CN113126480A - Universal PID parameter setting method - Google Patents

Universal PID parameter setting method Download PDF

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CN113126480A
CN113126480A CN202110600972.4A CN202110600972A CN113126480A CN 113126480 A CN113126480 A CN 113126480A CN 202110600972 A CN202110600972 A CN 202110600972A CN 113126480 A CN113126480 A CN 113126480A
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curve
pid parameter
controller
acceleration curve
coordinate system
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王飚
武飞
崔冰晶
柯吉
林少军
赵微微
霍梁
杨雨仪
马雨庆
董伊媚
唐必成
赵醒
秦裕德
吴浩
杨航
陈东瑞
吕亚泽
郑乐
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Changan University
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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.

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Abstract

The invention discloses a universal PID parameter setting method, a universal PID parameter setting device, universal PID parameter setting equipment and universal PID parameter setting media. The method is simple and convenient, does not need to consume much time, is suitable for various crowds, does not need a parameter setting method with rich engineering experience, and realizes a better control effect with less time and personnel cost.

Description

Universal PID parameter setting method
Technical Field
The invention belongs to the technical field of industrial control, and particularly relates to a universal PID parameter setting method.
Background
A proportional-Integral-Differential (PID) controller is a feedback loop component commonly used in industrial control applications, and is composed of a proportional unit P, an Integral unit I, and a Differential unit D. The basis of PID control is proportional control; 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 application, PID parameter setting is needed to obtain a PID setting parameter, and the PID controller controls the controlled object to operate by using the PID setting parameter.
The traditional PID control mode is the control mode which has the longest existence time at present. Although many advanced control methods are available, most of the control methods in the control loop are PID control, and many advanced controls are based on PID control, because of the advantages of simple PID control principle, convenient use, strong robustness and the like. And the parameter setting of the PID controller is the core content of the control system design. It determines the proportional coefficient, integral time and differential time of PID controller according to the controlled process characteristic.
One of the existing PID control modes is a theoretical calculation and calibration method, which is mainly used for determining controller parameters through theoretical calculation according to a mathematical model of a system. The calculation data obtained by the method can not be directly used, and must be adjusted and modified through engineering practice, so that the method is very complex, and the theoretical calculation result needs to be modified, so that the method is not convenient enough. The other is an engineering setting method, which mainly depends on engineering experience and is directly carried out in the test of a control system, specifically, a critical proportion method, an attenuation curve method and an experience method are mainly adopted. Requires a certain amount of experience and is time-consuming. And thirdly, PID self-tuning control based on a genetic algorithm. The algorithm is a modified version of the genetic algorithm, and the algorithm is applied to the principle similar to the genetic algorithm and iterated continuously until acceptable parameters appear. However, this method takes a long time to reach a steady state, and is not fast.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a universal PID parameter setting method to solve the problems of a plurality of parameter setting methods in the prior art but more defects.
In order to achieve the purpose, the invention adopts the following technical scheme to realize the purpose:
a universal PID parameter setting method comprises the following steps:
step 1, acquiring an acceleration curve of a controlled object;
step 2, selecting a reference object curve from a standard library, wherein the similarity between the reference object curve and an acceleration curve of a controlled object is highest;
and 3, adjusting the acceleration curve of the controlled object by a zooming method, and overlapping the adjusted acceleration curve with the reference object curve to obtain the set PID parameter.
The invention is further improved in that:
preferably, in step 1, the acceleration curve is obtained by recording the actual object test procedure, or from a known transfer function.
Preferably, the determining process with the highest similarity is as follows: if the transfer function exists, selecting a reference object curve in the standard library through the transfer function; otherwise, the reference object curve is determined in the standard library by whether overshoot is present, the size of the overshoot, or the adjustment time.
Preferably, in step 3, the scaling process includes compressing the height of the acceleration curve and compressing the length of the acceleration curve.
Preferably, the scaling factor is obtained by the length of the compression or extension acceleration curve
Figure BDA0003092676700000021
And
Figure BDA0003092676700000022
preferably, the relation between the scale factor and the coordinate system is as follows:
Figure BDA0003092676700000023
wherein the content of the first and second substances,
Figure BDA0003092676700000031
representing an artificial coordinate system, (t, x) representing a real coordinate system,
preferably, the PID parameter comprises a proportionality coefficient K of the controllerPIntegral coefficient T of controllerIAnd the differential coefficient T of the controllerD。
Preferably, the calculation process of the PID parameters is as follows:
Figure BDA0003092676700000032
wherein the content of the first and second substances,
Figure BDA0003092676700000033
representing the controller input in the manual coordinate system,
Figure BDA0003092676700000034
the scaling factor is indicative of the controller's scaling factor,
Figure BDA0003092676700000035
which represents the integral coefficient of the controller,
Figure BDA0003092676700000036
representing the derivative coefficient of the controller.
Compared with the prior art, the invention has the following beneficial effects:
the invention discloses a universal PID parameter setting method, which comprises the steps of comparing an obtained acceleration curve of a controlled object with a reference object curve, adjusting the length and the height of the acceleration curve of the controlled object by the acceleration curve of the controlled object through a zooming method, enabling the adjusted acceleration curve of the controlled object to be superposed with the reference object curve, and simultaneously obtaining a scale factor of the acceleration curve and the reference object curve, wherein the scale factor is a PID parameter after setting. The method is simple and convenient, does not need to consume much time, is suitable for various crowds, does not need a parameter setting method with rich engineering experience, and realizes a better control effect with less time and personnel cost.
Drawings
FIG. 1 is a diagram of data to be used;
FIG. 2 is an input diagram of an acceleration curve
FIG. 3 is a database interface diagram;
FIG. 4 is an initial graph of a controlled object and a reference object;
FIG. 5 is a combined view of a curve process of a controlled object and a reference control object;
fig. 6 is a graph of the control object and the reference curve with n-4;
FIG. 7 is a combined view of a controlled object and a reference controlled object;
FIG. 8 is a diagram showing the result of PID control parameters controlling the controlled object;
FIG. 9 is a view of the scaling processing of embodiment 2;
FIG. 10 is a simulation diagram of a vector switching time distribution unit of embodiment 2;
FIG. 11 is a sector vector switching point of embodiment 2;
FIG. 12 is a PWM generation diagram of the generation of embodiment 2;
FIG. 13 is a graph of the output of the PWM of embodiment 2;
fig. 14 is a servo motor dynamic curve of embodiment 2.
Detailed Description
The invention is described in further detail below with reference to the accompanying drawings:
in the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention; the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance; furthermore, unless expressly stated or limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly and encompass, for example, both fixed and removable connections; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
The main principle of the invention is as follows: tuning of PID parameters is achieved using scaling methods, which are mainly characterized by using data known under a nominal model, which is a highly calibrated system, to calculate the controller parameters required in the operating system, and this is considered as a standard system. The advantage of this algorithm is to reduce the time cost spent in the actual tuning process of the regulator and to ensure a high quality operation of the closed loop control system.
It is well known that many control objects of the same type have qualitatively similar response forms to the same input, with differences mainly manifested in the scale of the reaction, depending on the values of the parameters in the object transfer function. If the response map of one object is squeezed/stretched along the coordinate axes, it can be superimposed with the response map of another object with high accuracy. However, if a compression/stretching operation is performed, it is also necessary to convert it into another (manual) coordinate system, which is associated with the original (actual) coordinates by a simple linear relationship, as shown in equation (1):
Figure BDA0003092676700000051
in the above formula, the first and second carbon atoms are,
Figure BDA0003092676700000052
representing an artificial coordinate system, (t, x) representing a real coordinate system,
Figure BDA0003092676700000053
representing a scale factor. When the zooming method is operated, the zooming method uses the acceleration curves of the controlled object and the standard control object. The first step of the scaling method is to convert the acceleration curve of the working object from the actual coordinate system to the artificial coordinate system, and the second step is to find the scale factor at which the response of the controlled object (acceleration curve) in the artificial coordinate system is as close as possible to the similar response of the individual control objects of the reference system (reference acceleration curve). The response curve in the artificial coordinate system will be similar to that in the reference system, but there is a problem that,the work controller adjustment parameters are only valid in the artificial coordinate system and cannot act on the actual coordinate system. Therefore, the work data must be finally returned to the actual coordinate system by the scaling method.
The mathematical description of the operating PID controller in artificial coordinates is as follows:
Figure BDA0003092676700000054
in the formula (2), the first and second groups,
Figure BDA0003092676700000061
represents the output of the controller in the artificial coordinate system,
Figure BDA0003092676700000062
representing the controller input in the manual coordinate system,
Figure BDA0003092676700000063
the scaling factor is indicative of the controller's scaling factor,
Figure BDA0003092676700000064
which represents the integral coefficient of the controller,
Figure BDA0003092676700000065
representing the derivative coefficient of the controller.
Substituting equation (1) into equation (2) translates the mathematical description of the controller to the actual coordinate system:
Figure BDA0003092676700000066
in formula (3), y (t) represents the output of the controller in the actual coordinate system, and x represents the input of the controller in the actual coordinate system.
The adjustment parameters required in the actual coordinate system are usually contained in a conventional mathematical description:
Figure BDA0003092676700000067
in equation (4), y (t) represents the output of the controller, x represents the controller input, KPIndicating the scaling factor, T, of the controllerIRepresenting the integral coefficient, T, of the controllerDRepresenting the derivative coefficient of the controller.
If equations (3) and (4) represent the same controller, then the corresponding coefficients are the same:
Figure BDA0003092676700000068
from equation (5) above, the scaling settings for the operating PID controller can be calculated and converted to control parameters in the actual coordinate system (t, x):
Figure BDA0003092676700000069
Figure BDA0003092676700000071
the invention realizes the process of setting PID parameters by using a zooming method through an upper computer, and the process is specifically divided into a plurality of steps introduced below.
The first step is to prepare data, the upper computer needs data about the acceleration curve (transient response) of the controlled object, which can be obtained by testing and recording the acceleration curve on the actual object or by calculating from the known transfer function, and the data is to be processed.
The second step is to input the data on the constructed acceleration curve to the upper computer, as shown in fig. 2 below.
The third step is to select a reference system library, open the "tunable controller type" section, and select the appropriate reference system library from the list. In the case of tuning a classical PID controller, a base library of PID criteria is selected. A table such as that shown in fig. 3 may appear with different curves for each row, with the one selected having the reference object curve most similar to the controlled object curve. The highest similarity is judged according to specific parameters, and for different controlled objects, different parameters are involved, such as the overshoot of transient response, the adjustment time and other index measures. More specifically, if a transfer function exists, a curve with similar links in the standard library can be selected according to the links of the transfer function. If no transfer function exists or a transfer function exists and after the first step, a similar curve is preliminarily selected, the curve similarity can be determined according to whether overshoot exists or not, the overshoot amount or the adjustment time and other parameters.
The fourth step is to perform a specific zooming process, the initial curves of the controlled object and the reference control object are shown in fig. 4, the two curves are different, but the two lines have very obvious similarity in form, when the zooming process is performed, the curve of the controlled object is compressed and deformed on the ordinate axis by pressing the "down" key, and the curve is slightly extended along the abscissa by pressing the "right" key. Changing the scaling factor with a fixing step, the fixing step being: according to the actual situation of the curve, the left key or the right key and the up key or the down key are selected to enable the two curves to be as close as possible and repeat continuously, so that a more accurate scale factor is obtained. In this case, the acceleration profile of the work object moves smoothly along the coordinate plane, approaching the reference profile. The most accurate visual coincidence of the resulting curves is shown in fig. 4, resulting in a value for the scale factor. After the scale factor is obtained, and the parameter required by the PID controller is displayed on the interface after a parameter calculation button is clicked, the parameter at the moment can be better used in most working environments, and the use time is very short. For more experienced engineers, it is found that the s-shape of the acceleration curve of the reference object is more pronounced than that of the work object, which means that a reference object of a smaller order may be more suitable for the work object, and thus a system of control objects with n-4 may be selected in the reference library. As shown in fig. 5, the curves of the reference control object and the work object appear on one coordinate plane. The result of scaling adjustment is shown in fig. 7, and at this time, the curve overlap ratio is higher, so that a better control effect can be obtained.
The first step is as follows: data preparation
Data about the servo motors are prepared in a custom system, and for information about the servo motors, the program requires data about its acceleration profile (transient response). They can be obtained by experimentally recording an acceleration curve on an actual object or by calculation from a transfer function of the following formula (7), and when a calculation method is used, "Mathcad" can be used to calculate the acceleration curve. For clarity, the present invention constructs an acceleration curve in Excel, as shown in FIG. 1 below.
The transfer function has the following form:
Figure BDA0003092676700000081
the second step is that: data entry
And then, inputting the data on the constructed acceleration curve to an upper computer. At this time, a curve as shown in fig. 2 can be seen.
The third step: selecting a library of reference systems
The "tunable controller type" section is opened and the appropriate reference system library is selected from the list. In the case of tuning a classical PID controller, a base library of PID criteria is selected. A table such as that shown in fig. 3 may appear with different curves for each row, with the one selected having the reference object curve most similar to the controlled object curve.
The fourth step: selecting a reference object curve
In the present embodiment, objects having the same n (transfer function order) and r (transfer function integral element number) are considered to be objects of the same type. From the known transfer function formula (7), n is 5 and r is 0. In column 2 (n) and column 3 (r) of the table, the corresponding object curve with n equal to 5 and r equal to 0 is found, as shown in fig. 4.
The fifth step: scaling procedure
The initial graphs of the controlled object and the reference control object are clearly visible in fig. 4. As can be seen from fig. 4, the two curves are different, but the two lines have a very clear similarity in form. During zooming, pressing down key to control the compression deformation of the ordinate axisThe curve of the object, pressing the "right" key, stretches slightly along the abscissa. Changing the scale factor in fixed steps
Figure BDA0003092676700000091
In this case, the acceleration profile of the work object moves smoothly along the coordinate plane, approaching the reference profile. The most accurate visual coincidence of the resulting curves is shown in fig. 5. The following scale factor values were obtained:
Figure BDA0003092676700000092
after clicking the 'parameter calculation' button, the interface displays the parameters required by the PID controller: kp＝0.725；Ti＝21.7；Td7.23. Experience with scaling methods has shown that generally a better matching of the acceleration curves of the work and reference control object can be achieved. If we now look at fig. 5 again, we find that the s-shape of the acceleration curve of the reference object is more pronounced than that of the work object, which indicates that a smaller order reference object may be more suitable for the work object, and so we can select a system of control objects with n-4 in the reference library. As in fig. 6, the curves of the reference control object and the work object appear on one coordinate plane. As shown in fig. 6, the initial curves do not match, and therefore a scaling process is performed to combine the curves together. The results are shown in FIG. 7.
As can be seen from fig. 7, the accuracy of curve superimposition is high. The interface can see a steady state value of the scale factor,
Figure BDA0003092676700000093
and sending a command of 'parameter calculation', obtaining PID controller parameters: kp＝1.07；Ti＝24.2；Td＝7.1。
This is the way the scaling method works when a high accuracy of visual coincidence of the acceleration curves of the reference and working control objects is achieved. It is particularly important for practical application of the scaling method that it is able to provide the available PID settings even with a relatively low accuracy of the combination of acceleration curves achieved during the scaling process.
And finally, setting the obtained PID parameters to control the motor, wherein the control result is shown in figure 8.
Example 2 a simulation example was put into a motor for verification.
When case verification is carried out, the control of the Mochuan servo motor is mainly realized, and the control strategy is SVPWM control. In the debugging process of the control system, an oscilloscope and a universal meter are mainly used as instruments. The experiment also uses a multifunctional serial port debugging assistant to assist in debugging. The software used was mainly Quartus II 13.1 and Keil uVision 5.
In the experimental test, the model of the motor is TS4607N2190E200, and the specific parameters are shown in table 1 below
TABLE 1 Servo-motor parameter table
Figure BDA0003092676700000101
The controlled object in the test control hardware object is a servo motor, and the servo motor is connected with an upper computer.
The experiment is based on servo motor vector control as a theoretical basis, and adopts a motor control mode as SVPWM control. The specific experimental process is as follows:
1. adjustment by zooming
After the scaling process, as shown in FIG. 9, K is obtainedp＝28.2，Ti＝1.25，Td＝8.00。
SVPWM Generation
SVPWM- -space vector pulse width modulation technique is to control the flux space vector of an AC motor to approximate a circle to produce a constant torque. The device mainly comprises a vector switch time distribution unit, a sector vector switching point unit, a PWM wave generation unit and the like. The specific model sim simulation diagram is as follows:
(1) a simulation diagram of a vector switching time allocation unit is shown in fig. 10. According to Uα，UβAnd calculating the action time tm, tn of the voltage vector corresponding to the sector.
(2) A sector vector switch point unit simulation diagram is shown in fig. 11. The switching points are Tcm1, Tcm2, Tcm 3.
(3) A simulation diagram of a unit generating a PWM wave is shown in fig. 12.
PWM wave output situation is shown in FIG. 13
4. Dynamic curve of motor rotation speed
The speed is shown in fig. 14, and the stable speed r is 560, it can be seen that the time for the motor to reach the stable speed is fast.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (8)

1. A universal PID parameter setting method is characterized by comprising the following steps:
step 1, acquiring an acceleration curve of a controlled object;
step 2, selecting a reference object curve from a standard library, wherein the similarity between the reference object curve and an acceleration curve of a controlled object is highest;
and 3, adjusting the acceleration curve of the controlled object by a zooming method, and overlapping the adjusted acceleration curve with the reference object curve to obtain the set PID parameter.
2. The generalized PID parameter tuning method according to claim 1, wherein in step 1, the acceleration curve is obtained by recording the actual object test process, or the acceleration curve is obtained from the known transfer function.
3. The generalized PID parameter tuning method according to claim 2, wherein the judgment process with the highest similarity is as follows: if the transfer function exists, selecting a reference object curve in the standard library through the transfer function; otherwise, the reference object curve is determined in the standard library by whether overshoot is present, the size of the overshoot, or the adjustment time.
4. The generalized PID parameter tuning method according to claim 1, wherein in step 3, the scaling process is compressing or extending the height of the acceleration curve and compressing or extending the length of the acceleration curve.
5. The generalized PID parameter tuning method of claim 4, wherein the scaling factor is obtained by compressing or extending the length of the acceleration curve
Figure FDA0003092676690000011
And
Figure FDA0003092676690000012
6. the generalized PID parameter tuning method of claim 5, wherein the relationship between the scale factor and the coordinate system is:
Figure FDA0003092676690000013
wherein the content of the first and second substances,
Figure FDA0003092676690000014
representing an artificial coordinate system and (t, x) representing a real coordinate system.
7. The method for tuning a universal PID parameter according to any one of claims 1-6, wherein the PID parameter comprises a proportionality coefficient K of a controllerPIntegral coefficient T of controllerIAnd the differential coefficient T of the controllerD。
8. The universal PID parameter tuning method according to claim 7, wherein the calculation process of the PID parameter is:
Figure FDA0003092676690000021
wherein the content of the first and second substances,
Figure FDA0003092676690000022
representing the controller input in the manual coordinate system,
Figure FDA0003092676690000023
the scaling factor is indicative of the controller's scaling factor,
Figure FDA0003092676690000024
which represents the integral coefficient of the controller,
Figure FDA0003092676690000025
representing the derivative coefficient of the controller.
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Application publication date: 20210716