CN103365207A - Industrial process control method and industrial process control equipment - Google Patents
Industrial process control method and industrial process control equipment Download PDFInfo
- Publication number
- CN103365207A CN103365207A CN2012100846374A CN201210084637A CN103365207A CN 103365207 A CN103365207 A CN 103365207A CN 2012100846374 A CN2012100846374 A CN 2012100846374A CN 201210084637 A CN201210084637 A CN 201210084637A CN 103365207 A CN103365207 A CN 103365207A
- Authority
- CN
- China
- Prior art keywords
- stable state
- input variable
- state input
- variable
- value
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Landscapes
- Feedback Control In General (AREA)
Abstract
The invention discloses an industrial process control method and industrial process control equipment. The method comprises the steps of setting a steady-state input variable weight for a steady-state input variable corresponding to each input variable in a steady state and setting a steady-state input variable target value for at least one steady-state input variable. Optimization calculation is carried out based on an objective function and a steady-state functional relationship model between multiple steady-state output variables and multiple steady-state input variables so as to obtain a value, enabling the objective function to take an extreme value under the condition of meeting a preset condition, of a next-time steady-state input variable, and the value is used as a next-time steady-state input variable value. The next-time steady-state input variable value is transmitted to a basic control loop to control controllable variables of industrial equipment. The method provided by the invention can enable industrial process control based on a target setting point to be realized on the premise of giving consideration to the economic performance of a system.
Description
Technical field
The present invention relates to the industrial process control field, relate in particular to a kind of control method and equipment of industrial process.
Background technology
The Process Control System of using in the industrial process, a plurality of output variables that usually have a plurality of input variables and change with the change of these input variables.These a plurality of input variables are normally carried out the controllable variable of the commercial unit of industrial process, and a plurality of output variable can be the relevant variable of operation result of industrial process.The multivariable Control of industrial process can be divided into two-layer, and the upper strata is steady-state optimization, and lower floor is dynamically control.Actual industrial process all is dynamic, so the state of system also is continuous conversion.The stable state of industrial process refers to the steady state (SS) that system embodies when the time is tending towards infinite.The steady-state optimization of industrial process is under certain system performance and given constraint condition, obtains to make the more excellent systematic steady state operating point of production run performance when system is steady state (SS).The steady state operation point can be represented by the steady-state value of input variable and the steady-state value of output variable.And then, can controllable variable be set according to the steady-state value of the input variable in the steady state operation point that obtains, implement industrial process control.
For obtaining the steady state operation point of system, the steady-state optimization method of industrial process can realize with reflection production run economic performance objective function.These economic performances can be the economic benefit that produces of production run or the cost that consumes etc.Be intended to obtain steady state operation point when economic performance is optimum towards the steady-state optimization of economic performance, and then use the input variable value of this steady state operation point and output variable value to carry out process control, to realize better economic performance target.
Usually, the steady-state optimization method of existing industrial process is to seek next working point constantly that makes production run economic performance optimum on the basis of system's current time operating point.The target that this method will reach is based on system's current time operating point and obtains next new operating point constantly of system, although this method has been considered the economic performance of production run, but this method is not the tracking to any stable state target setting point only based on the operating point of system's current time.
For example, in a kind of steady-state optimization method, calculate the objective function of embodiment economic performance in the minimal value that satisfies in the situation of certain boundary conditions.
Objective function can for:
Wherein, C
T=[c
1c
2C
m] be one group of cost coefficient.
The steady-state optimization method of industrial process not only can realize making economic performance reach more excellent process control, can also realize that the impact point take any stable state set point as target is followed the tracks of.Impact point is followed the tracks of and is referred to after setting the stable state set point, on the basis of system's current time steady state operation point, seeks next constantly new steady state operation point, makes new steady state operation point approach as much as possible the stable state set point that sets.
In a kind of method that target set point is followed the tracks of, at first, the target setting set point, this target set point is carried out real-time optimization by the Nonlinear Steady optimizer on system upper strata and is obtained,
Select subsequently quadratic model object function to calculate, the formula table of this objective function is shown:
The implication of this objective function is on the basis of system's current time steady state operation point, to seek next constantly new steady state operation point (U
∞(k+1), Y
∞(k+1)), make new steady state operation point and given target set point (U
T, Y
T) distance is the shortest under the least square meaning, namely near target set point.
Although this method can make new steady operation point (U to a certain extent
∞(k+1), Y
∞(k+1)) near (U
T, Y
T), but this goal-setting point-tracking method only take and goal-setting between degree of closeness as purpose, do not consider economic performance, poor practicability for industrial process control.
Summary of the invention
Embodiment of the invention technical matters to be solved is to take into account under the prerequisite of certain economic performance realize the control of industrial process by the target setting set point.
For solving the problems of the technologies described above, according to an aspect of the present invention, the embodiment of the invention provides a kind of control method of industrial process, a plurality of output variables that described industrial process has a plurality of input variables and changes with the change of described a plurality of input variables, described a plurality of input variable is to carry out the controllable variable of the commercial unit of described industrial process, described a plurality of output variable is the variable relevant with the operation result of described industrial process, described a plurality of input variable and described a plurality of output variable corresponding a plurality of stable state input variables and a plurality of stable state output variable under stable state need to satisfy predefined condition
It is characterized in that described method comprises:
Step 2. based target function and be optimized calculating about the stable function relational model between described a plurality of stable state output variables and the described a plurality of stable state input variable, satisfying in the situation of described predefined condition with acquisition, make described objective function obtain the value of next moment stable state input variable of extreme value, as next moment stable state input variable value, described objective function is take described stable state input variable weights, described stable state input variable desired value as parameter, and the function take described next moment stable state input variable as variable;
Step 3. passes to the base control loop with described next moment stable state input variable value controllable variable of described commercial unit is implemented control.
Preferably, described objective function is described next constantly linear function or quadratic function of the product of the difference of stable state input variable and described stable state input variable desired value and described stable state input variable weights.
Preferably, described stable state input variable weights are the related value at costs of described stable state input variable value generation unit change.
Preferably, stable function relational model between described a plurality of stable state input variable and the described a plurality of stable state output variable is that the stable state output increment is linear combination and the round-off error sum of stable state input increment and disturbance input increment, the coefficient of linear combination is determined according to the object steady-state model
Described stable state output increment is the difference between next moment stable state output variable and the current time stable state output variable,
Described stable state input increment is the difference between next moment stable state input variable and the current time stable state input variable,
Described disturbance input increment is the constantly difference between the disturbance input value of current time disturbance input value and upper.
Preferably, this control method also comprises:
Set stable state input variable target zone for described at least one stable state input variable, described stable state input variable desired value is among described stable state input variable target zone;
Repeatedly repeat described step 2 and step 3, so that next moment stable state input variable value of described at least one the stable state input variable that finally obtains is within described stable state input variable target zone.
Preferably, also comprise:
For described at least one stable state output variable is set stable state output variable target zone,
Wherein, by repeatedly repeating described step 2 and step 3, also so that according to described next stable state input variable value constantly, next of described at least one the stable state output variable that obtains by described stable function relational model constantly stable state output variable value within described stable state output variable target zone.
Preferably, part stable state input variable is the first stable state input variable of Offered target set point not in described a plurality of stable state input variable, part stable state input variable is the second stable state input variable that is provided with target set point, and described target set point comprises stable state input variable desired value
Described objective function is:
The linear function of the difference of next moment first stable state input variable and current time the first stable state input variable and the product of the first stable state input variable weights, add next constantly linear function of the product of the difference of second stable state input variable and stable state input variable desired value and the second stable state input variable weights, perhaps
Next is the quadratic function of the product of the difference of first stable state input variable and current time the first stable state input variable and the first stable state input variable weights constantly, adds the quadratic function of the product of the difference of next moment second stable state input variable and stable state input variable desired value and the second stable state input variable weights.
According to a second aspect of the invention, a kind of control appliance of industrial process also is provided, a plurality of output variables that described industrial process has a plurality of input variables and with the change of described a plurality of input variables, changes, described a plurality of input variable is to carry out the controlled variable of the industrial equipment of described industrial process, described a plurality of output variable is the variable relevant with the operation result of described industrial process, described a plurality of input variable and described a plurality of output variable corresponding a plurality of stable state input variables and a plurality of stable state output variable under stable state need to meet predefined condition
It is characterized in that this opertaing device comprises:
Setting device is used for for each stable state input variable stable state input variable weights being set, and at least one stable state input variable stable state input variable desired value is set;
Optimize calculation element, be used for the based target function and be optimized calculating about the stable function relational model between described a plurality of stable state output variables and the described a plurality of stable state input variable, satisfying in the situation of described predefined condition with acquisition, make described objective function obtain the value of next moment stable state input variable of extreme value, as next moment stable state input variable value, described objective function is take described stable state input variable weights, described stable state input variable desired value as parameter, and the function take described next moment stable state input variable as variable;
The commercial unit control device is used for that described next moment stable state input variable value is passed to the base control loop controllable variable of described commercial unit is implemented control.
Preferably, described objective function is described next constantly linear function or quadratic function of the product of the difference of stable state input variable and described stable state input variable desired value and described stable state input variable weights.
Preferably, this opertaing device also comprises:
The target zone setting device is used to described at least one stable state input variable to set stable state input variable target zone, described stable state input variable desired value among described stable state input variable target zone,
Described optimization calculation element repeatedly repeats described optimization and calculates, so that next moment stable state input variable value of described at least one the stable state input variable that finally obtains is within described stable state input variable target zone.
Control method by industrial process provided by the present invention, stable function relational model between based target function and stable state input variable and the stable state output variable is optimized calculating, objective function is as parameter take predefined stable state input variable weights and stable state input variable desired value, calculating makes objective function obtain next moment stable state input variable of extreme value, as next moment stable state input variable.The setting of stable state input variable weights and objective function extreme value obtain the consideration that has embodied the systematic economy performance, simultaneously, follow the tracks of as target set point by setting stable state input variable desired value, be implemented under the prerequisite of taking into account the systematic economy performance tracking to target set point, thereby next that obtains constantly stable state input variable has more practicality, and then next moment stable state input variable value that the controllable variable of commercial unit is set to obtain is controlled to realize the more excellent industrial process of performance.
Description of drawings
By referring to the detailed description of accompanying drawing to exemplary embodiment of the present invention, it is clear that further feature of the present invention and advantage thereof will become.
The accompanying drawing that consists of the part of instructions has been described embodiments of the invention, and is used for explaining principle of the present invention together with the description.
With reference to accompanying drawing, according to following detailed description, can more be expressly understood the present invention, wherein:
Fig. 1 shows the schematic flow sheet of control method embodiment provided by the present invention;
Fig. 2 shows the synoptic diagram that the present invention sets stable state input variable target zone;
Fig. 3 shows the synoptic diagram that the present invention sets stable state output variable target zone;
Fig. 4 shows the track synoptic diagram of next moment stable state input variable value among the control method embodiment provided by the present invention;
Fig. 5 shows the structural representation of opertaing device embodiment provided by the present invention.
Embodiment
Describe various exemplary embodiment of the present invention in detail now with reference to accompanying drawing.It should be noted that: unless specify in addition, positioned opposite, numeral expression formula and the numerical value of the step of setting forth in these embodiments do not limit the scope of the invention.
Below be illustrative to the description only actually of at least one exemplary embodiment, never as any restriction to the present invention and application or use.
May not discuss in detail for the known technology of person of ordinary skill in the relevant, method and apparatus, but in suitable situation, described technology, method and apparatus should be regarded as authorizing the part of instructions.
In all examples with discussing shown here, it is exemplary that any occurrence should be construed as merely, rather than as restriction.Therefore, other example of exemplary embodiment can have different values.
It should be noted that: represent similar terms in similar label and the letter accompanying drawing below, therefore, in case be defined in a certain Xiang Zaiyi accompanying drawing, then in accompanying drawing subsequently, do not need it is further discussed.
A plurality of output variables that industrial process has a plurality of control inputs variablees and changes with the change of these a plurality of input variables.A plurality of input variables are to carry out the controllable variable of the commercial unit of industrial process, a plurality of output variables are variablees relevant with the operation result of industrial process, for the Linear Multivariable process, the correspondence between a plurality of input variables and a plurality of output variable can be described with certain functional relationship model.Functional relationship model is definite by the intrinsic propesties of system, utilizes the functional relationship model of system to obtain the control output variable according to the control inputs variable, and vice versa.
Input variable and the functional relationship model between the output variable of industrial process systems can have multiple.After the functional relationship model of the system of acquisition, also need functional relationship model is carried out the stable state processing, with the acquisition system when reaching stable state the stable state input variable and the stable function relational model between the stable state output variable, stable state input variable and stable state output variable are corresponding to input variable and the expression of output variable under stable state of system.
A plurality of stable state input variables of industrial process and the stable function relational model of a plurality of stable state output variables can have multiple.For example, a kind of stable function relational model can be expressed as linear combination and the round-off error sum that the stable state output increment is stable state input increment and disturbance input increment, the coefficient of linear combination is determined according to the object steady-state model, wherein, the stable state output increment is the difference between next moment stable state output variable and the current time stable state output variable, stable state input increment is the difference between next moment stable state input variable and the current time stable state input variable, and the disturbance input increment is the constantly difference between the disturbance input value of current time disturbance input value and upper.
For the industrial processes of reality, there are respectively certain edge-restraint condition in stable state input variable and stable state output variable.Therefore, a plurality of stable state input variables and a plurality of stable state output variable need to satisfy certain predefined condition so that next constantly stable state input variable and next constantly the stable state output variable between the upper boundary values and lower border value of separately edge-restraint condition.
In addition, stable state input variable and stable state output variable also will be subject to the restriction of stable state increment constraint condition in the implementation of optimizing and controlling, stable state input increment and stable state output increment lay respectively between the upper boundary values and lower border value of increment constraint condition separately.Stable state input increment is the difference between next moment stable state input variable and the current time stable state input variable, and the stable state output increment is the difference between next moment stable state output variable and the current time stable state output variable,
With reference to shown in Figure 1, this figure is the schematic flow sheet of a kind of embodiment of control method of industrial process of the present invention, and the below introduces the step of the control method embodiment of industrial process of the present invention in detail.
A plurality of output variables that industrial process described in each embodiment has a plurality of input variables and changes with the change of a plurality of input variables.A plurality of input variables are to carry out the controllable variable of the commercial unit of industrial process, and a plurality of output variables are variablees relevant with the operation result of industrial process.To be a plurality of input variables of system and a plurality of output variable be in expression under the stable state in system for a plurality of stable state input variables and a plurality of stable state output variable, and a plurality of stable state input variables are corresponding with a plurality of input variables and a plurality of output variable with a plurality of stable state output variables.
A plurality of stable state input variables and a plurality of stable state output variable satisfy predefined condition, both aforementioned edge-restraint condition and increment constraint condition.
In step 101, for each stable state input variable arranges stable state input variable weights, and at least one stable state input variable stable state input variable desired value is set.
Because stable state input increment Delta U
∞(k) with stable state output increment Δ Y
∞(k) there is the represented linear dependence relation of above-mentioned stable function relational model, therefore, can both are unified with stable state input increment Delta U
∞(k) expression.
Using stable state input increment Delta U
∞(k) expression stable state output increment Δ Y
∞(k) afterwards, for concrete industrial process, be stable state input increment Delta U
∞(k) stable state input variable weights are set.The method that weights are set can be that benefit or the cost that the unit increment with the stable state input variable produces carries out standardization, and the parameter behind the Application standard represents benefit or the cost of each stable state input variable.Be that stable state input variable weights are the related value at costs of stable state input variable value generation unit change.Can use ± symbol distinguishes cost and benefit ,+expression cost ,-expression benefit.For example, the set of the stable state input variable weights of each stable state input variable can be expressed as C
T=[c
1c
2C
m], m is the number of stable state input variable.
A plurality of stable state input variables of industrial process may have different characteristics, wherein a part of stable state input variable needs the target setting set point, method for tracking target by steady-state optimization calculates next steady state operation point constantly, in the situation that reaches the economic performance optimum, make next steady state operation point constantly approach as much as possible the target set point of setting.But, for another part stable state input variable target setting set point not, only the calculating of the method for tracking target by steady-state optimization makes next steady state operation point constantly, in the situation that reaches the economic performance optimum, next steady state operation point constantly is as much as possible near the stable state input variable value of current time.
For the stable state input variable that needs the target setting set point, except needs arrange stable state input variable weights, also need to arrange stable state input variable desired value U
T
Target set point is desired systematic steady state operating point, and target set point comprises stable state input variable desired value U
TWith stable state output variable desired value Y
TBecause stable state input variable desired value U
TWith stable state output variable desired value Y
TBetween the linear dependence relation that exists, therefore, by stable state input variable desired value U is set
TAnd the relation of the linear dependence between them, can obtain stable state output variable desired value Y
T
Target set point can be the result that the optimizer optimization on system upper strata is calculated, and also can be rule of thumb given ideal value of technologist.
In step 102, based target function and be optimized calculating about the stable function relational model between a plurality of stable state output variables and a plurality of stable state input variable, satisfying in the situation of predefined condition with acquisition, make objective function obtain the value of next moment stable state input variable of extreme value, constantly input the steady-state variable value as next.Objective function is take stable state input variable weights, stable state input variable desired value as parameter, and a following moment stable state input variable is the function of variable.
Be to embody the economic performance of industrial process systems, objective function can be selected take stable state input variable weights and stable state input variable desired value as parameter, and following one constantly the stable state input variable be the function of variable.Because stable state input variable weights are relevant with certain economic target of stable state input variable, therefore, satisfying in the situation of predefined condition, make objective function obtain the value of next moment stable state input variable of extreme value, as next moment stable state input variable value, can realize the extreme value of this kind economic target, and follow the tracks of as target set point by setting stable state input variable desired value, thereby can be implemented in the tracking that realizes under the prerequisite of taking into account the systematic economy performance target set point.
Objective function can be next constantly linear function or quadratic function of the product of the difference of stable state input variable and stable state input variable desired value and stable state input variable weights.
In step 103, next moment stable state input variable value is passed to the base control loop controllable variable of commercial unit is implemented control.Next stable state input variable value constantly that the controllable variable of commercial unit is set in step 102 to obtain, thus can realize the stable state input variable desired value of more approaching setting and take into account the industrial process control of economy.
Be optimized calculate when obtaining objective function and obtaining extreme value next constantly in the process of the value of stable state input variable, a plurality of stable state output variables can obtain by the stable function relational model between a plurality of stable state input variables and a plurality of stable state output variable.Thereby can also realize that the based target function obtains in the situation of predefined condition, near the target set point (U of setting
T, Y
T) next steady-working state (U
∞(k+1), Y
∞(k+1)).
Next steady-working state (the U that the based target function obtains
∞(k+1), Y
∞(k+1)) except satisfying above-mentioned predefined condition, namely in another embodiment, can also further increase (U
∞(k+1), Y
∞(k+1)) soft-constraint condition was both set stable state input variable target zone (U for the stable state input variable
Tmin, U
Tmax), input variable desired value U
TAmong stable state input variable target zone, and be stable state output variable setting stable state output variable target zone (Y
Tmin, Y
Tmax), satisfy following infinitive group:
U
Tmin≤U
∞(k+1)≤U
Tmax
Y
Tmin≤Y
∞(k+1)≤Y
Tmax
Wherein,
With
Be respectively lower bound and the upper bound of the stable state input variable target zone of setting.Usually, the soft-constraint condition is with respect to the more strict condition of aforementioned predefined condition, therefore, and U
Tmin, U
TmaxValue be different from U
Min, U
Max, UT as a rule
Min〉=U
Min, U
Tmax≤ U
Max
With reference to shown in Figure 2, (U
Tmin, U
Tmax) scope that covers of value is less than (U
Min, U
Max), U among the figure
T_rangeExpression U
TScope that can value.
With reference to shown in Figure 3, similarly, (Y
Tmin, Y
Tmax) scope that covers of value is less than (Y
Min, Y
Max), Y among Fig. 3
T_rangeExpression Y
TScope that can value.
Using objective function to be optimized calculating to realize in the tracing process to target set point that the result who finishes suboptimization calculating is (U
∞(k+1), Y
∞(k+1)) may not satisfy soft-constraint condition both stable state input and stable state output variable target zone, therefore can use the method for iteration repeatedly to carry out optimization calculating, so that next moment stable state input variable U that finally obtains
∞(k+1) at this stable state input variable target zone (U
Tmin, U
Tmax) within, and next output variable stable state Y constantly of at least one the stable state output variable that obtains by the stable function relational model
∞(k+1) at output variable target zone (Y
Tmin, Y
Tmax) within.
With reference to shown in Figure 4, this figure stable state input variable at following a moment steady-state value is example, shows through next moment stable state input variable value U after the iterative computation repeatedly
∞(k+1) reach stable state input variable target zone (U
Tmin, U
Tmax) within trajectory diagram.In Fig. 4, Δ U
∞' (k) represent next constantly stable state input variable U
∞(k+1) with stable state input variable desired value U
TPoor, Δ U
∞(k) represent next constantly stable state input variable U
∞(k+1) with current time stable state input variable U
∞(k) poor.
Further, obtaining next constantly stable state input variable U
∞(k+1) after, can be with U
∞(k+1) pass to the base control loop controllable variable of commercial unit is implemented control.
With U
∞(k+1) pass to the base control loop and implement control after, system is subject to the control in base control loop, state will change, thereby step 102 in next can circulate again execution above-described embodiment constantly, both according to stable state input variable desired value, and based target function and stable function relational model are optimized calculating, to obtain next new moment stable state input variable value and next new moment stable state output variable value, execution in step 103 is controlled again, i.e. repeatedly repeated execution of steps 102 and step 103, so that next moment stable state input variable value of at least one the stable state input variable that finally obtains is within stable state input variable target zone, and according to next stable state input variable value constantly, next of at least one the stable state output variable that obtains by the stable function relational model constantly stable state output variable value within stable state output variable target zone.
In the process of carrying out loop optimization calculating, the input variable desired value can be immovable usually after setting.
In addition, as a kind of optional embodiment, also can only set stable state input variable target zone (U for the stable state input variable
Tmin, U
Tmax), stable state input variable desired value is among this input variable target zone.Repeatedly repeated execution of steps 102 and step 103 are so that next of the stable state input variable that finally obtains stable state input variable value U constantly
∞(k+1) at stable state input variable target zone (U
Tmin, U
Tmax) within.In such an embodiment, next moment stable state output variable Y
∞(k+1) only need to satisfy the predefined constraint condition of system.
As previously mentioned, may have different characteristics according to a plurality of input variables, in the computation process of carrying out an industrial process control, for a plurality of stable state input variables corresponding to a plurality of input variables, may need part stable state input variable target setting set point, in the situation that reaches the economic performance optimum, the method for setting up an office by target setting is optimized the target set point of calculating the approaching as far as possible setting of steady state operation point that makes next moment.To another part stable state input variable target setting set point not, in the situation that reaches the economic performance optimum, calculate and make next steady state operation point constantly as far as possible near the steady state operation point of current time.
Particularly, part stable state input variable is the first stable state input variable of Offered target set point not in a plurality of stable state input variables, part stable state input variable is the second stable state input variable that is provided with target set point, target set point comprises stable state input variable desired value, objective function can for:
The linear function of the difference of next moment first stable state input variable and current time the first stable state input variable and the product of the first stable state input variable weights, add next constantly linear function of the product of the difference of second stable state input variable and stable state input variable desired value and the second stable state input variable weights, perhaps
Next is the quadratic function of the product of the difference of first stable state input variable and current time the first stable state input variable and the first stable state input variable weights constantly, adds the quadratic function of the product of the difference of next moment second stable state input variable and stable state input variable desired value and the second stable state input variable weights.
With reference to shown in Figure 5, the present invention also provides the opertaing device of the corresponding industrial process of control method a kind of and of the present invention, and this figure is the structural representation of a kind of embodiment of opertaing device.
A plurality of output variables that industrial process has a plurality of input variables and changes with the change of a plurality of input variables, a plurality of input variables are to carry out the controllable variable of the commercial unit of industrial process, a plurality of output variables are variablees relevant with the operation result of industrial process, a plurality of input variables and a plurality of output variable corresponding a plurality of stable state input variables and a plurality of stable state output variable under stable state need to satisfy predefined condition, and this opertaing device 500 comprises setting device 501, optimizes calculation element 502 and commercial unit control device 503.
Optimizing calculation element 502 is used for the based target function and is optimized calculating about the stable function relational model between a plurality of stable state output variables and a plurality of stable state input variable, satisfying in the situation of predefined condition with acquisition, make objective function obtain the value of next moment stable state input variable of extreme value, as next moment stable state input variable value, objective function is take stable state input variable weights, stable state input variable desired value as parameter, and a following moment stable state input variable is the function of variable.
Commercial unit control device 503 is used for that next moment stable state input variable value is passed to the base control loop controllable variable of commercial unit is implemented control.
In another kind of embodiment, objective function is next constantly linear function or quadratic function of the product of the difference of stable state input variable and stable state input variable desired value and stable state input variable weights.
In another kind of embodiment, this opertaing device also comprises the target zone setting device.
The target zone setting device is used at least one stable state input variable to set stable state input variable target zone, stable state input variable desired value among stable state input variable target zone,
Optimize calculation element and repeatedly repeat optimization calculating, so that next moment stable state input variable value of at least one the stable state input variable that finally obtains is within stable state input variable target zone.
So far, control method and equipment according to a kind of industrial process of the present invention have been described in detail.For fear of covering design of the present invention, details more known in the field are not described.Those skilled in the art can understand how to implement technical scheme disclosed herein fully according to top description.
In addition, the annexation between the constituent apparatus of embodiment of the invention equipment only represents to concern example based on an information flow direction of the present invention, is not restricted to physical connection relation, and also not necessarily realize embodiment of the invention institute necessary or only for.
May realize in many ways method and apparatus of the present invention.For example, can realize method and system of the present invention by any combination of software, hardware, firmware or software, hardware, firmware.The said sequence that is used for the step of described method only is in order to describe, and the step of method of the present invention is not limited to above specifically described order, unless otherwise specify.In addition, in certain embodiments, can be the program that is recorded in the recording medium with the invention process also, these programs comprise for the machine readable instructions that realizes the method according to this invention.Thereby the present invention also covers the recording medium that storage is used for the program of executive basis method of the present invention.
Although by example specific embodiments more of the present invention are had been described in detail, it should be appreciated by those skilled in the art that above example only is in order to describe, rather than in order to limit the scope of the invention.It should be appreciated by those skilled in the art, can in situation about not departing from the scope of the present invention with spirit, above embodiment be made amendment.Scope of the present invention is limited by claims.
Claims (10)
1. the control method of an industrial process,
A plurality of output variables that described industrial process has a plurality of input variables and changes with the change of described a plurality of input variables, described a plurality of input variable is to carry out the controllable variable of the commercial unit of described industrial process, described a plurality of output variable is the variable relevant with the operation result of described industrial process, described a plurality of input variable and described a plurality of output variable corresponding a plurality of stable state input variables and a plurality of stable state output variable under stable state need to satisfy predefined condition
It is characterized in that described method comprises:
Step 1. arranges stable state input variable weights for each stable state input variable, and at least one stable state input variable stable state input variable desired value is set;
Step 2. based target function and be optimized calculating about the stable function relational model between described a plurality of stable state output variables and the described a plurality of stable state input variable, satisfying in the situation of described predefined condition with acquisition, make described objective function obtain the value of next moment stable state input variable of extreme value, as next moment stable state input variable value, described objective function is take described stable state input variable weights, described stable state input variable desired value as parameter, and the function take described next moment stable state input variable as variable;
Step 3. passes to the base control loop with described next moment stable state input variable value controllable variable of described commercial unit is implemented control.
2. control method according to claim 1 is characterized in that, described objective function is described next constantly linear function or quadratic function of the product of the difference of stable state input variable and described stable state input variable desired value and described stable state input variable weights.
3. control method according to claim 1 is characterized in that, described stable state input variable weights are the related value at costs of described stable state input variable value generation unit change.
4. control method according to claim 1, it is characterized in that, stable function relational model between described a plurality of stable state input variable and the described a plurality of stable state output variable is that the stable state output increment is linear combination and the round-off error sum of stable state input increment and disturbance input increment, the coefficient of linear combination is determined according to the object steady-state model
Described stable state output increment is the difference between next moment stable state output variable and the current time stable state output variable,
Described stable state input increment is the difference between next moment stable state input variable and the current time stable state input variable,
Described disturbance input increment is the constantly difference between the disturbance input value of current time disturbance input value and upper.
5. control method according to claim 4 is characterized in that, also comprises:
Set stable state input variable target zone for described at least one stable state input variable, described stable state input variable desired value is among described stable state input variable target zone;
Repeatedly repeat described step 2 and step 3, so that next moment stable state input variable value of described at least one the stable state input variable that finally obtains is within described stable state input variable target zone.
6. control method according to claim 5 is characterized in that, also comprises:
For described at least one stable state output variable is set stable state output variable target zone,
Wherein, by repeatedly repeating described step 2 and step 3, also so that according to described next stable state input variable value constantly, next of described at least one the stable state output variable that obtains by described stable function relational model constantly stable state output variable value within described stable state output variable target zone.
7. control method according to claim 2 is characterized in that,
Part stable state input variable is the first stable state input variable of Offered target set point not in described a plurality of stable state input variable, part stable state input variable is the second stable state input variable that is provided with target set point, described target set point comprises stable state input variable desired value
Described objective function is:
The linear function of the difference of next moment first stable state input variable and current time the first stable state input variable and the product of the first stable state input variable weights, add next constantly linear function of the product of the difference of second stable state input variable and stable state input variable desired value and the second stable state input variable weights, perhaps
Next is the quadratic function of the product of the difference of first stable state input variable and current time the first stable state input variable and the first stable state input variable weights constantly, adds the quadratic function of the product of the difference of next moment second stable state input variable and stable state input variable desired value and the second stable state input variable weights.
8. the opertaing device of an industrial process,
A plurality of output variables that described industrial process has a plurality of input variables and changes with the change of described a plurality of input variables, described a plurality of input variable is to carry out the controllable variable of the commercial unit of described industrial process, described a plurality of output variable is the variable relevant with the operation result of described industrial process, described a plurality of input variable and described a plurality of output variable corresponding a plurality of stable state input variables and a plurality of stable state output variable under stable state need to satisfy predefined condition
It is characterized in that this opertaing device comprises:
Setting device is used for for each stable state input variable stable state input variable weights being set, and at least one stable state input variable stable state input variable desired value is set;
Optimize calculation element, be used for the based target function and be optimized calculating about the stable function relational model between described a plurality of stable state output variables and the described a plurality of stable state input variable, satisfying in the situation of described predefined condition with acquisition, make described objective function obtain the value of next moment stable state input variable of extreme value, as next moment stable state input variable value, described objective function is take described stable state input variable weights, described stable state input variable desired value as parameter, and the function take described next moment stable state input variable as variable;
The commercial unit control device is used for that described next moment stable state input variable value is passed to the base control loop controllable variable of described commercial unit is implemented control.
9. opertaing device according to claim 8 is characterized in that, described objective function is described next constantly linear function or quadratic function of the product of the difference of stable state input variable and described stable state input variable desired value and described stable state input variable weights.
10. opertaing device according to claim 8 is characterized in that, also comprises:
The target zone setting device is used to described at least one stable state input variable to set stable state input variable target zone, described stable state input variable desired value among described stable state input variable target zone,
Described optimization calculation element repeatedly repeats described optimization and calculates, so that next moment stable state input variable value of described at least one the stable state input variable that finally obtains is within described stable state input variable target zone.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210084637.4A CN103365207B (en) | 2012-03-28 | 2012-03-28 | A kind of control method of industrial process and equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210084637.4A CN103365207B (en) | 2012-03-28 | 2012-03-28 | A kind of control method of industrial process and equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103365207A true CN103365207A (en) | 2013-10-23 |
| CN103365207B CN103365207B (en) | 2016-05-11 |
Family
ID=49366790
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210084637.4A Active CN103365207B (en) | 2012-03-28 | 2012-03-28 | A kind of control method of industrial process and equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103365207B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113283059A (en) * | 2021-04-29 | 2021-08-20 | 汪洋 | Chain architecture, model unit and configuration method of distributed serial computing |
| CN115453862A (en) * | 2022-11-09 | 2022-12-09 | 质子汽车科技有限公司 | Adaptive control system and parameter adjusting method thereof |
| CN115963795A (en) * | 2023-01-04 | 2023-04-14 | 浙江中智达科技有限公司 | Process industrial control method, device, equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE2921038A1 (en) * | 1978-05-24 | 1979-11-29 | Hitachi Ltd | PROCESS FOR ADAPTIVE PROCESS CONTROL |
| CN1270333A (en) * | 1995-06-14 | 2000-10-18 | 霍尼韦尔公司 | Optimization of procedure controller in multi-variable pre-detecting controller |
| CN1490690A (en) * | 2002-09-11 | 2004-04-21 | ����-��˹â��ϵͳ�ɷ�����˾ | Integrated model predicting control and optimization in process control system |
| CN1900857A (en) * | 2005-07-20 | 2007-01-24 | 王建 | Real time operation optimizing method for multiple input and multiple output continuous producing process |
| CN101620414A (en) * | 2009-08-12 | 2010-01-06 | 华东理工大学 | Method for optimizing cracking depth of industrial ethane cracking furnace on line |
-
2012
- 2012-03-28 CN CN201210084637.4A patent/CN103365207B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE2921038A1 (en) * | 1978-05-24 | 1979-11-29 | Hitachi Ltd | PROCESS FOR ADAPTIVE PROCESS CONTROL |
| CN1270333A (en) * | 1995-06-14 | 2000-10-18 | 霍尼韦尔公司 | Optimization of procedure controller in multi-variable pre-detecting controller |
| CN1490690A (en) * | 2002-09-11 | 2004-04-21 | ����-��˹â��ϵͳ�ɷ�����˾ | Integrated model predicting control and optimization in process control system |
| CN1900857A (en) * | 2005-07-20 | 2007-01-24 | 王建 | Real time operation optimizing method for multiple input and multiple output continuous producing process |
| CN101620414A (en) * | 2009-08-12 | 2010-01-06 | 华东理工大学 | Method for optimizing cracking depth of industrial ethane cracking furnace on line |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113283059A (en) * | 2021-04-29 | 2021-08-20 | 汪洋 | Chain architecture, model unit and configuration method of distributed serial computing |
| CN115453862A (en) * | 2022-11-09 | 2022-12-09 | 质子汽车科技有限公司 | Adaptive control system and parameter adjusting method thereof |
| CN115453862B (en) * | 2022-11-09 | 2023-02-28 | 质子汽车科技有限公司 | Self-adaptive control system and parameter adjusting method thereof |
| CN115963795A (en) * | 2023-01-04 | 2023-04-14 | 浙江中智达科技有限公司 | Process industrial control method, device, equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103365207B (en) | 2016-05-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Giorgetti et al. | Hybrid model predictive control application towards optimal semi-active suspension | |
| Lanusse et al. | CRONE control system design toolbox for the control engineering community: tutorial and case study | |
| CN101344065B (en) | Parameter optimization method of hydraulic turbine speed control system based on satisfaction control | |
| Song et al. | Adaptive backstepping control of train systems with traction/braking dynamics and uncertain resistive forces | |
| CN102073270B (en) | The Fractional Order PID control method of single-input single-output time lag system | |
| CN101813916B (en) | Self-adaptive prediction function control method for nonlinear production process | |
| CN102129259B (en) | Neural network proportion integration (PI)-based intelligent temperature control system and method for sand dust environment test wind tunnel | |
| CN104698842B (en) | A kind of LPV model nonlinear forecast Control Algorithms based on interior point method | |
| CN103645725A (en) | Teaching track planning method and system for robot | |
| Kubalík et al. | Symbolic regression methods for reinforcement learning | |
| CN101763083A (en) | An effective industrial process dynamic optimization system and method capable of controlling variable parameterization | |
| CN102540875A (en) | Discrete time-delay system control method based on satisfaction digital PID (Proportion Integration Differentiation) controller | |
| CN105204345A (en) | Self-adaptive fractional order sliding-mode control method | |
| CN103365207A (en) | Industrial process control method and industrial process control equipment | |
| CN105425580A (en) | Construction method of ITAE (Integral Time absolute error) optimal N-type system | |
| CN104135205A (en) | Control method for maximum torque current rate of induction motor | |
| CN101763087B (en) | Industrial process dynamic optimization system and method based on nonlinear conjugate gradient method | |
| Gazzaneo et al. | Multilayer operability framework for process design, intensification, and modularization of nonlinear energy systems | |
| Sun et al. | Nonconvex activation noise-suppressing neural network for time-varying quadratic programming: Application to omnidirectional mobile manipulator | |
| Wu et al. | Finite‐time control for a fractional‐order non‐linear HTGS | |
| CN106773688A (en) | A kind of direct adaptive control method and device | |
| Sawant et al. | A decision-making methodology for automated guided vehicle selection problem using a preference selection index method | |
| CN103970017A (en) | TS fuzzy control based synchronizing method for fractional order chaotic system and integer order chaotic system | |
| CN112462608B (en) | Discrete sliding mode track and speed tracking control method for high-speed train | |
| CN110209122A (en) | A kind of control method, device, medium and the equipment of multiaxial motion platform |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |