CN113934239A - Electric injection molding pressure control method based on fuzzy PID algorithm - Google Patents
Electric injection molding pressure control method based on fuzzy PID algorithm Download PDFInfo
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- CN113934239A CN113934239A CN202111116901.3A CN202111116901A CN113934239A CN 113934239 A CN113934239 A CN 113934239A CN 202111116901 A CN202111116901 A CN 202111116901A CN 113934239 A CN113934239 A CN 113934239A
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- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D16/00—Control of fluid pressure
- G05D16/20—Control of fluid pressure characterised by the use of electric means
- G05D16/2006—Control of fluid pressure characterised by the use of electric means with direct action of electric energy on controlling means
- G05D16/2013—Control of fluid pressure characterised by the use of electric means with direct action of electric energy on controlling means using throttling means as controlling means
- G05D16/2026—Control of fluid pressure characterised by the use of electric means with direct action of electric energy on controlling means using throttling means as controlling means with a plurality of throttling means
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Abstract
The invention discloses an electric injection molding pressure control method based on a fuzzy PID algorithm, which belongs to the technical field of electric injection molding control, and dynamically adjusts parameters of a PID controller by taking an error and an error change rate as input controllers, and specifically comprises the following steps: s1, determining the input quantity of the injection molding machine control system; s2, fuzzification processing is carried out according to the input quantity; and S3, performing deblurring processing on the input quantity after the fuzzification processing. According to the invention, the calculation difficulty can be obviously reduced through fuzzy subset of fuzzy processing numerical value interval and application of the triangular membership function, the numerical value obtained through fuzzy calculation can reflect the current working condition in real time, the calculation result is used for adjusting the PID parameter in real time, and the variable gain controls the pressure of the thermoplastic material injected into the mold, so that the effect of quickly following and reducing overshoot can be realized through the designed fuzzy PID controller, and the dynamic adjustment of the POD parameter can be realized.
Description
Technical Field
The invention belongs to the technical field of electric injection molding control, and particularly relates to an electric injection molding pressure control method based on a fuzzy PID algorithm.
Background
In the plastic injection molding process, the plastic product is warped and deformed due to the inconsistent cooling rate of each part of the polymer melt, the orientation of polymer molecules and other reasons, so that the appearance of the product is influenced, the service performance of the product is greatly reduced, and even the plastic product is scrapped. The proper technological parameters of the charging barrel temperature, the injection pressure, the injection time, the mold temperature, the pressure maintaining pressure, the time and the like are selected in combination with the rheological property of the material, so that the warping deformation of the product can be effectively reduced.
The injection pressure, the pressure maintaining pressure and the back pressure of the injection molding machine are controlled by the control system, so that the control system has the characteristics of complex control model and large disturbance quantity, and cannot perform exact calculation control through an exact mathematical model. The mainstream controller in the current market is mainly controlled by PID control.
Chinese patent application publication No. CN108181802A discloses a method for optimizing and setting parameters of a PID controller with controllable performance, which optimizes and calculates the parameters obtained by a theoretical calculation and setting method, and the parameters are always kept unchanged after parameter setting is finished and can not be properly and dynamically adjusted along with the change of system parameters; meanwhile, the Chinese patent application publication number of CN112406058B discloses a parameter regulation and control method of a PID controller of an injection molding machine, which converts the parameter setting problem of the PID controller into an expression form of an optimal control problem, gives an optimization target, a system dynamic model and constraint conditions, solves the gradient information of an optimal target function to-be-regulated parameter based on a gradient optimization thought, automatically finds the optimal solution of the PID controller parameter based on gradient information iterative optimization, and realizes the dynamic regulation of the PID controller parameter.
However, when the PID controller performs the variable control, the pressure is easily overshot and even fluctuated due to the variation of disturbance variable and different processes, and the control of the injection pressure cannot be well satisfied.
Disclosure of Invention
The invention aims to: the electric injection pressure control method based on the fuzzy PID algorithm is provided for solving the problem that pressure overshoot and even fluctuation are easily generated due to the change of disturbance quantity and different processes during variable control.
In order to achieve the purpose, the invention adopts the following technical scheme:
an electric injection molding pressure control method based on a fuzzy PID algorithm dynamically adjusts parameters of a PID controller by taking an error and an error change rate as input controllers, and specifically comprises the following steps:
s1, determining the input quantity of the injection molding machine control system, transmitting the technological parameters of the injection molding machine to a detector through a sensor, and feeding the obtained technological information back to the injection molding machine by the control system to obtain the corresponding input quantity of the injection molding machine control system;
s2, fuzzifying according to the input quantity, dividing corresponding numerical value intervals according to the corresponding input quantity transmitted by the control system, and fuzzifying according to a fuzzy rule;
and S3, performing deblurring processing on the input quantity after the fuzzification processing to obtain a real-time working condition result, and adjusting PID parameters in real time according to the result.
As a further description of the above technical solution:
the step of fuzzifying the input quantity in the step S2 includes dividing the input quantity into a certain numerical value interval by the numerical value of the input quantity, dividing the input deviation e and the deviation change rate ec into 7 grades and establishing a fuzzy subset;
the fuzzy subset and the specific numerical correspondence are introduced into the fuzzy domain (-3, -2, -1, 0, 1, 2, 3), and since the maximum value of the measured pressure is PVmax and the minimum value is PVmin, the mapping function of e and ec in the fuzzy domain is:
F（e）=3*e/(PVmax-PVmin)；
F（ec）=3*ec/(2*(PVmax-PVmin))。
as a further description of the above technical solution:
the dividing grades are respectively as follows: negative large (NB), Negative Medium (NM), Negative Small (NS), Zero (ZO), Positive Small (PS), Positive Medium (PM), positive large (PB), the fuzzy subset is defined as { NB, NM, NS, ZO, PS, PM, PB }.
As a further description of the above technical solution:
further comprising reducing the number of computations using a trigonometric membership function, the membership to PM being 0.5 if the quantificational result is 1.5 and the membership to PS being 0.5.
As a further description of the above technical solution:
the deblurring processing function in S3:
as a further description of the above technical solution:
the injection molding machine control system comprises an analog quantity and switching value control part, an operation interface, input and output equipment and an operation system.
As a further description of the above technical solution:
the operating system also includes a model database configured to store fuzzy data for the injection molding machine.
As a further description of the above technical solution:
the input and output equipment comprises one or more position sensors and pressure sensors, the position sensors and the pressure sensors are respectively installed in the extrusion screw and the material cavity, a temperature sensor is further arranged in the material cavity, and the input quantity comprises injection pressure, pressure maintaining pressure and back pressure.
As a further description of the above technical solution:
the injection molding machine fuzzy PID controller using the control method is also included.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
according to the invention, after the fuzzy processing is carried out on the injection molding machine control system through the fuzzy rule, the calculation difficulty can be obviously reduced through the fuzzy subset of the fuzzy processing numerical value interval and the application of the triangular membership function, the current working condition can be reflected in real time through the numerical value obtained by solving the fuzzy calculation, the calculation result is used for adjusting the PID parameter in real time, and the variable gain controls the pressure of the thermoplastic material injected into the mold, so that the effect of reducing overshoot through fast following can be realized through the designed fuzzy PID controller, and the dynamic adjustment of the PID parameter can be realized.
Drawings
FIG. 1 is a schematic diagram of a triangular membership function of an electric injection molding pressure control method based on a fuzzy PID algorithm according to the invention;
FIG. 2 is a diagram of the effect of a classical PID controller;
FIG. 3 is a fuzzy PID controller effect diagram of the electric injection pressure control method based on the fuzzy PID algorithm.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, 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 invention.
Example 1
Referring to fig. 1-3, the present invention provides a technical solution: an electric injection molding pressure control method based on fuzzy PID algorithm, which dynamically adjusts the parameters of a PID controller by using an error and an error change rate as input controllers, wherein an injection molding machine control system comprises an analog quantity and switch quantity control part, an operation interface, input and output equipment and an operation system; the operating system further includes a model database configured to store fuzzy data of the injection molding machine; the input and output equipment comprises one or more position sensors and pressure sensors, the position sensors and the pressure sensors are respectively installed in the extrusion screw and the material cavity, a temperature sensor is further arranged in the material cavity, the input quantity comprises injection pressure, pressure maintaining pressure and back pressure, and the method specifically comprises the following steps:
s1, determining the input quantity of the injection molding machine control system, transmitting the technological parameters of the injection molding machine to a detector through a sensor, and feeding the obtained technological information back to the injection molding machine by the control system to obtain the corresponding input quantity of the injection molding machine control system;
the step of fuzzifying the input quantity in the step S2 includes dividing the input quantity into a certain numerical interval by the numerical value of the input quantity, dividing the input deviation e and the deviation change rate ec into 7 grades, and establishing a fuzzy subset;
the fuzzy subset and the specific numerical correspondence are introduced into the fuzzy domain (-3, -2, -1, 0, 1, 2, 3), and since the maximum value of the measured pressure is PVmax and the minimum value is PVmin, the mapping function of e and ec in the fuzzy domain is:
F（e）=3*e/(PVmax-PVmin)；
F（ec）=3*ec/(2*(PVmax-PVmin))；
the dividing grades are respectively as follows: negative large (NB), Negative Medium (NM), Negative Small (NS), Zero (ZO), Positive Small (PS), Positive Medium (PM), positive large (PB), defining the fuzzy subset as { NB, NM, NS, ZO, PS, PM, PB };
s2, fuzzifying according to the input quantity, dividing corresponding numerical value intervals according to the corresponding input quantity transmitted by the control system, and fuzzifying according to a fuzzy rule;
in the fuzzy rule processing, the fuzzy rule of Kp is defined as follows:
where the fuzzy rule for Ki is defined as follows:
wherein the fuzzy rule of Kd is defined as follows:
s3, performing deblurring processing on the input quantity after the fuzzification processing to obtain a real-time working condition result, and adjusting PID parameters in real time according to the result, wherein the deblurring processing function formula 1:
the method also comprises the steps of reducing the calculated amount by using a triangular membership function, wherein the membership degree of PM is 0.5 if the quantificational result is 1.5, and the membership degree of PS is also 0.5;
as shown in fig. 2 to 3, the operating condition result after the deblurring process is compared with the conventional non-blurred PID controller, and the fluctuation of the PID controller controlled by the blurring process in the embodiment is obviously better than that of the conventional controller.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (9)
1. An electric injection molding pressure control method based on a fuzzy PID algorithm is characterized in that parameters of a PID controller are dynamically adjusted by using a controller with an error and an error change rate as input, and the method specifically comprises the following steps:
s1, determining the input quantity of the injection molding machine control system, transmitting the technological parameters of the injection molding machine to a detector through a sensor, and feeding the obtained technological information back to the injection molding machine by the control system to obtain the corresponding input quantity of the injection molding machine control system;
s2, fuzzifying according to the input quantity, dividing corresponding numerical value intervals according to the corresponding input quantity transmitted by the control system, and fuzzifying according to a fuzzy rule;
and S3, performing deblurring processing on the input quantity after the fuzzification processing to obtain a real-time working condition result, and adjusting PID parameters in real time according to the result.
2. The electric injection pressure control method based on the fuzzy PID algorithm, wherein the fuzzification of the input quantity in the S2 comprises dividing the input quantity into a certain numerical interval by the numerical value of the input quantity, dividing the input deviation e and the deviation change rate ec into 7 grades and establishing fuzzy subsets;
the fuzzy subset and the specific numerical correspondence are introduced into the fuzzy domain (-3, -2, -1, 0, 1, 2, 3), and since the maximum value of the measured pressure is PVmax and the minimum value is PVmin, the mapping function of e and ec in the fuzzy domain is:
F（e）=3*e/(PVmax-PVmin)；
F（ec）=3*ec/(2*(PVmax-PVmin))。
3. the electric injection molding pressure control method based on the fuzzy PID algorithm according to claim 2, wherein the grades are respectively as follows: negative large (NB), Negative Medium (NM), Negative Small (NS), Zero (ZO), Positive Small (PS), Positive Medium (PM), positive large (PB), the fuzzy subset is defined as { NB, NM, NS, ZO, PS, PM, PB }.
4. The method of claim 2, further comprising reducing the calculation amount by using a trigonometric membership function, wherein the membership degree to PM is 0.5 and the membership degree to PS is 0.5 when the result of the calculation is 1.5.
5. The electric injection pressure control method based on fuzzy PID algorithm of claim 1, wherein the de-fuzzy processing function in S3:
6. the electric injection pressure control method based on the fuzzy PID algorithm of the claim 1, wherein the injection machine control system comprises an analog quantity and switch quantity control part, an operation interface, an input and output device and an operation system.
7. The method of claim 6, wherein the operating system further comprises a model database configured to store fuzzy data of the injection molding machine.
8. The electric injection molding pressure control method based on the fuzzy PID algorithm of claim 6, wherein the input and output device comprises one or more position sensors and pressure sensors, and the position sensors and the pressure sensors are respectively installed in the extrusion screw and the material cavity, and a temperature sensor is further installed in the material cavity, and the input quantity comprises injection pressure, holding pressure and back pressure.
9. The electric injection molding pressure control method based on the fuzzy PID algorithm according to the claims 1-8, characterized in that, the method further comprises an injection molding machine fuzzy PID controller using the control method.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114548735A (en) * | 2022-02-17 | 2022-05-27 | 武汉重工铸锻有限责任公司 | Intelligent production scheduling method for batch manufacturing of marine diesel engine crankshafts |
| CN116068880A (en) * | 2023-01-28 | 2023-05-05 | 西安远通耐特汽车安全技术有限公司 | Modified nylon production process feed cylinder temperature regulation and control system based on fuzzy PID |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104890205A (en) * | 2015-05-20 | 2015-09-09 | 华中科技大学 | Barrel temperature control method of injection molding machine |
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Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104890205A (en) * | 2015-05-20 | 2015-09-09 | 华中科技大学 | Barrel temperature control method of injection molding machine |
Non-Patent Citations (1)
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| 王德志: "基于模糊PID的注塑机料筒熔料温度自动控制", 《合成树脂及塑料》, pages 70 - 72 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114548735A (en) * | 2022-02-17 | 2022-05-27 | 武汉重工铸锻有限责任公司 | Intelligent production scheduling method for batch manufacturing of marine diesel engine crankshafts |
| CN116068880A (en) * | 2023-01-28 | 2023-05-05 | 西安远通耐特汽车安全技术有限公司 | Modified nylon production process feed cylinder temperature regulation and control system based on fuzzy PID |
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