CN103365207B - A kind of control method of industrial process and equipment - Google Patents
A kind of control method of industrial process and equipment Download PDFInfo
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Abstract
The invention discloses a kind of control method and equipment of industrial process. The method comprises: for each input variable corresponding stable state input variable under stable state, stable state input variable weights are set, and at least one stable state input variable, stable state input variable desired value are set. Based target function and be optimized calculating about the stable function relational model between multiple stable state output variables and multiple stable state input variable, to obtain in the situation that meeting predefined condition, make object function obtain the value of next moment stable state input variable of extreme value, as next moment stable state input variable value. Next moment stable state input variable value is passed to base control loop to be implemented to control to the controlled variable of industrial equipment. Method provided by the present invention can realize the industrial process control of based target set point under the prerequisite of taking into account systematic economy performance.
Description
Technical Field
The invention relates to the field of industrial process control, in particular to a control method and equipment of an industrial process.
Background
Process control systems used in industrial processes typically have a plurality of input variables and a plurality of output variables that vary as the input variables change. These multiple input variables are typically controlled variables of an industrial device executing the industrial process, while the multiple output variables may be variables related to the operational outcome of the industrial process. The multi-variable control of the industrial process can be divided into two layers, wherein the upper layer is stable state optimization, and the lower layer is dynamic control. The actual industrial process is dynamic and therefore the state of the system is constantly changing. The steady state of an industrial process is the steady state that the system exhibits as time goes to infinity. The steady state optimization of the industrial process is to obtain a steady state operation point of the system, which enables the production process to have better performance when the system is in a steady state, under certain system performance and given constraint conditions. The steady state operating point may be represented by a steady state value of the input variable and a steady state value of the output variable. Further, the industrial process control can be performed by setting the controlled variable in accordance with the steady-state value of the input variable at the obtained steady-state operation point.
To obtain the steady state operating point of the system, a steady state optimization method of the industrial process can be implemented using an objective function that reflects the economic performance of the production process. These economic properties may be the economic benefit of the production process or the cost consumed, etc. The steady-state optimization for the economic performance aims to obtain a steady-state operating point when the economic performance is optimal, and then process control is carried out by using an input variable value and an output variable value of the steady-state operating point so as to achieve a better economic performance target.
Generally, the steady state optimization method of the existing industrial process is to find the next working point at the moment to optimize the economic performance of the production process based on the current working point of the system. The method aims to obtain a new operating point at the next moment of the system based on the operating point at the current moment of the system, and although the method considers the economic performance of the production process, the method is only based on the operating point at the current moment of the system and is not used for tracking any steady-state set target point.
For example, in a steady state optimization method, the minimum value of an objective function representing economic performance is calculated under the condition that certain boundary conditions are met.
The objective function may be:
wherein, CT＝[c1c2…cm]Is a set of cost coefficients.
Representing the difference between a set of steady state input variables at the next time and the steady state input variables at the current time.
The steady-state optimization method of the industrial process not only can realize process control for enabling economic performance to be better, but also can realize target point tracking taking any steady-state set point as a target. The target point tracking means that after the steady-state set point is set, a new steady-state operating point at the next moment is searched on the basis of the steady-state operating point at the current moment of the system, and the new steady-state operating point is made to be as close to the set steady-state set point as possible.
In a method for tracking a target set point, first, a target set point is set, the target set point is obtained by a nonlinear steady-state optimizer on the upper layer of a system through real-time optimization,
a quadratic objective function is then selected for calculation, the formula of which is:
the meaning of the objective function is that on the basis of the steady-state operation point of the system at the current moment, a new steady-state operation point (U) at the next moment is searched∞(k+1)，Y∞(k +1)), bringing the new steady-state operating point to the given target set point (U)T，YT) The distance is shortest, i.e. closest to the target set point, in the least squares sense.
This method can nevertheless bring about a new steady-state operating point (U) to some extent∞(k+1)，Y∞(k +1)) is close to (U)T，YT) However, this target set point tracking method is only aimed at the degree of closeness to the target setting, and does not consider economical performance, and is not practical for industrial process control.
Disclosure of Invention
The technical problem to be solved by the embodiment of the invention is to realize the control of the industrial process by setting a target set point on the premise of considering certain economic performance.
To solve the above technical problem, according to one aspect of the present invention, there is provided a control method of an industrial process, the industrial process having a plurality of input variables and a plurality of output variables that vary with changes in the plurality of input variables, the plurality of input variables being controllable variables of an industrial device that executes the industrial process, the plurality of output variables being variables related to an operation result of the industrial process, a plurality of steady-state input variables and a plurality of steady-state output variables corresponding to the plurality of input variables and the plurality of output variables in a steady state need to satisfy a preset condition,
characterized in that the method comprises:
step 1, setting a steady-state input variable weight value for each steady-state input variable, and setting a steady-state input variable target value for at least one steady-state input variable;
step 2, performing optimization calculation based on an objective function and a steady-state function relationship model between the steady-state output variables and the steady-state input variables to obtain a value of a steady-state input variable at the next moment, which makes the objective function obtain an extreme value under the condition of meeting the preset condition, as a steady-state input variable value at the next moment, wherein the objective function is a function which takes the weight value of the steady-state input variable, the target value of the steady-state input variable as parameters, and the steady-state input variable at the next moment as a variable;
and 3, transmitting the steady-state input variable value at the next moment to a basic control loop to control the controllable variable of the industrial equipment.
Preferably, the objective function is a first order function or a second order function of a product of a difference between the steady-state input variable and the steady-state input variable target value at the next time and the steady-state input variable weight.
Preferably, the steady-state input variable weight is a cost value related to a unit change of the steady-state input variable value.
Preferably, the steady state functional relationship model between the plurality of steady state input variables and the plurality of steady state output variables is such that the steady state output increment is the sum of a linear combination of the steady state input increment and the disturbance input increment and the correction error, the coefficient of the linear combination is determined according to the object steady state model,
the steady state output increment is a difference between a steady state output variable at a next time and a steady state output variable at a current time,
the steady state input increment is the difference between the steady state input variable at the next time and the steady state input variable at the current time,
the disturbance input increment is the difference between the disturbance input value at the current moment and the disturbance input value at the last moment.
Preferably, the control method further includes:
setting a steady-state input variable target range for the at least one steady-state input variable, the steady-state input variable target value being within the steady-state input variable target range;
and repeating the step 2 and the step 3 for a plurality of times, so that the steady-state input variable value of the at least one steady-state input variable obtained finally at the next moment is within the steady-state input variable target range.
Preferably, the method further comprises the following steps:
setting a steady state output variable target range for the at least one steady state output variable,
and repeating the step 2 and the step 3 for a plurality of times, so that the steady-state output variable value of the at least one steady-state output variable obtained by the steady-state functional relationship model at the next moment is within the steady-state output variable target range according to the steady-state input variable value at the next moment.
Preferably, a part of the plurality of steady state input variables is a first steady state input variable without a target set point set, a part of the steady state input variables is a second steady state input variable with a target set point set, the target set point includes a steady state input variable target value,
the objective function is:
a linear function of the product of the weight of the first steady-state input variable and the difference between the first steady-state input variable and the first steady-state input variable at the next moment, and a linear function of the product of the weight of the second steady-state input variable and the difference between the target value of the second steady-state input variable and the steady-state input variable at the next moment, or
The second steady-state input variable weight is calculated by adding the product of the difference between the first steady-state input variable and the current first steady-state input variable at the next moment and the first steady-state input variable weight to the second steady-state input variable weight.
According to the second aspect of the present invention, there is also provided a control apparatus for an industrial process having a plurality of input variables which are controllable variables of an industrial apparatus which executes the industrial process, and a plurality of output variables which are variable with changes of the plurality of input variables, the plurality of output variables being variables related to an operation result of the industrial process, a plurality of steady-state input variables and a plurality of steady-state output variables corresponding to the plurality of input variables and the plurality of output variables in a steady state being required to satisfy a preset condition,
characterized in that the control device comprises:
the setting device is used for setting a steady-state input variable weight value for each steady-state input variable and setting a steady-state input variable target value for at least one steady-state input variable;
an optimization calculation device, configured to perform optimization calculation based on an objective function and a steady-state function relationship model between the multiple steady-state output variables and the multiple steady-state input variables, so as to obtain, as a next-time steady-state input variable value, a value of a next-time steady-state input variable that causes the objective function to obtain an extremum when the preset condition is satisfied, where the objective function is a function in which the steady-state input variable weight value, the steady-state input variable target value are used as parameters, and the next-time steady-state input variable is used as a variable;
and the industrial equipment control device is used for transmitting the steady-state input variable value at the next moment to the basic control loop to control the controllable variable of the industrial equipment.
Preferably, the objective function is a first order function or a second order function of a product of a difference between the steady-state input variable and the steady-state input variable target value at the next time and the steady-state input variable weight.
Preferably, the control apparatus further includes:
target range setting means for setting a steady-state input variable target range for the at least one steady-state input variable, the steady-state input variable target value being within the steady-state input variable target range,
the optimization calculation means repeatedly executes the optimization calculation a plurality of times so that the steady-state input variable value at the next moment of the at least one steady-state input variable finally obtained is within the steady-state input variable target range.
According to the control method of the industrial process, optimization calculation is carried out based on an objective function and a steady-state function relation model between a steady-state input variable and a steady-state output variable, the objective function takes a preset steady-state input variable weight and a steady-state input variable target value as parameters, and a steady-state input variable at the next moment, which enables the objective function to obtain an extreme value, is calculated and used as the steady-state input variable at the next moment. The setting of the weight of the steady-state input variable and the obtaining of the extreme value of the objective function reflect the consideration of the economic performance of the system, and meanwhile, the target value of the steady-state input variable is set as the target set point to track, so that the tracking of the target set point is realized on the premise of considering the economic performance of the system, the obtained steady-state input variable at the next moment has higher practicability, and the controllable variable of the industrial equipment is set as the obtained steady-state input variable value at the next moment to realize the industrial process control with better performance.
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Other features of the present invention and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention.
The invention will be more clearly understood from the following detailed description, taken with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart diagram illustrating an embodiment of a control method provided by the present invention;
FIG. 2 is a schematic diagram of the present invention setting a steady state input variable target range;
FIG. 3 is a schematic diagram illustrating the setting of a steady state output variable target range according to the present invention;
FIG. 4 is a schematic diagram showing a trace of steady-state input variable values at the next time in an embodiment of the control method provided by the present invention;
fig. 5 shows a schematic structural diagram of an embodiment of the control device provided by the present invention.
Detailed Description
Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that: unless specifically stated otherwise, the relative arrangement of the steps, numerical expressions and numerical values set forth in these examples do not limit the scope of the invention.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
An industrial process has a plurality of control input variables and a plurality of output variables that vary as these plurality of input variables change. The plurality of input variables are controllable variables of an industrial plant executing the industrial process, the plurality of output variables are variables related to the operation result of the industrial process, and for a linear multivariable process, the correspondence between the plurality of input variables and the plurality of output variables can be described by using a certain functional relation model. The functional relationship model is determined by the intrinsic characteristics of the system, and the control output variable can be obtained according to the control input variable by using the functional relationship model of the system, and vice versa.
There are many types of functional relationship models between input variables and output variables of an industrial process system. After the functional relationship model of the system is obtained, the functional relationship model needs to be subjected to steady-state processing to obtain a steady-state functional relationship model between a steady-state input variable and a steady-state output variable of the system when the system reaches a steady state, and the steady-state input variable and the steady-state output variable correspond to the representation of the input variable and the output variable of the system under the steady state.
The steady state functional relationship model for the plurality of steady state input variables and the plurality of steady state output variables of the industrial process can be of a variety of types. For example, a steady-state functional relationship model may be expressed such that the steady-state output increment is a sum of a linear combination of a steady-state input increment and a disturbance input increment and a correction error, the coefficient of the linear combination being determined according to the object steady-state model, wherein the steady-state output increment is a difference between a steady-state output variable at a next time and a steady-state output variable at a current time, the steady-state input increment is a difference between a steady-state input variable at the next time and a steady-state input variable at the current time, and the disturbance input increment is a difference between a disturbance input value at the current time and a disturbance input value at the previous time.
For an actual industrial production process, certain boundary constraint conditions exist for a steady-state input variable and a steady-state output variable respectively. Therefore, the plurality of steady-state input variables and the plurality of steady-state output variables need to satisfy certain preset conditions, so that the steady-state input variables and the steady-state output variables at the next time are located between the upper boundary value and the lower boundary value of the respective boundary constraint conditions.
In addition, the steady-state input variables and the steady-state output variables are further limited by steady-state increment constraints during the optimization and control execution, and the steady-state input increments and the steady-state output increments are respectively positioned between the upper boundary value and the lower boundary value of the respective increment constraints. The steady state input increment is a difference between a steady state input variable at a next time and a steady state input variable at a present time, the steady state output increment is a difference between a steady state output variable at the next time and a steady state output variable at the present time,
referring to fig. 1, which is a schematic flow chart showing an embodiment of a method for controlling an industrial process according to the present invention, the steps of the embodiment of the method for controlling an industrial process according to the present invention will be described in detail.
The industrial process described in the embodiments has a plurality of input variables and a plurality of output variables that vary as the plurality of input variables change. The plurality of input variables are controllable variables of an industrial device that executes an industrial process, and the plurality of output variables are variables related to an operation result of the industrial process. The plurality of steady state input variables and the plurality of steady state output variables are representations of the plurality of input variables and the plurality of output variables of the system at steady state of the system, the plurality of steady state input variables and the plurality of steady state output variables corresponding to the plurality of input variables and the plurality of output variables.
The plurality of steady state input variables and the plurality of steady state output variables satisfy predetermined conditions, namely, the boundary constraint condition and the increment constraint condition.
In step 101, a steady-state input variable weight is set for each steady-state input variable, and a steady-state input variable target value is set for at least one steady-state input variable.
Due to steady state input delta U∞(k) And steady state output increment delta Y∞(k) Since there is a linear correlation represented by the steady-state functional relationship model, both can be unified by the steady-state input increment Δ U∞(k) And (4) showing.
Using steady state input delta U∞(k) Indicating steady state output delta deltay∞(k) Thereafter, for a particular industrial process, the steady state input delta U is incremented∞(k) And setting a steady-state input variable weight. The weight value can be set by normalizing the benefit or cost generated by the unit increment of the steady-state input variable and using the normalized parameter to express the benefit or cost of each steady-state input variable. That is, the steady-state input variable weight is a cost value related to a unit change of the steady-state input variable value. The + sign can be used to distinguish between cost and benefit, + represents cost, -represents benefit. For example, the steady-state input variable weights for each steady-state input variableThe collection can be represented as CT＝[c1c2…cm]And m is the number of steady state input variables.
The plurality of steady state input variables of the industrial process may have different characteristics, wherein a part of the steady state input variables need to be set with a target set point, a steady state operating point at the next moment is calculated by a steady state optimization target tracking method, and the steady state operating point at the next moment is made to be as close to the set target set point as possible under the condition of achieving the optimal economic performance. However, the target set point is not set for another part of the steady-state input variables, and the steady-state operating point at the next moment is made to be as close as possible to the steady-state input variable value at the current moment under the condition of achieving the optimal economic performance only by the calculation of the steady-state optimization target tracking method.
For the steady-state input variable needing to be set to the target set point, in addition to the weight value of the steady-state input variable, a target value U of the steady-state input variable needs to be setT。
The target setpoint is a desired steady state operating point of the system, the target setpoint including a steady state input variable target value UTAnd steady state output variable target value YT. Target value U of variable due to steady state inputTAnd steady state output variable target value YTThere is a linear correlation between them, and therefore, by setting the steady-state input variable target value UTAnd a linear correlation relationship therebetween, a steady-state output variable target value Y can be obtainedT。
The target set point may be the result of an optimizer optimization calculation at the upper layer of the system or may be an ideal value given empirically by the process personnel.
In step 102, optimization calculation is performed based on the objective function and a steady-state function relationship model between the plurality of steady-state output variables and the plurality of steady-state input variables, so as to obtain a value of a steady-state input variable at a next time, which makes the objective function to take an extreme value when a preset condition is satisfied, as a next-time input steady-state variable value. The objective function is a function which takes the steady-state input variable weight and the steady-state input variable target value as parameters and takes the steady-state input variable as a variable at the next moment.
In order to reflect the economic performance of the industrial process system, the objective function can select a function which takes the steady-state input variable weight and the steady-state input variable target value as parameters and takes the steady-state input variable as a variable at the next moment. Because the weight of the steady-state input variable is related to a certain economic index of the steady-state input variable, under the condition of meeting the preset condition, the target function obtains the value of the steady-state input variable at the next moment of the extreme value, and the value is used as the value of the steady-state input variable at the next moment, so that the extreme value of the economic index can be realized, and the target value of the steady-state input variable is set as the target set point for tracking, so that the tracking of the target set point can be realized on the premise of considering the economic performance of the system.
The objective function may be a first order function or a second order function of the product of the steady state input variable weight and the difference between the steady state input variable and the steady state input variable target value at the next time.
In step 103, the steady state input variable value at the next time is transmitted to the basic control loop to control the controllable variable of the industrial equipment. The controlled variable of the industrial equipment is set to the steady-state input variable value at the next time obtained in step 102, so that the industrial process control closer to the set steady-state input variable target value and in consideration of the economy can be realized.
In the process of performing optimization calculation to obtain the value of the steady-state input variable at the next moment when the objective function obtains the extreme value, the plurality of steady-state output variables can be obtained through a steady-state functional relationship model between the plurality of steady-state input variables and the plurality of steady-state output variables. Thereby, it is also possible to obtain the target set point (U) which is closest to the setting under the condition of the preset condition based on the objective functionT，YT) Next stable operating state (U)∞(k+1)，Y∞(k+1))。
Next stable operating state (U) obtained based on the objective function∞(k+1)，Y∞(k +1)) in addition to satisfying the above-mentioned predetermined condition, that is, in another embodiment, the pair (U) may be further added∞(k+1)，Y∞(k +1)) soft constraint condition setting a steady-state input variable target range (U) for the steady-state input variableTmin，UTmax) Input variable target value UTWithin the steady state input variable target range and setting a steady state output variable target range (Y) for the steady state output variableTmin，YTmax) The following set of polynomials is satisfied:
UTmin≤U∞(k+1)≤UTmax
YTmin≤Y∞(k+1)≤YTmax
wherein,andrespectively, the lower bound and the upper bound of the set steady state input variable target range. In general, the soft constraint condition is a more strict condition than the previously set condition, and therefore, U is a condition that is more strict than the previously set conditionTmin、UTmaxIs different from Umin、UmaxGenerally speaking UTmin≥Umin，UTmax≤Umax。
Referring to FIG. 2, (U)Tmin，UTmax) The range of value coverage is less than (U)min，Umax) U in the figureT_rangeRepresents UTA range of values can be taken.
Referring to FIG. 3, similarly, (Y)Tmin，YTmax) The range covered by the value is less than (Y)min，Ymax) Y in FIG. 3T_rangeRepresents YTA range of values can be taken.
In the process of using the objective function to perform optimization calculation to track the target set point, the result of one optimization calculation is completed, namely (U)∞(k+1)，Y∞(k +1)) may not satisfy the soft constraints, i.e., the steady-state input and steady-state output variable target ranges, so that the optimization calculation may be performed multiple times using an iterative method such that the resulting steady-state input variable U at the next time is obtained∞(k +1) in the steady state input variable target range (U)Tmin，UTmax) And a steady state Y of the output variable at the next moment of the at least one steady state output variable obtained by the steady state functional relationship model∞(k +1) in the output variable target range (Y)Tmin，YTmax) Within.
Referring to FIG. 4, the steady state value of the steady state input variable at the next moment is shown as an example, and the steady state input variable value U at the next moment after a plurality of iterative computations∞(k +1) reaching the steady state input variable target range (U)Tmin，UTmax) Inside the track map. In FIG. 4, Δ U∞' (k) denotes a steady-state input variable U at the next time∞(k +1) and steady state input variable target value UTDifference of Δ U∞(k) Represents the steady state input variable U at the next moment∞(k +1) and the steady state input variable U at the current time∞(k) The difference between them.
Further, the steady state input variable U at the next moment is obtained∞After (k +1), U may be substituted∞And (k +1) transmitting to a basic control loop to control the controllable variable of the industrial equipment.
In will U∞After (k +1) is transmitted to the basic control loop to implement control, the system is controlled by the basic control loop, the state is changed, so that step 102 in the above embodiment can be executed in a next time and in a loop manner, the optimization calculation is performed based on the objective function and the steady-state function relation model according to the steady-state input variable target value to obtain a new steady-state input variable value at the next time and a new steady-state output variable value at the next time, and step 103 is executed again to implement control, namely, the control is executed repeatedly for multiple timesAnd 102 and 103, enabling the steady-state input variable value of the at least one steady-state input variable obtained finally at the next moment to be within the steady-state input variable target range, and enabling the steady-state output variable value of the at least one steady-state output variable obtained through the steady-state functional relation model at the next moment to be within the steady-state output variable target range according to the steady-state input variable value at the next moment.
In performing the loop optimization calculation, the input variable target value may be set and then typically not changed.
In addition, as an alternative embodiment, the steady-state input variable target range (U) may be set only for the steady-state input variableTmin，UTmax) The steady state input variable target value is within the input variable target range. Repeating the steps 102 and 103 for a plurality of times to obtain the steady-state input variable value U at the next moment of the steady-state input variable∞(k +1) in the steady-state input variable target range (U)Tmin，UTmax) Within. In such an embodiment, the steady state output variable Y at the next time is∞(k +1) only needs to satisfy the constraint conditions set in advance by the system.
As described above, according to the characteristic that a plurality of input variables may have different characteristics, in the calculation process of one industrial process control, for a plurality of steady-state input variables corresponding to the plurality of input variables, a target set point may need to be set for a part of the steady-state input variables, and under the condition that the economic performance is optimal, the optimization calculation is performed by a method of setting the target set point so that the steady-state operating point at the next moment is as close as possible to the set target set point. And (4) not setting a target set point for the other part of steady-state input variables, and calculating to enable the steady-state operating point at the next moment to be as close as possible to the steady-state operating point at the current moment under the condition of achieving optimal economic performance.
Specifically, a part of the plurality of steady-state input variables is a first steady-state input variable without a target set point, a part of the steady-state input variables is a second steady-state input variable with the target set point, the target set point includes a target value of the steady-state input variable, and the target function may be:
a linear function of the product of the weight of the first steady-state input variable and the difference between the first steady-state input variable and the first steady-state input variable at the next moment, and a linear function of the product of the weight of the second steady-state input variable and the difference between the target value of the second steady-state input variable and the steady-state input variable at the next moment, or
The second steady-state input variable weight is calculated by adding the product of the difference between the first steady-state input variable and the current first steady-state input variable at the next moment and the first steady-state input variable weight to the second steady-state input variable weight.
Referring to fig. 5, the present invention further provides a control device of an industrial process corresponding to the control method of the present invention, and the figure is a schematic structural diagram of an embodiment of the control device.
The industrial process has a plurality of input variables which are controllable variables of an industrial device which executes the industrial process, and a plurality of output variables which are variables related to an operation result of the industrial process, and a plurality of steady-state input variables and a plurality of steady-state output variables corresponding to the plurality of input variables and the plurality of output variables in a steady state need to satisfy a predetermined condition, and the control device 500 includes a setting means 501, an optimization calculation means 502, and an industrial device control means 503.
The setting device 501 is configured to set a steady-state input variable weight for each steady-state input variable, and set a steady-state input variable target value for at least one steady-state input variable.
The optimization calculation device 502 is configured to perform optimization calculation based on an objective function and a steady-state function relationship model between a plurality of steady-state output variables and a plurality of steady-state input variables, so as to obtain a value of a steady-state input variable at a next time, which makes the objective function obtain an extreme value when a preset condition is satisfied, as a steady-state input variable value at the next time, where the objective function is a function in which a steady-state input variable weight value and a steady-state input variable target value are used as parameters, and the steady-state input variable at the next time is used as a variable.
The industrial equipment control device 503 is used for transmitting the steady-state input variable value at the next moment to the basic control loop to control the controllable variable of the industrial equipment.
In another embodiment, the objective function is a first order function or a second order function of the product of the steady state input variable weight and the difference between the steady state input variable and the steady state input variable target value at the next time.
In another embodiment, the control apparatus further comprises target range setting means.
The target range setting means is for setting a steady-state input variable target range for at least one steady-state input variable, the steady-state input variable target value being within the steady-state input variable target range,
the optimization calculation means repeatedly performs the optimization calculation a plurality of times so that the steady-state input variable value at the next moment of the finally obtained at least one steady-state input variable is within the steady-state input variable target range.
So far, a control method and apparatus of an industrial process according to the present invention have been described in detail. Some details well known in the art have not been described in order to avoid obscuring the concepts of the present invention. It will be fully apparent to those skilled in the art from the foregoing description how to practice the presently disclosed embodiments.
In addition, the connection relationship between the constituent devices of the device according to the embodiment of the present invention only represents one example of the information flow relationship according to the present invention, and is not limited to the physical connection relationship, and is not necessarily required or limited to implement the embodiment of the present invention.
The method and apparatus of the present invention may be implemented in a number of ways. For example, the methods and systems of the present invention may be implemented in software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order for the steps of the method is for illustrative purposes only, and the steps of the method of the present invention are not limited to the order specifically described above unless specifically indicated otherwise. Furthermore, in some embodiments, the present invention may also be embodied as a program recorded in a recording medium, the program including machine-readable instructions for implementing a method according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.
Although some specific embodiments of the present invention have been described in detail by way of illustration, it should be understood by those skilled in the art that the above illustration is only for the purpose of illustration and is not intended to limit the scope of the invention. It will be appreciated by those skilled in the art that modifications may be made to the above embodiments without departing from the scope and spirit of the invention. The scope of the invention is defined by the appended claims.
Claims (10)
1. A method for controlling an industrial process, comprising,
the industrial process has a plurality of input variables which are controllable variables of an industrial device executing the industrial process and a plurality of output variables which are variables related to an operation result of the industrial process, and a plurality of steady-state input variables and a plurality of steady-state output variables corresponding to the plurality of input variables and the plurality of output variables in a steady state need to satisfy a preset condition,
characterized in that the method comprises:
step 1, setting a steady-state input variable weight value for each steady-state input variable, and setting a steady-state input variable target value for at least one steady-state input variable;
step 2, performing optimization calculation based on an objective function and a steady-state function relationship model between the steady-state output variables and the steady-state input variables to obtain a value of a steady-state input variable at the next moment, which makes the objective function obtain an extreme value under the condition of meeting the preset condition, as a steady-state input variable value at the next moment, wherein the objective function is a function which takes the weight value of the steady-state input variable, the target value of the steady-state input variable as parameters, and the steady-state input variable at the next moment as a variable;
and 3, transmitting the steady-state input variable value at the next moment to a basic control loop to control the controllable variable of the industrial equipment.
2. The control method according to claim 1, wherein the objective function is a first order function or a second order function of a product of a difference between the steady-state input variable and the steady-state input variable target value at the next time and the steady-state input variable weight.
3. The control method according to claim 1, wherein the steady-state input variable weight is a cost value related to a unit change in the steady-state input variable value.
4. The control method of claim 1, wherein the steady state functional relationship model between the plurality of steady state input variables and the plurality of steady state output variables is that a steady state output increment is a sum of a correction error and a linear combination of a steady state input increment and a disturbance input increment, coefficients of the linear combination being determined according to a subject steady state model,
the steady state output increment is a difference between a steady state output variable at a next time and a steady state output variable at a current time,
the steady state input increment is the difference between the steady state input variable at the next time and the steady state input variable at the current time,
the disturbance input increment is the difference between the disturbance input value at the current moment and the disturbance input value at the last moment.
5. The control method according to claim 4, characterized by further comprising:
setting a steady-state input variable target range for the at least one steady-state input variable, the steady-state input variable target value being within the steady-state input variable target range;
and repeating the step 2 and the step 3 for a plurality of times, so that the steady-state input variable value of the at least one steady-state input variable obtained finally at the next moment is within the steady-state input variable target range.
6. The control method according to claim 5, characterized by further comprising:
setting a steady state output variable target range for at least one steady state output variable,
and repeating the step 2 and the step 3 for a plurality of times, so that the steady-state output variable value of the at least one steady-state output variable obtained by the steady-state functional relationship model at the next moment is within the steady-state output variable target range according to the steady-state input variable value at the next moment.
7. The control method according to claim 2,
wherein a portion of the plurality of steady state input variables are first steady state input variables for which a target set point is not set, and a portion of the steady state input variables are second steady state input variables for which the target set point is set, the target set point comprising a steady state input variable target value,
the objective function is:
a linear function of the product of the weight of the first steady-state input variable and the difference between the first steady-state input variable and the first steady-state input variable at the next moment, and a linear function of the product of the weight of the second steady-state input variable and the difference between the target value of the second steady-state input variable and the steady-state input variable at the next moment, or
The second steady-state input variable weight is calculated by adding the product of the difference between the first steady-state input variable and the current first steady-state input variable at the next moment and the first steady-state input variable weight to the second steady-state input variable weight.
8. A control apparatus for an industrial process having a plurality of input variables which are controllable variables of an industrial apparatus which executes the industrial process and a plurality of output variables which are variables relating to an operation result of the industrial process, which are variables that vary with a change in the plurality of input variables, a plurality of steady-state input variables and a plurality of steady-state output variables corresponding to the plurality of input variables and the plurality of output variables in a steady state are required to satisfy a preset condition,
characterized in that the control device comprises:
the setting device is used for setting a steady-state input variable weight value for each steady-state input variable and setting a steady-state input variable target value for at least one steady-state input variable;
an optimization calculation device, configured to perform optimization calculation based on an objective function and a steady-state function relationship model between the multiple steady-state output variables and the multiple steady-state input variables, so as to obtain, as a next-time steady-state input variable value, a value of a next-time steady-state input variable that causes the objective function to obtain an extremum when the preset condition is satisfied, where the objective function is a function in which the steady-state input variable weight value, the steady-state input variable target value are used as parameters, and the next-time steady-state input variable is used as a variable;
and the industrial equipment control device is used for transmitting the steady-state input variable value at the next moment to the basic control loop to control the controllable variable of the industrial equipment.
9. The control apparatus according to claim 8, wherein the objective function is a first-order function or a second-order function of a product of a difference between the steady-state input variable and the steady-state input variable target value at the next time and the steady-state input variable weight.
10. The control apparatus according to claim 8, characterized by further comprising:
target range setting means for setting a steady-state input variable target range for the at least one steady-state input variable, the steady-state input variable target value being within the steady-state input variable target range,
the optimization calculation means repeatedly executes the optimization calculation a plurality of times so that the steady-state input variable value at the next moment of the at least one steady-state input variable finally obtained is within the steady-state input variable target range.
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