Apparatus and method for calculating proxy limits to support cascaded model predictive control (MPC)

Patent metadata

Field	Value
Publication number	US-10379503-B2
Application number	US-201414523508-A
Country	US
Kind code	B2
Filing date	Oct 24, 2014
Priority date	Jul 21, 2014
Publication date	Aug 13, 2019
Grant date	Aug 13, 2019

Abstract

A method includes receiving, at a master model predictive control (MPC) controller from a slave MPC controller, information indicating to what extent the slave MPC controller is able to change multiple manipulated variables in each of multiple directions within a variable space without violating process variable constraints of the slave MPC controller. The method also includes estimating a feasibility region associated with the slave MPC controller using the information, where the feasibility region identifies a portion of the variable space in which combinations of manipulated variable values satisfy the process variable constraints. In addition, the method includes performing plantwide optimization at the master MPC controller using the feasibility region, where a solution generated during the plantwide optimization includes one of the combinations of manipulated variable values within the feasibility region.

First claim

What is claimed is:

1. A method comprising:
sending multiple inquiry optimization calls from a master model predictive control (MPC) controller to a slave MPC controller, each inquiry optimization call associated with a different direction among multiple directions within a variable space;
receiving in response to each of the enquiry optimization calls, at the master MPC controller from the slave MPC controller, information indicating to what extent the slave MPC controller is able to change a manipulated variable of multiple manipulated variables in the direction associated with the respective enquiry optimization call within the variable space without violating process variable constraints of the slave MPC controller, the variable space including a first feasibility region defined by the process variable constraints;
estimating a second feasibility region associated with the slave MPC controller using the information, the second feasibility region identifying a portion of the first feasibility region in which combinations of manipulated variable values of the multiple manipulated variables satisfy the process variable constraints; and
performing plantwide optimization at the master MPC controller using the second feasibility region, wherein a solution generated during the plantwide optimization includes one of the combinations of manipulated variable values within the second feasibility region;
wherein receiving the information comprises receiving proxy limit values from the slave MPC controller in response to the inquiry optimization calls; and
wherein each proxy limit value identifies a maximum distance in one of the directions within the variable space that the slave MPC controller is able to change the manipulated variables without violating the process variable constraints.

2. The method of claim 1 , wherein the multiple directions are defined with reference to a current operating point associated with the slave MPC controller, the current operating point defining a specified point in the variable space.

3. The method of claim 2 , wherein the multiple directions are distributed at a specified interval around the current operating point associated with the slave MPC controller.

4. The method of claim 1 , further comprising: identifying at least one of the multiple directions.

5. The method of claim 4 , wherein at least one of the multiple directions comprises a direction perpendicular to a linear variable limit associated with the slave MPC controller.

6. The method of claim 1 , further comprising: repeating the receiving and estimating steps for multiple slave MPC controllers;
wherein the solution generated during the plantwide optimization honors all process variable constraints of all slave MPC controllers.

7. The method of claim 1 , wherein the multiple directions comprise at least three directions.

8. The method of claim 1 , wherein the multiple directions comprise eight directions at a 45° interval.

9. An apparatus comprising:
a master model predictive control (MPC) controller comprising:
at least one network interface configured to:
send multiple inquiry optimization calls to a slave MPC controller, each inquiry optimization call associated with a different direction among multiple directions within a variable space; and
receive in response to each of the enquiry optimization calls, from the slave MPC controller, information indicating to what extent the slave MPC controller is able to change a manipulated variable of multiple manipulated variables in the direction associated with the respective enquiry optimization call within the variable space without violating process variable constraints of the slave MPC controller, the variable space including a first feasibility region defined by the process variable constraints; and
at least one processing device configured to: estimate a second feasibility region associated with the slave MPC controller using the information, the second feasibility region identifying a portion of the first feasibility region in which combinations of manipulated variable values of the multiple manipulated variables satisfy the process variable constraints; and
perform plantwide optimization using the second feasibility region, wherein a solution generated during the plantwide optimization includes one of the combinations of manipulated variable values within the second feasibility region;
wherein the at least one processing device is configured to receive proxy limit values from the slave MPC controller in response to the inquiry optimization calls; and
wherein each proxy limit value identifies a maximum distance in one of the directions within the variable space that the slave MPC controller is able to change the manipulated variables without violating the process variable constraints.

10. The apparatus of claim 9 , wherein the multiple directions are defined with reference to a current operating point associated with the slave MPC controller, the current operating point defining a specified point in the variable space.

11. The apparatus of claim 10 , wherein the multiple directions are distributed at a specified interval around the current operating point associated with the slave MPC controller.

12. The apparatus of claim 9 , wherein the at least one processing device is further configured to identify at least one of the multiple directions.

13. The apparatus of claim 12 , wherein at least one of the multiple directions comprises a direction perpendicular to a linear variable limit associated with the slave MPC controller.

14. The apparatus of claim 9 , wherein: the at least one processing device is further configured to repeat the receiving and estimating operations for multiple slave MPC controllers; and
the solution generated during the plantwide optimization honors all process variable constraints of all slave MPC controllers.

15. The apparatus of claim 9 , wherein the multiple directions comprise at least three directions.

16. A non-transitory computer readable medium containing a computer program, the computer program comprising computer readable program code that when executed causes at least one processing device to:
send multiple inquiry optimization calls from a master model predictive control (MPC) controller to a slave MPC controller, each inquiry optimization call associated with a different direction among multiple directions within a variable space;
receive, at the master MPC controller from the slave MPC controller in response to each of the inquiry optimization calls, information indicating to what extent the slave MPC controller is able to change a manipulated variable of multiple manipulated variables in the direction associated with the respective enquiry optimization call within the variable space without violating process variable constraints of the slave MPC controller, the variable space including a first feasibility region defined by the process variable constraints;
estimate a second feasibility region associated with the slave MPC controller using the information, the second feasibility region identifying a portion of the first feasibility region in which combinations of manipulated variable values of the multiple manipulated variables satisfy the process variable constraints; and
perform plantwide optimization at the master MPC controller using the second feasibility region, wherein a solution generated during the plantwide optimization includes one of the combinations of manipulated variable values within the second feasibility region;
wherein the information comprises proxy limit values from the slave MPC controll

Assignees

• Honeywell Int Inc

Inventors

• Lu Joseph Z

Classifications

• H04L41/0823

  characterised by the purposes of a change of settings, e.g. optimising configuration for enhancing reliability (for optimising operational conditions of wireless networks H04W24/02) · CPC title

• H04L67/12 Primary

  specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks · CPC title

• H04L41/145

  involving simulating, designing, planning or modelling of a network · CPC title

• G05B13/048 Primary

  using a predictor · CPC title

• H04L41/042

  comprising distributed management centres cooperatively managing the network · CPC title