Integrated model predictive control and optimization within a process control system
First Claim
1. A process control system for controlling a process, comprising:
- a multiple-input/multiple-output controller that produces, during each operational cycle of the process control system, multiple control outputs configured to control the process based on multiple measured inputs from the process and based on a set of target values provided to the multiple-input/multiple output controller during each operational cycle of the process control system; and
an optimizer that develops the set of target values for use by the multiple-input/multiple-output controller during each operational cycle of the process control system,wherein the optimizer produces the set of target values based on predicted steady state values of control and auxiliary outputs of the process.
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Abstract
An integrated optimization and control technique integrates an optimization procedure, such as a linear or quadratic programming optimization procedure, with advanced control, such as model predictive control, within a process plant in which the number of control and auxiliary variables can be greater than the number of manipulated variables within the process plant. The technique first determines a step response matrix defining the correlation between changes in the manipulated variables and each of the process variables that are used during optimization. A subset of the control variables and auxiliary variables is then selected to be used as inputs to a model predictive control routine used to perform control during operation of the process and a square M by M control matrix to be used by the model predictive control routine is generated. Thereafter, during each scan of the process controller, the optimizer routine calculates the optimal operating target of each of the complete set of control and auxiliary variables and provides the determined target operating points for each of the selected subset of control and auxiliary variables to the model predictive control routine as inputs. The model predictive control routine determines changes in the manipulated variables for use in controlling the process from the target and measured values for each of the subset of the control and auxiliary variables and the M by M control matrix.
210 Citations
61 Claims
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1. A process control system for controlling a process, comprising:
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a multiple-input/multiple-output controller that produces, during each operational cycle of the process control system, multiple control outputs configured to control the process based on multiple measured inputs from the process and based on a set of target values provided to the multiple-input/multiple output controller during each operational cycle of the process control system; and an optimizer that develops the set of target values for use by the multiple-input/multiple-output controller during each operational cycle of the process control system, wherein the optimizer produces the set of target values based on predicted steady state values of control and auxiliary outputs of the process. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A process control system for controlling a process, comprising:
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an optimizer that determines an optimal operating point of the process based on a first number of predicted values of control and auxiliary variables of the process and based on a second number of current values of manipulated variables of the process; and a multiple-input/multiple-output controller that produces the second number of manipulated control signals to control the manipulated variables of the process based on a predetermined subset of the first number of predicted values of the control and auxiliary variables of the process, wherein the predetermined subset is less in number than the first number of predicted values of the control and auxiliary variables of the process. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28)
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29. A method of controlling a process having a plurality of manipulated variables and a multiplicity of control and auxiliary variables capable of being effected by changes in the manipulated variables, wherein the plurality of manipulated variables is different in number than the multiplicity of control and auxiliary variables, the method comprising;
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selecting a subset of the multiplicity of control and auxiliary variables to use in performing process control wherein the subset of the multiplicity of control and auxiliary variables is less than all of the multiplicity of control and auxiliary variables; creating a control matrix using the selected subset of the multiplicity of the control and auxiliary variables and the plurality of manipulated variables; generating a controller from the control matrix having the selected subset of the multiplicity of the control and auxiliary variables as inputs and the plurality of manipulated variables as outputs; performing process optimization by selecting a process operating point to minimize or maximize an objective function dependent on the plurality of manipulated variables and the multiplicity of control and auxiliary variables, said process operating point defined by a set of target values for the selected subset of the multiplicity control and auxiliary variables; performing a multiple-input/multiple output control technique using a controller generated from the control matrix to develop a set of manipulated variable values from the target values for the selected subset of the multiplicity of control and auxiliary variables and measured values of the selected subset of the multiplicity of control and auxiliary variables; and using the developed set of manipulated variable values to control the process. - View Dependent Claims (30, 31, 32, 33, 34, 35, 36, 37, 38)
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39. A process control element for use as a portion of a process control routine implemented on a processor to control a plurality of control and auxiliary parameters of a process using a multiplicity of manipulated parameters, the process control element comprising:
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a computer readable medium; a function block stored on the computer readable medium which, when executed on the processor implements multiple-input/multiple output control of the process during each control scan period, the function block including; an objective function that defines an optimization criteria based on each of the plurality of control and auxiliary parameters; an optimizer routine that uses the objective function to produce a set of optimal target values for the control and auxiliary parameters during each control scan period; a control matrix that relates a predetermined subset of the plurality of control and auxiliary parameters to the multiplicity of manipulated parameters, wherein the subset of the plurality of control and auxiliary parameters is less than all of the plurality of control and auxiliary parameters; and a multiple-input/multiple-output control routine that produces a control signal for each of the multiplicity of manipulated parameters during each control scan period using the control matrix and the target values for the subset of the plurality of control and auxiliary parameters, wherein the control signals are determined to drive the subset of the plurality of control and auxiliary parameters to the optimal target values for the subset of control and auxiliary parameters. - View Dependent Claims (40, 41, 42, 43, 44, 45, 46, 47, 48)
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49. A method of performing control of a process having a first number of control and auxiliary variables controlled by a second number of manipulated variables, the method comprising:
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determining a step response matrix defining a response of each of the control and auxiliary variables to changes in each of the manipulated variables; selecting a subset of the control and auxiliary variables, the subset having the same or less number of control and auxiliary variables as manipulated variables; creating a square control matrix from the responses within the response matrix for the selected subset of the control and auxiliary variables and the manipulated variables, wherein the subset of the plurality of control and auxiliary parameters is less than all of the plurality of control and auxiliary parameters; and during each scan of the process; obtaining a measure of each of the selected subset of the control and auxiliary variables; calculating an optimal operating target value for each of the selected subset of the control and auxiliary variables; performing a multiple-input/multiple-output control routine using the target values for the each of the selected subset of the control and auxiliary variables, the measures of the selected subset of the control and auxiliary variables and the control matrix to produce a set of manipulated parameter signals; and using the manipulated parameter signals to control the process. - View Dependent Claims (50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61)
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Specification