least one disturbance input.

24. The method of claim 21, wherein optimizing the operation of the process includes using the stored process control states to predict a new process control state and analyzing the optimality of the new process control state based on preset optimization criteria.

25. The method of claim 24, wherein analyzing the optimality of the new process control state base on preset optimization criteria includes using an objective function that includes factors related to one or more of the process outputs and to one or more of the process inputs to define the optimization criteria.

26. The method of claim 24, wherein optimizing the operation of the process includes developing a process model from the stored process control states and predicting the new process control state using the developed process model.

27. The method of claim 21, further including limiting the number of indications of process control states stored in the memory by removing one or more indications of process control states from the memory.

28. The method of claim 27, wherein removing one or more of the indications of the process control states from the memory includes removing the one or more indications of the process control states based on the length of time that the one or more indications of the process control states have been stored in the memory or based on an indication of the amount of usage of the one or more of the process control states in response to changes in the one or more process disturbances.

29. The method of claim 20, wherein each of the indications of each of the multiplicity of process control states includes a set of process control inputs and a set of process outputs that result from the set of process control inputs being applied to the process and wherein determining the set of control inputs to be provided to the process based on one or more of the stored indications of the multiplicity of process control states includes determining the set of process control inputs from the control inputs of the one or more of the stored indications of the multiplicity of the process control states.

30. A method of optimizing the operation of a process, comprising:

determining a multiplicity of process control states during ongoing operation of the process by determining values for each of a set of process inputs and a set of process outputs that result from the set of process inputs being applied to the process to thereby define a particular process control state;

storing an indication of each of the multiplicity of process control states in a memory; and

periodically determining a new set of process control inputs to be used to control the process by predicting the response of the process to a proposed set of process control inputs based on at least one of the stored indications of the process control states and analyzing the optimality of the proposed set of process control inputs using an optimality criteria that uses both the proposed set of process control inputs and a set of predicted process control outputs that result from the proposed set of process control inputs.

31. The method of claim 30, wherein periodically determining a new set of process control inputs includes developing a process model from one or more of the stored indications of the process control states and using the developed process model to develop the predicted process control outputs from the proposed set of process control inputs.

32. The method of claim 30, wherein periodically determining a new set of process control inputs includes developing a process model from one or more of the stored indications of the process control states, selecting a desired set of process control outputs as the set of predicted process control outputs and using the developed process model and the selected desired set of process control outputs to determine the proposed set of process control inputs.

33. The method of claim 30, wherein determining the multiplicity of process control states during ongoing operation of the process includes determining values for each of a set of process control inputs and each of a set of process disturbance inputs.

34. The method of claim 33, wherein periodically determining the new set of process control inputs to be used to control the process includes determining the at least one of the stored process control states by analyzing the relative difference between the values of the disturbance inputs of a current process control state and the disturbance inputs of the process control states stored in the memory.

35. A method of controlling a process, comprising:

determining a multiplicity of process control states during ongoing operation of the process by determining values for each of a set of process inputs and a set of process outputs that result from the set of process inputs being applied to the process to thereby define a particular process control state;

storing an indication of each of the multiplicity of process control states in a memory;

monitoring the current state of the process to determine when the process experiences a significant change; and

when the process experiences a significant change, determining a set of control inputs to be provided to the process based on one or more of the stored indications of the multiplicity of process control states and controlling the process using the determined set of control inputs to move the process towards a more optimal process control state in response to the significant change.

36. The method of controlling a process of claim 35, wherein monitoring the current state of the process includes monitoring the set of process inputs provided to the process to determine a significant change in one or more of the set of process inputs provided to the process.

37. The method of controlling a process of claim 35, wherein each of the set of process inputs includes one or more disturbance inputs and wherein monitoring the current state of the process includes monitoring the disturbance inputs applied to the process to determine a significant change in one or more of the disturbance inputs applied to the process.

38. The method of controlling a process of claim 35, wherein determining the set of control inputs to be provided to the process based on one or more of the stored indications of the multiplicity of process control states includes comparing the current state of the process to the indications of the stored process control states and determining the one or more of the stored indications of the multiplicity of process control states to use based on the comparison.

39. The method of controlling a process of claim 38, wherein comparing the current state of the process to the indications of the stored process control states includes comparing the process inputs of the current state of the process to the process inputs of the stored indications of at least some of the multiplicity of process control states.

40. The method of controlling a process of claim 38, wherein each of the set of process inputs for each process control state includes one or more process disturbance inputs and wherein comparing the current state of the process to the indications of the stored process control states includes comparing the process disturbance inputs of the current state of the process to the process disturbance inputs of the stored indications of at least some of the multiplicity of process control states.