CN112782969A - PID parameter setting method and device, storage medium and equipment - Google Patents

PID parameter setting method and device, storage medium and equipment Download PDF

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CN112782969A
CN112782969A CN202011566703.2A CN202011566703A CN112782969A CN 112782969 A CN112782969 A CN 112782969A CN 202011566703 A CN202011566703 A CN 202011566703A CN 112782969 A CN112782969 A CN 112782969A
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value
control system
filter coefficient
performance evaluation
preset
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CN112782969B (en
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裘坤
李雨宽
刘志勇
吴洁芸
吴庆尉
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Zhejiang Supcon Technology Co Ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B11/00—Automatic controllers
    • G05B11/01—Automatic controllers electric
    • G05B11/36—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential
    • G05B11/42—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential for obtaining a characteristic which is both proportional and time-dependent, e.g. P.I., P.I.D.
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

The application discloses a PID parameter setting method, a device, a storage medium and equipment, which are used for calculating the total simulation duration of a control system based on an industrial process model. And determining the value range of the filter coefficient according to the total simulation duration, wherein the filter coefficient is a calculation parameter contained in a preset expression, and the preset expression is used for indicating the PID parameter. And selecting the value of the filter coefficient from the value range, substituting the value into a preset expression, and calculating to obtain the numerical value of the PID parameter. And simulating the control system based on the numerical value of the PID parameter to obtain dynamic response data. And substituting the dynamic response data into a preset performance index function, and calculating to obtain a performance evaluation value. A target value is selected from a plurality of values of the filter coefficient. Substituting the target value into a preset expression, and calculating to obtain a setting value of the PID parameter. By utilizing the method to adjust the PID parameters, the control performance of the PID controller can be improved, so that the control requirements of rapidity and stability of a control system are met.

Description

PID parameter setting method and device, storage medium and equipment
Technical Field
The present application relates to the field of data processing, and in particular, to a PID parameter tuning method, apparatus, storage medium, and device.
Background
PID control is a comprehensive control based on Proportional (proportionality), Integral (Integral) and Derivative (Derivative) of deviation, a simple but effective control algorithm based on estimates of "present" and "past" information. Due to the advantages of simple algorithm, good robustness, high reliability and the like, the PID control strategy is widely applied to a control system of an industrial process. The PID control is based on proportional control to determine the response speed of the system; integral control may eliminate steady state errors, but may increase system overshoot; differential control can accelerate the response speed of the large inertia system and weaken the overshoot tendency. Before the PID controller is put into use, PID parameters (including a proportional coefficient, an integral coefficient and a differential coefficient) are required to be set (so-called PID parameter setting, which is essentially to select an optimal value for the proportional coefficient, the integral coefficient and the differential coefficient), and the setting value of the PID parameters is obtained, so that the compromise between the control accuracy and the speed of the PID controller is obtained.
At present, in the prior art, a genetic algorithm is generally used for setting a PID parameter, however, the setting effect (namely the setting value of the PID parameter) of the prior art is difficult to meet the control requirements of rapidity and stability of a control system (or a PID controller) at the same time.
Disclosure of Invention
The application provides a PID parameter setting method, a device, a storage medium and equipment, and aims to improve the control performance of a PID controller so as to meet the control requirements of rapidity and stability of a control system.
In order to achieve the above object, the present application provides the following technical solutions:
a PID parameter tuning method comprises the following steps:
calculating the total simulation duration of the control system based on the industrial process model; the industrial process model is used for indicating a control object of a PID controller, and the control system is constructed based on the PID controller and the industrial process model;
determining the value range of the filter coefficient according to the total simulation duration; the filter coefficient is a calculation parameter contained in a preset expression; the preset expression is used for indicating PID parameters;
selecting the value of the filter coefficient from the value range, substituting the value into the preset expression, and calculating to obtain the numerical value of the PID parameter;
simulating the control system based on the numerical value of the PID parameter to obtain dynamic response data;
substituting the dynamic response data into a preset performance index function, and calculating to obtain a performance evaluation value; the performance evaluation value is used for indicating the out-of-control probability of the control system;
selecting a target value from a plurality of values of the filter coefficient; wherein the target value is a value satisfying a preset condition; the preset conditions are as follows: the performance evaluation value obtained by corresponding calculation based on the value is smaller than a preset threshold value;
substituting the target value into the preset expression, and calculating to obtain the setting value of the PID parameter.
Optionally, the calculating a total simulation duration of the control system based on the industrial process model includes:
simulating the industrial process model to obtain a starting value and a steady-state value of the step response of the industrial process model;
calculating the time difference between the initial value and the steady-state value to obtain steady-state duration;
and calculating the total simulation time length of the control system according to the steady-state time length.
Optionally, the selecting a value of the filter coefficient from the value range, substituting the value into the preset expression, and calculating to obtain a value of the PID parameter includes:
dividing the value range of the filter coefficient into n intervals according to a preset value interval; n is a positive integer;
counting the upper limit value and the lower limit value of each interval to obtain n different numerical values;
taking the n different numerical values as n values of the filter coefficient;
and substituting the n values of the filter coefficient into the preset expression respectively, and correspondingly calculating to obtain n numerical values of the PID parameter.
Optionally, the simulating the control system based on the value of the PID parameter to obtain dynamic response data includes:
respectively substituting n numerical values of the PID parameters into the control system, and carrying out n times of simulation on the control system according to preset simulation conditions to obtain n groups of dynamic response data; wherein n is a positive integer, and the preset simulation conditions are as follows: and performing unit step disturbance on an output set value of the control system, and increasing 1/3 units of amplification interference on the output of the control system under the condition that the control time is more than 0.5 time of the total simulation time.
Optionally, selecting a target value from the plurality of values of the filter coefficient includes:
selecting n values of the filter coefficient from the value range, wherein n is a positive integer;
counting n performance evaluation values obtained by corresponding calculation based on the n values;
selecting the performance evaluation value with the minimum value from the n performance evaluation values as a target performance evaluation value;
and taking the value of the filter coefficient corresponding to the target performance evaluation value as a target value under the condition that the target performance evaluation value is determined to be smaller than the preset threshold value.
Optionally, the method further includes:
under the condition that the target performance evaluation value is determined to be not smaller than the preset threshold value, repeating the step to obtain a new target performance evaluation value, and taking the value of the filter coefficient corresponding to the new target performance evaluation value as the target value until the new target performance evaluation value is smaller than the preset threshold value;
wherein the steps include:
adjusting the value range of the filter coefficient according to the value of the filter coefficient corresponding to the target performance evaluation value, so that the value range is reduced;
selecting n values of the filter coefficient from the adjusted value range;
counting n performance evaluation values obtained by corresponding calculation based on the n values;
and selecting the performance evaluation value with the minimum value from the n performance evaluation values as a new target performance evaluation value.
Optionally, the performance indicator function includes a calculation formula of a performance indicator, where the performance indicator is a combination of an error time integral of the control system, an overshoot factor of an output of the control system, an oscillation factor of an output of the control system, an undershoot factor of an output of the control system, and an oscillation factor of a controlled variable of the control system.
A PID parameter tuning device, comprising:
the first calculation unit is used for calculating the total simulation duration of the control system based on the industrial process model; the industrial process model is used for indicating a control object of a PID controller, and the control system is constructed based on the PID controller and the industrial process model;
the time length determining unit is used for determining the value range of the filter coefficient according to the total simulation time length; the filter coefficient is a calculation parameter contained in a preset expression; the preset expression is used for indicating PID parameters;
the second calculation unit is used for selecting the value of the filter coefficient from the value range, substituting the value into the preset expression and calculating to obtain the numerical value of the PID parameter;
the simulation unit is used for simulating the control system based on the numerical value of the PID parameter to obtain dynamic response data;
the third calculating unit is used for substituting the dynamic response data into a preset performance index function to calculate a performance evaluation value; the performance evaluation value is used for indicating the out-of-control probability of the control system;
a selecting unit configured to select a target value from the plurality of values of the filter coefficient; wherein the target value is a value satisfying a preset condition; the preset conditions are as follows: the performance evaluation value obtained by corresponding calculation based on the value is smaller than a preset threshold value;
and the fourth calculation unit is used for substituting the target value into the preset expression to calculate the setting value of the PID parameter.
A computer-readable storage medium comprising a stored program, wherein the program performs the PID parameter tuning method.
A PID parameter tuning apparatus comprising: a processor, a memory, and a bus; the processor and the memory are connected through the bus;
the memory is used for storing a program, and the processor is used for running the program, wherein the program executes the PID parameter tuning method during running.
According to the technical scheme, the total simulation duration of the control system is calculated based on the industrial process model. The industrial process model is used for indicating a control object of the PID controller, and the control system is constructed based on the PID controller and the industrial process model. And determining the value range of the filter coefficient according to the total simulation time length. The filter coefficients are calculation parameters contained in a preset expression, and the preset expression is used for indicating PID parameters. And selecting the value of the filter coefficient from the value range, substituting the value into a preset expression, and calculating to obtain the numerical value of the PID parameter. And simulating the control system based on the numerical value of the PID parameter to obtain dynamic response data. And substituting the dynamic response data into a preset performance index function, and calculating to obtain a performance evaluation value, wherein the performance evaluation value is used for indicating the out-of-control probability of the control system. A target value is selected from a plurality of values of the filter coefficient. Wherein the target value is a value satisfying a preset condition. The preset conditions are as follows: and the performance evaluation value obtained by corresponding calculation based on the value is smaller than a preset threshold value. Substituting the target value into a preset expression, and calculating to obtain a setting value of the PID parameter. The PID parameters are indicated by the preset expression, only the only filter coefficient needs to be subjected to iterative optimization, and the value range of the filter coefficient is predetermined based on the total simulation duration. In addition, the performance evaluation value is calculated by adopting the performance index and the performance index function, the filter coefficient is set according to the performance evaluation value, the setting value of the PID parameter is ensured to be finally calculated, the out-of-control probability of the control system can be smaller than a preset threshold value, and therefore the stability of the control system is improved. Therefore, the PID parameters are adjusted by using the method, the control performance of the PID controller can be improved, and the control requirements of the control system on rapidity and stability are met.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1a is a schematic diagram of a PID parameter tuning method provided in an embodiment of the present application;
fig. 1b is a schematic structural diagram of a control system according to an embodiment of the present disclosure;
FIG. 1c is a schematic illustration of a step response curve of an industrial process model according to an embodiment of the present disclosure;
fig. 1d is a schematic diagram of a control effect variation curve of a control system according to an embodiment of the present disclosure;
FIG. 1e is a schematic diagram of a control effect curve of another control system provided in the embodiment of the present application;
fig. 2a is a schematic diagram of a derivation process of a preset expression according to an embodiment of the present application;
fig. 2b is a schematic structural diagram of another control system provided in the embodiment of the present application;
fig. 2c is a schematic structural diagram of another control system provided in the embodiment of the present application;
FIG. 3 is a schematic diagram of another PID parameter tuning method provided in an embodiment of the present application;
fig. 4 is a schematic structural diagram of a PID parameter tuning device provided in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
As shown in fig. 1a, a schematic diagram of a PID parameter tuning method provided in an embodiment of the present application includes the following steps:
s101: a single-loop PID negative feedback control system (hereinafter referred to as a control system for short, and essentially understood as a mathematical model) is constructed based on a PID controller and an industrial process model (i.e., a mathematical model of a control object of the PID controller).
The output of the PID controller is u (t), the input is e (t), the output of the industrial process model (which may be understood as the output of the control system) is y (t), the input is u (t), u (t) represents the control quantity of the PID controller (which may be understood as the control quantity of the control system), e (t) is y (t) -r (t), r (t) is the output set value of the control system, t is the control time, the expression of the industrial process model is g(s), and s is a complex variable in a complex domain. Specifically, the schematic structure of the control system is shown in fig. 1 b.
A PID controller is a conventional linear controller that forms a deviation e (t) from a given value and an actual output value, and forms a controlled variable u (t) by linearly combining the proportion, integral, and differential of the deviation e (t) to control a controlled object (for example, an industrial process model), and an expression of the PID controller is shown in formula (1).
Figure BDA0002861879840000071
In the formula (1), KPRepresents the proportionality coefficient, KIRepresents the integral coefficient, KDRepresenting the differential coefficient.
The so-called industrial process model can be understood as: first order lag model
Figure BDA0002861879840000072
And second order lag model
Figure BDA0002861879840000073
τ is the pure lag time (which can be set by the skilled person according to the actual situation), and a, b, and c are all constants.
S102: and simulating the industrial process model to obtain an initial value and a steady-state value of the step response of the industrial process model, and calculating the time difference between the initial value and the steady-state value to obtain the steady-state duration.
The specific implementation process of simulating the industrial process model to obtain the initial value and the steady-state value of the step response of the industrial process model is common knowledge familiar to those skilled in the art, and is not described herein again.
Specifically, assume an industrial process model of
Figure BDA0002861879840000074
To pair
Figure BDA0002861879840000075
Performing simulation to obtain a step response curve of the industrial process model as shown in FIG. 1c, calculating the time difference between the initial value and the steady state value to obtain the steady state duration TssIt was 70 seconds (i.e., 1.12 min).
S103: and calculating the total simulation time length of the control system according to the steady-state time length.
The total simulation duration indicates the total operation time of the control system. And substituting the steady-state duration into a formula (2) to calculate the total simulation duration.
Figure BDA0002861879840000081
In the formula (2), TPIDRepresenting the total duration of the simulation.
It should be noted that, in addition to calculating the total simulation duration, the simulation interval of the control system needs to be calculated, so as to facilitate the subsequent simulation of the control system. In the embodiment of the application, the simulation interval is Ts, and Ts is 0.001TPID。
Specifically, assume an industrial process model of
Figure BDA0002861879840000082
And the step response curve of the industrial process model is shown in figure 1c, and the steady-state duration T is obtained through calculationssSubstituting 70 seconds into the formula (2), and calculating to obtain the total simulation time length TPID780 seconds, the simulation interval Ts is 0.78 seconds.
S104: and calculating the value range of the filter coefficient according to the total simulation duration.
The filter coefficient is a calculation parameter contained in a preset expression, and the preset expression is used for indicating a PID parameter.
It should be noted that, according to the total simulation duration, the value range of the filter coefficient λ obtained by calculation is: lambda is more than or equal to 0.01 and less than or equal to lambdamax1，λmax1The value range of (c) is shown in formula (3).
Figure BDA0002861879840000083
In particular, assume a total simulation duration TPIDAnd 780 seconds, the value range of the filter coefficient lambda is more than or equal to 0.01 and less than or equal to 30.
The so-called filter coefficient is a parameter proposed by the existing inner-mode method. In the internal model method, the whole control system is approximately composed of an equivalent controller (instead of a PID controller) and an industrial process model, the equivalent controller is composed of an internal model controller and an estimation model of the industrial process model, the internal model controller includes a low-pass filter, and therefore, a function of a filter coefficient (i.e., the above-mentioned preset expression) can be used to perform tuning instead of a PID parameter of the PID controller.
The so-called internal model method, i.e. the internal model control strategy, is a novel control strategy for designing a controller based on a process mathematical model in the prior art. The method has the advantages of simple structure, intuitive design, no need of an accurate object model, less online adjustment parameters, easy adjustment and the like. The method has a remarkable effect particularly on the improvement of robustness and anti-interference performance and the control of a large-time-lag system, and provides an effective way for the control of a nonlinear system. The method has good tracking performance and anti-interference capability and certain robustness to model mismatch, so that the method is more and more widely applied to industrial process control.
S105: and selecting n values of the filter coefficient from the value range, substituting the values into a preset expression respectively, and correspondingly calculating to obtain n numerical values of the PID parameter.
The value range of the filter coefficient can be equally divided into n intervals according to a preset value interval, the upper limit value and the lower limit value of each interval are counted to obtain n different values, the n different values are used as n values of the filter coefficient, the n values of the filter coefficient are substituted into a preset expression, and the n values of the PID parameter are correspondingly calculated.
It should be noted that, since the PID parameter includes a proportional coefficient, an integral coefficient, and a differential coefficient, for this reason, n values of the filter coefficient are respectively substituted into a preset expression, and n values of the proportional coefficient, n values of the integral coefficient, and n values of the differential coefficient are obtained through calculation. That is, one value of the PID parameter specifically refers to: a value of the proportionality coefficient, a value of the integral coefficient, and a value of the derivative coefficient.
The so-called preset expression is derived based on the existing inner model method, and the derivation principle is as follows: expressing the scaling coefficients K separately by a function of the filter coefficients λPIntegral coefficient KIAnd a differential coefficient KD。
In the industrial process model of
Figure BDA0002861879840000091
In the case of (2), the preset expression is as shown in formula (4).
Figure BDA0002861879840000092
In the formula (4), the first and second groups,
p(0)＝b；
p′(0)＝a+bτ；
p″(0)＝2(aτ+0.5bτ2)；
q(0)＝λ+τ；
q′(0)＝τλ+0.5τ2；
q″(0)＝τ2λ。
in the industrial process model of
Figure BDA0002861879840000101
In the case of (2), the preset expression is as shown in equation (5).
Figure BDA0002861879840000102
In the formula (5), the first and second groups,
p(0)＝c；
p′(0)＝b+cτ；
p″(0)＝2(a+bτ+0.5cτ2)；
q(0)＝2λ+τ；
q′(0)＝λ2+2τλ+0.5τ2；
q″(0)＝2(τλ2+τ2λ)。
it should be noted that, the derivation process of the preset expression may refer to the steps shown in fig. 2a and the explanation of the steps.
S106: and substituting n numerical values of the PID parameters into the control system respectively, and performing n times of simulation on the control system according to preset simulation conditions to correspondingly obtain n groups of dynamic response data.
The preset simulation conditions comprise: making unit step disturbance on output set value r (T), and making control time T be greater than 0.5 times total simulation time length TPIDIn the case of (2), 1/3 units of amplification disturbance d are added to the output y (t) of the control system. In the embodiment of the application, each set of dynamic response data includes a control quantity u of the control system, an output y of the control system, and an output set value r of the control system.
It should be noted that the control system needs to be simulated once by substituting the respective values of the proportional coefficient, the integral coefficient, and the differential coefficient into the control system.
S107: and substituting the n groups of dynamic response data into a preset performance index function respectively, and correspondingly calculating to obtain n performance evaluation values.
And substituting each group of dynamic response data into a preset performance index function to correspondingly calculate a performance evaluation value, wherein the performance evaluation value is used for indicating the out-of-control probability of the control system. The performance index function includes a calculation formula of a performance index, and the performance index is a combination of an error time integral of the control system, an overshoot factor of an output of the control system, an oscillation factor of an output of the control system, an undersize factor of an output of the control system, and an oscillation factor of a control amount of the control system.
In the embodiment of the present application, the performance indicator function is shown in equation (6).
J＝ITAE·W1·W2·W3·W4 (6)
In the formula (6), J represents a performance evaluation value, ITAE represents an error time integral of a control system, W1Representing the overshoot factor, W, of the output y of the control system2An oscillation factor, W, representing the output y of the control system3Too small a factor, W, representing the output y of the control system4An oscillation factor representing a control quantity u of the control system.
In the formula (6), the first and second groups,
Figure BDA0002861879840000111
Figure BDA0002861879840000112
Figure BDA0002861879840000113
Figure BDA0002861879840000114
Figure BDA0002861879840000115
kmodelrepresenting the steady state gain of the industrial process model.
S108: and counting n performance evaluation values obtained by corresponding calculation based on n values of the filter coefficient, and selecting the performance evaluation value with the minimum value from the n performance evaluation values as a target performance evaluation value.
S109: and taking the value of the filter coefficient corresponding to the target performance evaluation value as a target value under the condition that the target performance evaluation value is smaller than the preset threshold value.
S110: and under the condition that the target performance evaluation value is not smaller than the preset threshold value, repeating the step to obtain a new target performance evaluation value, and taking the value of the filter coefficient corresponding to the new target performance evaluation value as a target value until the new target performance evaluation value is smaller than the preset threshold value.
Wherein, the step includes: adjusting the value range of the filter coefficient according to the value of the filter coefficient corresponding to the target performance evaluation value, so that the value range is reduced; selecting n values of the filter coefficient from the adjusted value range; counting n performance evaluation values obtained by corresponding calculation based on n values; and selecting the performance evaluation value with the minimum value from the n performance evaluation values as a new target performance evaluation value.
The value range of the adjusted filter coefficient lambda is as follows: lambda [ alpha ]min2≤λ≤λmax2，λmin2The value range of (A) is shown in formula (7), λmax2The value range of (c) is shown in formula (8).
λmin2＝max(0.01，λOPT-λmax1/10) (7)
λmax2＝λOPT+λmax1/10 (8)
In the formulae (7) and (8), λOPTRepresenting the target value.
It should be noted that, as can be seen from equations (7) and (8), the value range of the adjusted filter coefficient is obviously reduced compared with the value range of the filter coefficient before adjustment, so as to implement iterative optimization of the filter coefficient.
In the embodiment of the present application, step S110 is to perform iterative optimization on the filter coefficient by using the performance index function, that is, to implement tuning of the filter coefficient. Compared with the prior art, for KP、KIAnd KDThe three parameters are subjected to iterative optimization, and the filter coefficient is only subjected to iterative optimization in the embodiment, so that the consumed computing resources are obviously less, the setting speed is obviously higher, and the requirement on the rapidity control of a control system can be met. In addition, the value range of the filter coefficient is determined in advance based on the total simulation duration, the value range is continuously reduced in the iterative optimization process, and the value of the filter coefficient is determined based on the preset value interval, so that the value of the filter coefficient is faster and more accurate, and the setting efficiency of the filter coefficient is further improved.
Specifically, the execution steps are repeated for 4 times to obtain 44 values of the filter coefficient, and the target value meeting the preset condition is lambdaOPT2.89, the preset conditions are as follows: taking value lambda based on targetOPTThe calculated performance evaluation value is less than the preset threshold value corresponding to 2.89. In addition, for 4 times of simulation process of the control system, the control effect variation curve of the control system is shown in fig. 1 d.
It should be noted that the above specific implementation process is only for illustration.
S111: substituting the target value into a preset expression, and calculating to obtain a setting value of the PID parameter.
In the iterative optimization process of the filter coefficient, factors capable of reflecting the out-of-control of the control system (including error time integral of the control system, overshoot factor of output of the control system, oscillation factor of output of the control system, undersize factor of output of the control system and oscillation factor of control quantity of the control system) are included in the performance index function, effective performance indexes are provided for calculating the out-of-control probability of the control system, the PID parameters are adjusted (namely the filter coefficient is adjusted) according to the performance indexes, and the control requirements of rapidity and stability of the control system can be met.
Specifically, the target value is lambdaOPTSubstituting the value of 2.89 into a preset expression, and calculating the setting value K of the PID parameterP＝0.801，KI＝0.0634，KD2.115. In addition, referring to fig. 1e, the setting values of the PID parameters obtained based on the present embodiment are substituted into the control system to obtain a control effect curve of the control system (i.e., "J" line shown in fig. 1 e), and the setting values of the PID parameters obtained by the prior art setting are substituted into the control system to obtain a control effect curve of the control system (i.e., "ITAE" line and "ISE" line shown in fig. 1 e). Obviously, the fluctuation range of the control effect curve obtained in the prior art is far higher than that of the control effect curve obtained in the embodiment, so that the setting effect of the embodiment on the PID parameters can be proved to be superior to that of the prior art.
In summary, the PID parameters are indicated by using the preset expression, only iterative optimization is needed to be performed on the unique filter coefficients, and the value range of the filter coefficients is predetermined based on the total simulation duration. In addition, the performance evaluation value is calculated by adopting the performance index and the performance index function, the filter coefficient is set according to the performance evaluation value, the setting value of the PID parameter is ensured to be finally calculated, the out-of-control probability of the control system can be smaller than a preset threshold value, and therefore the stability of the control system is improved. Therefore, the method of the embodiment is used for setting the PID parameters, so that the control performance of the PID controller can be improved, and the control requirements of the control system on rapidity and stability can be met.
As shown in FIG. 2a, the industrial process model is used as
Figure BDA0002861879840000141
For example, a schematic diagram of a derivation process of a preset expression provided in an embodiment of the present application includes the following steps:
s201: hysteresis loop e for industrial process models-τsAn all-pole approximation is performed.
Wherein, a hysteresis loop section e-τsThe all-pole approximation process of (a) is shown in equation (9).
Figure BDA0002861879840000142
S202: and decomposing the industrial process model to obtain a first model and a second model.
The process of decomposing the industrial process model is shown in the formulas (10) and (11).
Figure BDA0002861879840000143
Figure BDA0002861879840000144
In the formulae (10) and (11), G+(s) represents a first model, G-(s) represents a second model.
S203: and constructing a control system based on the internal model controller, the first model and the second model.
Wherein, based on the internal model controller, the first model and the second model, the structure of the constructed control system can be seen as shown in fig. 2b, "internal model G" represents the first model
Figure BDA0002861879840000145
"represents the second model.
In the embodiment of the present application, the expression of the internal model controller is shown in equation (12).
Figure BDA0002861879840000146
In equation (12), C is the internal model controller, the function f(s) can be understood as a low pass filter, and the expression of the function f(s) is shown in equation (13).
Figure BDA0002861879840000147
In order to make the internal model controller reasonable and practical, the order n in the formula (13) should be the maximum value, that is, n is 1. For this reason, the expression of the function f(s) can be as shown in equation (14).
f(s)＝1/(λs+1) (14)
S204: and forming the inner model controller and the second model into an equivalent controller.
Wherein, the expression of the equivalent controller is shown as formula (15).
Figure BDA0002861879840000151
In equation (15), K represents a control parameter of an equivalent controller (i.e., a so-called PID parameter).
It should be noted that, after the internal model controller and the second model are combined into an equivalent controller, the structure of the control system may be changed accordingly, and specifically, the changed structure may be shown in fig. 2 c.
S205: carrying out Meglalin expansion on s in the formula (15) to obtain a proportionality coefficient KPIntegral coefficient KIAnd a differential coefficient KDThe respective expression.
Wherein, the specific process of the mculing expansion is performed on s in the formula (15), as shown in the formula (16).
Figure BDA0002861879840000152
In the formula (16), KP＝Q′(0)，KI＝Q-1(0)，KD＝Q″(0)/2。
For the convenience of calculation, equation (16) is transformed into equation (17).
Figure BDA0002861879840000153
In the formula (17), the reaction mixture,
p(s)＝0.5τ2s3+(aτ+0.5bτ2)s2+(a+bτ)s+b；
q(s)＝0.5τ2λs2+(τλ+0.5τ2)s+(λ+τ)。
to pair
Figure BDA0002861879840000154
And (3) carrying out derivation to obtain:
Figure BDA0002861879840000155
Figure BDA0002861879840000156
Figure BDA0002861879840000157
in summary, the preset expression can be derived and obtained effectively by using the process described in this embodiment.
It should be noted that the embodiments shown in fig. 1a and fig. 2a are optional implementations of the PID parameter tuning method described in the present application. For this reason, the flow mentioned in the above embodiment can be summarized as the method shown in fig. 3.
As shown in fig. 3, a schematic diagram of another PID parameter tuning method provided in the embodiment of the present application includes the following steps:
s301: and calculating the total simulation time length of the control system based on the industrial process model.
The industrial process model is used for indicating a control object of the PID controller, and the control system is constructed based on the PID controller and the industrial process model.
S302: and determining the value range of the filter coefficient according to the total simulation time length.
The filter coefficient is a calculation parameter included in a preset expression. The preset expression is used to indicate PID parameters.
S303: and selecting the value of the filter coefficient from the value range, substituting the value into a preset expression, and calculating to obtain the numerical value of the PID parameter.
S304: and simulating the control system based on the numerical value of the PID parameter to obtain dynamic response data.
S305: and substituting the dynamic response data into a preset performance index function, and calculating to obtain a performance evaluation value.
Wherein the performance assessment value is indicative of a probability of runaway of the control system.
S306: a target value is selected from a plurality of values of the filter coefficient.
Wherein, the target value is a value meeting a preset condition, and the preset condition is as follows: and the performance evaluation value obtained by corresponding calculation based on the value is smaller than a preset threshold value.
S307: substituting the target value into a preset expression, and calculating to obtain a setting value of the PID parameter.
In summary, the PID parameters are indicated by using the preset expression, only iterative optimization is needed to be performed on the unique filter coefficients, and the value range of the filter coefficients is predetermined based on the total simulation duration. In addition, the performance evaluation value is calculated by adopting the performance index and the performance index function, the filter coefficient is set according to the performance evaluation value, the setting value of the PID parameter is ensured to be finally calculated, the out-of-control probability of the control system can be smaller than a preset threshold value, and therefore the stability of the control system is improved. Therefore, the method of the embodiment is used for setting the PID parameters, so that the control performance of the PID controller can be improved, and the control requirements of the control system on rapidity and stability can be met.
Corresponding to the PID parameter tuning method mentioned in the above embodiment, the present application also provides a PID parameter tuning device.
As shown in fig. 4, a schematic structural diagram of a PID parameter tuning apparatus provided in an embodiment of the present application includes:
the first calculation unit 100 is configured to calculate a total simulation duration of the control system based on the industrial process model. The industrial process model is used for indicating a control object of the PID controller, and the control system is constructed based on the PID controller and the industrial process model.
The first computing unit 100 is specifically configured to: simulating the industrial process model to obtain an initial value and a steady-state value of the step response of the industrial process model; calculating the time difference between the initial value and the steady-state value to obtain the steady-state duration; and calculating the total simulation time length of the control system according to the steady-state time length.
And a duration determining unit 200, configured to determine a value range of a filter coefficient according to the total simulation duration, where the filter coefficient is a calculation parameter included in a preset expression, and the preset expression is used to indicate a PID parameter.
And a second calculating unit 300, configured to select a value of the filter coefficient from the value range, and substitute the value into the preset expression to calculate a value of the PID parameter.
The second computing unit 300 is specifically configured to: dividing the value range of the filter coefficient into n intervals according to a preset value interval, wherein n is a positive integer; counting the upper limit value and the lower limit value of each interval to obtain n different numerical values; taking n different numerical values as n values of the filter coefficient; and substituting the n values of the filter coefficient into a preset expression respectively, and correspondingly calculating to obtain n numerical values of the PID parameter.
And the simulation unit 400 is used for simulating the control system based on the numerical value of the PID parameter to obtain dynamic response data.
The simulation unit 400 is specifically configured to: respectively substituting n numerical values of the PID parameters into the control system, and simulating the control system according to preset simulation conditions to obtain n groups of dynamic response data; wherein n is a positive integer, and the preset simulation conditions are as follows: and (3) unit step disturbance is carried out on the output set value of the control system, and 1/3 unit amplification interference is added to the output of the control system under the condition that the control time is more than 0.5 time of the total simulation time.
And a third calculating unit 500, configured to substitute the dynamic response data into a preset performance index function, and calculate a performance evaluation value. The performance estimates are used to indicate a probability of runaway of the control system.
The performance index function comprises a calculation formula of a performance index, wherein the performance index is the combination of an error time integral of the control system, an overshoot factor of the output of the control system, an oscillation factor of the output of the control system, an undersize factor of the output of the control system and an oscillation factor of a control quantity of the control system.
A selecting unit 600 is configured to select a target value from a plurality of values of the filter coefficient. Wherein the target value is a value satisfying a preset condition. The preset conditions are as follows: and the performance evaluation value obtained by corresponding calculation based on the value is smaller than a preset threshold value.
Wherein, the selecting unit 600 is specifically configured to: selecting n values of the filter coefficient from the value range, wherein n is a positive integer; counting n performance evaluation values obtained by corresponding calculation based on n values; selecting a performance evaluation value with the minimum value from the n performance evaluation values as a target performance evaluation value; and taking the value of the filter coefficient corresponding to the target performance evaluation value as a target value under the condition that the target performance evaluation value is smaller than the preset threshold value.
The selecting unit 600 is further configured to: and under the condition that the target performance evaluation value is not smaller than the preset threshold value, repeating the step to obtain a new target performance evaluation value, and taking the value of the filter coefficient corresponding to the new target performance evaluation value as a target value until the new target performance evaluation value is smaller than the preset threshold value. Wherein, the step includes: adjusting the value range of the filter coefficient according to the value of the filter coefficient corresponding to the target performance evaluation value, so that the value range is reduced; selecting n values of the filter coefficient from the adjusted value range; counting n performance evaluation values obtained by corresponding calculation based on n values; and selecting the performance evaluation value with the minimum value from the n performance evaluation values as a new target performance evaluation value.
And a fourth calculating unit 700, configured to substitute the target value into a preset expression, and calculate a setting value of the PID parameter.
In summary, the PID parameters are indicated by using the preset expression, only iterative optimization is needed to be performed on the unique filter coefficients, and the value range of the filter coefficients is predetermined based on the total simulation duration. In addition, the performance evaluation value is calculated by adopting the performance index and the performance index function, the filter coefficient is set according to the performance evaluation value, the setting value of the PID parameter is ensured to be finally calculated, the out-of-control probability of the control system can be smaller than a preset threshold value, and therefore the stability of the control system is improved. Therefore, the method of the embodiment is used for setting the PID parameters, so that the control performance of the PID controller can be improved, and the control requirements of the control system on rapidity and stability can be met.
The present application further provides a computer-readable storage medium comprising a stored program, wherein the program performs the PID parameter tuning method provided herein.
The application also provides a PID parameter setting device, which comprises: a processor, a memory, and a bus. The processor is connected with the memory through a bus, the memory is used for storing programs, the processor is used for running the programs, and the program runs to execute the PID parameter setting method provided by the application, and the method comprises the following steps:
calculating the total simulation duration of the control system based on the industrial process model; the industrial process model is used for indicating a control object of a PID controller, and the control system is constructed based on the PID controller and the industrial process model;
determining the value range of the filter coefficient according to the total simulation duration; the filter coefficient is a calculation parameter contained in a preset expression; the preset expression is used for indicating PID parameters;
selecting the value of the filter coefficient from the value range, substituting the value into the preset expression, and calculating to obtain the numerical value of the PID parameter;
simulating the control system based on the numerical value of the PID parameter to obtain dynamic response data;
substituting the dynamic response data into a preset performance index function, and calculating to obtain a performance evaluation value; the performance evaluation value is used for indicating the out-of-control probability of the control system;
selecting a target value from a plurality of values of the filter coefficient; wherein the target value is a value satisfying a preset condition; the preset conditions are as follows: the performance evaluation value obtained by corresponding calculation based on the value is smaller than a preset threshold value;
substituting the target value into the preset expression, and calculating to obtain the setting value of the PID parameter.
Optionally, the calculating a total simulation duration of the control system based on the industrial process model includes:
simulating the industrial process model to obtain a starting value and a steady-state value of the step response of the industrial process model;
calculating the time difference between the initial value and the steady-state value to obtain steady-state duration;
and calculating the total simulation time length of the control system according to the steady-state time length.
Optionally, the selecting a value of the filter coefficient from the value range, substituting the value into the preset expression, and calculating to obtain a value of the PID parameter includes:
dividing the value range of the filter coefficient into n intervals according to a preset value interval; n is a positive integer;
counting the upper limit value and the lower limit value of each interval to obtain n different numerical values;
taking the n different numerical values as n values of the filter coefficient;
and substituting the n values of the filter coefficient into the preset expression respectively, and correspondingly calculating to obtain n numerical values of the PID parameter.
Optionally, the simulating the control system based on the value of the PID parameter to obtain dynamic response data includes:
respectively substituting the n numerical values of the PID parameters into the control system, and simulating the control system according to preset simulation conditions to obtain n groups of dynamic response data; wherein n is a positive integer, and the preset simulation conditions are as follows: and performing unit step disturbance on an output set value of the control system, and increasing 1/3 units of amplification interference on the output of the control system under the condition that the control time is more than 0.5 time of the total simulation time.
Optionally, selecting a target value from the plurality of values of the filter coefficient includes:
selecting n values of the filter coefficient from the value range, wherein n is a positive integer;
counting n performance evaluation values obtained by corresponding calculation based on the n values;
selecting the performance evaluation value with the minimum value from the n performance evaluation values as a target performance evaluation value;
and taking the value of the filter coefficient corresponding to the target performance evaluation value as a target value under the condition that the target performance evaluation value is determined to be smaller than the preset threshold value.
Optionally, the method further includes:
under the condition that the target performance evaluation value is determined to be not smaller than the preset threshold value, repeating the step to obtain a new target performance evaluation value, and taking the value of the filter coefficient corresponding to the new target performance evaluation value as the target value until the new target performance evaluation value is smaller than the preset threshold value;
wherein the steps include:
adjusting the value range of the filter coefficient according to the value of the filter coefficient corresponding to the target performance evaluation value, so that the value range is reduced;
selecting n values of the filter coefficient from the adjusted value range;
counting n performance evaluation values obtained by corresponding calculation based on the n values;
and selecting the performance evaluation value with the minimum value from the n performance evaluation values as a new target performance evaluation value.
Optionally, the performance indicator function includes a calculation formula of a performance indicator, where the performance indicator is a combination of an error time integral of the control system, an overshoot factor of an output of the control system, an oscillation factor of an output of the control system, an undershoot factor of an output of the control system, and an oscillation factor of a controlled variable of the control system.
The functions described in the method of the embodiment of the present application, if implemented in the form of software functional units and sold or used as independent products, may be stored in a storage medium readable by a computing device. Based on such understanding, part of the contribution to the prior art of the embodiments of the present application or part of the technical solution may be embodied in the form of a software product stored in a storage medium and including several instructions for causing a computing device (which may be a personal computer, a server, a mobile computing device or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. A PID parameter tuning method is characterized by comprising the following steps:
calculating the total simulation duration of the control system based on the industrial process model; the industrial process model is used for indicating a control object of a PID controller, and the control system is constructed based on the PID controller and the industrial process model;
determining the value range of the filter coefficient according to the total simulation duration; the filter coefficient is a calculation parameter contained in a preset expression; the preset expression is used for indicating PID parameters;
selecting the value of the filter coefficient from the value range, substituting the value into the preset expression, and calculating to obtain the numerical value of the PID parameter;
simulating the control system based on the numerical value of the PID parameter to obtain dynamic response data;
substituting the dynamic response data into a preset performance index function, and calculating to obtain a performance evaluation value; the performance evaluation value is used for indicating the out-of-control probability of the control system;
selecting a target value from a plurality of values of the filter coefficient; wherein the target value is a value satisfying a preset condition; the preset conditions are as follows: the performance evaluation value obtained by corresponding calculation based on the value is smaller than a preset threshold value;
substituting the target value into the preset expression, and calculating to obtain the setting value of the PID parameter.
2. The method of claim 1, wherein calculating a total simulation duration for the control system based on the industrial process model comprises:
simulating the industrial process model to obtain a starting value and a steady-state value of the step response of the industrial process model;
calculating the time difference between the initial value and the steady-state value to obtain steady-state duration;
and calculating the total simulation time length of the control system according to the steady-state time length.
3. The method according to claim 1, wherein the selecting a value of the filter coefficient from the value range, substituting the value into the preset expression, and calculating the value of the PID parameter comprises:
dividing the value range of the filter coefficient into n intervals according to a preset value interval; n is a positive integer;
counting the upper limit value and the lower limit value of each interval to obtain n different numerical values;
taking the n different numerical values as n values of the filter coefficient;
and substituting the n values of the filter coefficient into the preset expression respectively, and correspondingly calculating to obtain n numerical values of the PID parameter.
4. The method of claim 1, wherein simulating the control system based on the values of the PID parameters to obtain dynamic response data comprises:
respectively substituting n numerical values of the PID parameters into the control system, and carrying out n times of simulation on the control system according to preset simulation conditions to obtain n groups of dynamic response data; wherein n is a positive integer, and the preset simulation conditions are as follows: and performing unit step disturbance on an output set value of the control system, and increasing 1/3 units of amplification interference on the output of the control system under the condition that the control time is more than 0.5 time of the total simulation time.
5. The method of claim 1, wherein said selecting a target value from a plurality of said values of said filter coefficients comprises:
selecting n values of the filter coefficient from the value range, wherein n is a positive integer;
counting n performance evaluation values obtained by corresponding calculation based on the n values;
selecting the performance evaluation value with the minimum value from the n performance evaluation values as a target performance evaluation value;
and taking the value of the filter coefficient corresponding to the target performance evaluation value as a target value under the condition that the target performance evaluation value is determined to be smaller than the preset threshold value.
6. The method of claim 5, further comprising:
under the condition that the target performance evaluation value is determined to be not smaller than the preset threshold value, repeating the step to obtain a new target performance evaluation value, and taking the value of the filter coefficient corresponding to the new target performance evaluation value as the target value until the new target performance evaluation value is smaller than the preset threshold value;
wherein the steps include:
adjusting the value range of the filter coefficient according to the value of the filter coefficient corresponding to the target performance evaluation value, so that the value range is reduced;
selecting n values of the filter coefficient from the adjusted value range;
counting n performance evaluation values obtained by corresponding calculation based on the n values;
and selecting the performance evaluation value with the minimum value from the n performance evaluation values as a new target performance evaluation value.
7. The method of claim 1, wherein the performance indicator function comprises a calculation formula of a performance indicator, the performance indicator being a combination of an error time integral of the control system, an overshoot factor of an output of the control system, an oscillation factor of an output of the control system, an undershoot factor of an output of the control system, and an oscillation factor of a controlled quantity of the control system.
8. A PID parameter tuning device characterized by comprising:
the first calculation unit is used for calculating the total simulation duration of the control system based on the industrial process model; the industrial process model is used for indicating a control object of a PID controller, and the control system is constructed based on the PID controller and the industrial process model;
the time length determining unit is used for determining the value range of the filter coefficient according to the total simulation time length; the filter coefficient is a calculation parameter contained in a preset expression; the preset expression is used for indicating PID parameters;
the second calculation unit is used for selecting the value of the filter coefficient from the value range, substituting the value into the preset expression and calculating to obtain the numerical value of the PID parameter;
the simulation unit is used for simulating the control system based on the numerical value of the PID parameter to obtain dynamic response data;
the third calculating unit is used for substituting the dynamic response data into a preset performance index function to calculate a performance evaluation value; the performance evaluation value is used for indicating the out-of-control probability of the control system;
a selecting unit configured to select a target value from the plurality of values of the filter coefficient; wherein the target value is a value satisfying a preset condition; the preset conditions are as follows: the performance evaluation value obtained by corresponding calculation based on the value is smaller than a preset threshold value;
and the fourth calculation unit is used for substituting the target value into the preset expression to calculate the setting value of the PID parameter.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored program, wherein the program performs the PID parameter tuning method of any one of claims 1 to 7.
10. A PID parameter tuning apparatus, characterized by comprising: a processor, a memory, and a bus; the processor and the memory are connected through the bus;
the memory is used for storing a program, and the processor is used for running the program, wherein the program runs to execute the PID parameter tuning method of any one of claims 1-7.
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