High-precision metering and weighing system based on PLC control

Abstract

The invention discloses a high-precision metering and weighing system based on PLC control, relates to the technical field of metering and weighing, and realizes precise product weight measurement and sorting by combining a pressure sensor, a weighing module and a fuzzy PID control algorithm. The system can quickly convert the weight information of the product to be detected into a voltage signal, and after amplification and analog-to-digital conversion, an accurate digital signal is provided for the PLC. And the PLC performs error analysis and parameter adaptive adjustment by using a fuzzy PID algorithm, so that the control precision and the response speed are improved. In addition, through quantitative processing and use of a membership function, the system can effectively reduce errors and perform self-correction, and therefore the accuracy and reliability of overall weighing and sorting are improved. According to the invention, the weighing system can realize high-efficiency automatic control in industrial application, and can meet the weighing requirements of different products.

Description

Technical Field

[0001] The present invention relates to the technical field of weighing and measuring, and more particularly to a high-precision weighing and measuring system based on PLC control. Background Art

[0002] At present, traditional weighing systems face many challenges in the processing and measurement of frozen aquatic products, mainly reflected in insufficient weighing accuracy, lack of real-time data processing capabilities and lack of combination optimization methods. Many existing equipment adopts a single weighing method, which is affected by environmental factors and equipment aging, resulting in unstable weighing results. Any slight error may affect the final product quality. At the same time, traditional systems lack efficient data processing capabilities and cannot screen out effective weighing combinations in a timely manner, thereby reducing production efficiency. Due to the involvement of manual operations, the system often introduces additional errors due to human factors, resulting in instability in the weighing process. In addition, existing technologies fail to effectively handle unqualified weighing results, which directly leads to waste of resources, lack of intelligence and adaptability, and slow response to the weighing needs of different types of materials.

[0003] Therefore, how to improve the accuracy and efficiency of the weighing system is an urgent problem to be solved by those skilled in the art. Summary of the invention

[0004] In view of this, the present invention provides a high-precision weighing system based on PLC control to solve the problems existing in the background technology.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] A high-precision weighing system based on PLC control, comprising: a pressure sensor, a weighing module, a PLC controller, and a set weight-class sorting module; the pressure sensor, the weighing module, the PLC controller, and the set weight-class sorting module are connected in sequence;

[0007] The pressure sensor converts the weight of the product to be measured into a voltage signal through vertical displacement and sends it to the weighing module;

[0008] The weighing module amplifies and converts the received voltage signal in sequence to obtain a digital signal corresponding to the pressure signal, and transmits it to the PLC controller;

[0009] The PLC controller uses the fuzzy PID algorithm to analyze and process the digital signal to obtain the weight information and transmit it to the corresponding set weight level sorting module;

[0010] The weight-level sorting module is set to receive weight information, and when the displacement signal matches the corresponding sorting-level discharge port, the corresponding solenoid valve is controlled to switch on and off to cause the rotating cylinder to move the product to be tested to the corresponding storage basket.

[0011] Optionally, the pressure sensor is a resistive sensor with a resistance strain gauge as a conversion element. The hardware structure consists of an elastic element, a resistance strain gauge, a conversion circuit and a housing. The working principle is that when the elastic element is deformed by external pressure, the strain gauge attached to it is deformed accordingly, causing the strain resistance to change, thereby measuring the current pressure value.

[0012] Optionally, the weighing module includes a pre-amplifier circuit, an AD conversion circuit, and a control chip circuit;

[0013] The pre-amplifier circuit amplifies the collected voltage signal;

[0014] AD conversion circuit, converting the amplified voltage signal into a digital signal;

[0015] The control chip circuit receives the digital signal from the AD conversion circuit, performs data preprocessing operations, and sends the processed digital signal to the PLC controller.

[0016] Optionally, based on the structural characteristics of the CS5532 chip, design an AD conversion circuit; the analog power supply VA+=+5V, VA-=0V, the digital power supply VD+=+3.3V, and the reference voltage VREF use a stable external 3.3V power supply; the C1 and C2 pins are connected to the connection capacitor of the 22nF gain amplifier to suppress the amplifier potential increase and noise, the A0 and A1 pins are the analog logic output terminals of the chip, the OSC1 and OSC2 pins are respectively connected to the two ends of the 4.9125M external crystal oscillator circuit to provide an accurate clock for the system; the serial output pins CS, SDI, SDO, and SCLK are respectively connected to the NSS, MOSI, MISO, and SCK pins of the SPI bus of the AD control chip to communicate with peripherals, where CS is the chip select pin, which controls the serial port enable, and the low level is valid, SDI is the data input terminal, SDO is the data output terminal, and SCLK is the clock input terminal, which controls the shift of the A / D serial port data.

[0017] Optionally, the specific principle of the PLC controller using the fuzzy PID algorithm to analyze and process the digital signal is:

[0018] S1, obtaining the initial preset weight value of the weighing module and the actual weighing value after the product to be tested is put down, and obtaining the error e and the error change rate ec between the preset weight value and the actual weighing value;

[0019] S2. According to the error e and the error change rate ec, the control rule of the fuzzy adaptive algorithm is adopted to obtain the proportional gain Kp, the integral gain ki and the differential gain kd in the PID controller;

[0020] S3, setting the actual domain of error e and error change rate ec, obtaining the quantization factor to convert the error e and error change rate ec of the actual weighing value into the quantized error E and error change rate Ec;

[0021] S4, then set the corresponding fuzzy subset according to the domain of the quantized error E, error change rate Ec, proportional gain Kp, integral gain ki and differential gain kd;

[0022] S5, determine the membership function, and determine the fuzzy control based on the membership function, find the fuzzy relationship R, and determine the fuzzy output signal;

[0023] S6. The fuzzy output signal is clarified by the maximum membership method and converted into a clear output signal U. Optionally, the process of PID self-tuning correction is also included:

[0024] kp=kp'+Δkp

[0025] ki=kp'+Δki

[0026] kd=kd'+Δkd

[0027] In the formula, kp', kp', kd' are the proportional gain, reference gain and differential gain before correction; Δkp, Δki, Δkd are the correction coefficients;

[0028] The correction is completed by substituting the correction coefficient determined based on the error e of the actual weighing value and the error change rate ec into the formula.

[0029] Optionally, the quantization factor is:

[0030]

[0031] In the formula, e L Represents the minimum value of the error, e H Indicates the maximum value of the error; Indicates the minimum value of the error change rate, It represents the maximum value of the error change rate; m and n represent the width of the domain of error and error change rate respectively.

[0032] Optionally, the membership function is in triangular form, and its mathematical expression is as follows:

[0033]

[0034] Among them, a represents the abscissa of the left endpoint of the triangle membership function, b represents the abscissa of the right endpoint of the triangle membership function, and c is the abscissa of the vertex of the triangle membership function.

[0035] Optionally, the proportional factor is expressed as:

[0036]

[0037] In the formula, u H 、u L is the maximum and minimum value of the proportional gain Kp, integral gain ki and differential gain kd; y is the domain of the proportional gain Kp, integral gain ki and differential gain kd.

[0038] It can be seen from the above technical solutions that compared with the prior art, the present invention discloses a high-precision metering and weighing system based on PLC control, which realizes accurate product weight measurement and sorting by combining pressure sensors, weighing modules and fuzzy PID control algorithms. The system can quickly convert the weight information of the product to be measured into a voltage signal, and after amplification and analog-to-digital conversion, provide an accurate digital signal to the PLC. The PLC uses the fuzzy PID algorithm to perform error analysis and adaptive parameter adjustment to improve control accuracy and response speed. In addition, through the use of quantitative processing and membership functions, the system can effectively reduce errors and self-correct, thereby improving the accuracy and reliability of overall weighing and sorting. This design enables the weighing system to achieve efficient automatic control in industrial applications and adapt to the weighing requirements of different products. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0040] Figure 1 A schematic diagram of the system structure provided by the present invention;

[0041] Figure 2 The AD conversion circuit design principle diagram of the system structure provided by the present invention;

[0042] Figure 3 This is the fuzzy PID weighing principle diagram provided by the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] The embodiment of the present invention discloses a high-precision weighing system based on PLC control. Figure 1 As shown, it includes: a pressure sensor, a weighing module, a PLC controller, and a set weight level sorting module; the pressure sensor, the weighing module, the PLC controller, and the set weight level sorting module are connected in sequence;

[0045] The pressure sensor converts the weight of the product to be measured into a voltage signal through vertical displacement and sends it to the weighing module;

[0046] The weighing module amplifies and converts the received voltage signal in sequence to obtain a digital signal corresponding to the pressure signal, and transmits it to the PLC controller;

[0047] The PLC controller uses the fuzzy PID algorithm to analyze and process the digital signal to obtain the weight information and transmit it to the corresponding set weight level sorting module;

[0048] The weight-level sorting module is set to receive weight information, and when the displacement signal matches the corresponding sorting-level discharge port, the corresponding solenoid valve is controlled to switch on and off to cause the rotating cylinder to move the product to be tested to the corresponding storage basket.

[0049] In a specific embodiment, the pressure sensor is a resistive sensor with a resistance strain gauge as a conversion element. The hardware structure consists of an elastic element, a resistance strain gauge, a conversion circuit and a housing. The working principle is that when the elastic element is deformed by external pressure, the strain gauge attached to it is deformed together, causing the strain resistance to change, thereby measuring the current pressure value. HBM's PW4M weighing sensor can convert the pressure signal into an electrical signal and output a voltage signal of 0 to 20mv. In subsequent data acquisition, the signal amplitude, driving ability, linearity, anti-interference ability and other aspects need to be conditioned, which is achieved by constructing an amplifier circuit with multiple characteristics. The accuracy of the weighing sensor is shown in Table 1.

[0050] Table 1 Accuracy of weighing sensor

[0051] Accuracy level Minimum calibration scale Rated range C3 0.5g 0-3Kg

[0052] In a specific embodiment, the weighing module includes a pre-amplifier circuit, an AD conversion circuit, and a control chip circuit;

[0053] The pre-amplifier circuit amplifies the collected voltage signal;

[0054] AD conversion circuit, converting the amplified voltage signal into a digital signal;

[0055] The control chip circuit receives the digital signal from the AD conversion circuit, performs data preprocessing operations, and sends the processed digital signal to the PLC controller.

[0056] Considering that the output signal level of the pressure sensor is low and the internal resistance is large, the requirements of the amplifier include: 1. The resistance of the signal source must be lower than the input impedance, otherwise, a load effect will occur, causing the output voltage to deviate. 2. It can effectively suppress the noise of the operational amplifier, and the noise and input offset must be minimized when the signal-to-noise ratio is obtained. The absolute accuracy of the gain must be guaranteed in a special width to ensure the final output performance. Based on the design requirements of the amplifier, the present invention designs a dual operational amplifier preamplifier circuit. The circuit adopts a differential input module composed of two-stage operational amplifiers. The first-stage operational amplifier adopts the operational amplifier OPA2277. The amplifier has low noise and can effectively improve the signal resolution. It limits the output of the signal to a smaller range and greatly improves the linear performance of the system. The magnetic beads FB7, FB8, and the capacitor C16 are used to filter out the noise generated by the front stage. The second stage adopts the TLC2272 chip with full power amplitude output dual operational amplifier. The chip has the characteristics of high input impedance and low noise, a high common mode rejection ratio, and good linear output characteristics for millivolt-level input signals. Under an input excitation voltage of 5V, the system can accurately amplify 0-20mv signals to 2.5V-5V, meeting the needs of subsequent AD conversion circuits.

[0057] In a specific embodiment, based on the structural characteristics of the CS5532 chip, an AD conversion circuit is designed; Figure 2 As shown, analog power supply VA+=+5V, VA-=0V, digital power supply VD+=+3.3V, and reference voltage VREF uses a stable external 3.3V power supply; C1 and C2 pins are connected to the connection capacitor of the 22nF gain amplifier to suppress the amplifier potential increase and noise, A0 and A1 pins are the analog logic output terminals of the chip, OSC1 and OSC2 pins are respectively connected to the two ends of the 4.9125M external crystal oscillator circuit to provide an accurate clock for the system; serial output pins CS, SDI, SDO, and SCLK are respectively connected to the NSS, MOSI, MISO, and SCK pins of the SPI bus of the AD control chip to communicate with peripherals, where CS is the chip select pin, which controls the serial port to be enabled and is valid at a low level, SDI is the data input terminal, SDO is the data output terminal, and SCLK is the clock input terminal, which controls the shift of A / D serial port data.

[0058] In a specific embodiment, Figure 3 As shown in the figure, the specific principle of the PLC controller using the fuzzy PID algorithm to analyze and process digital signals is:

[0059] S1, obtaining the initial preset weight value of the weighing module and the actual weighing value after the product to be tested is put down, and obtaining the error e and error change rate ec between the preset weight value and the actual weighing value;

[0060] S2. According to the error e and the error change rate ec, the control rule of the fuzzy adaptive algorithm is adopted to obtain the proportional gain Kp, integral gain ki and differential gain kd in the PID controller;

[0061] S3, setting the actual domain of error e and error change rate ec, obtaining the quantization factor to convert the error e and error change rate ec of the actual weighing value into the quantized error E and error change rate Ec;

[0062] S4, then set the corresponding fuzzy subset according to the domain of the quantized error E, error change rate Ec, proportional gain Kp, integral gain ki and differential gain kd;

[0063] S5, determine the membership function, and determine the fuzzy control based on the membership function, find the fuzzy relationship R, and determine the fuzzy output signal;

[0064] S6. Clarify the fuzzy output signal through the maximum membership method and convert it into a clear output signal U, where U includes correction coefficients Δkp, Δki, and Δkd.

[0065] The so-called maximum membership method is to assign the element with the largest membership in the domain corresponding to the fuzzy output signal to the clear output signal U as the result of clarification.

[0066] The following is a specific description of the fuzzy PID algorithm:

[0067] 1. Model parameters: Select two inputs and three outputs.

[0068] Input variables:

[0069] The error between the actual weighing value and the set weighing value is

[0070] Weighing value error change rate ec

[0071] Output variables:

[0072] Kp, Ki, Kd;

[0073] 2. Set the actual domain of e: e∈[-2g, 2g];

[0074] Set the actual domain of ec: ec∈[-1,1];

[0075] Quantize e and ec to the fuzzy domain, and the quantization factor is

[0076]

[0077] In the formula, e L Represents the minimum value of the error, e H Indicates the maximum value of the error; Indicates the minimum value of the error change rate, It represents the maximum value of the error change rate; m and n represent the width of the domain of error and error change rate respectively.

[0078] e=[-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6]

[0079] Among them, -6=-2g, 6=2g, and the same applies to the others.

[0080] ec=[-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6]

[0081] Among them, -6=-1, 6=1, and so on.

[0082] Therefore, the corresponding fuzzy subset is

[0083] K e =[negative large, negative medium, negative small, zero, positive small, positive medium, positive large]

[0084] That is: NB, NM, NS, ZO, PS, PM, PB

[0085] K ec =[negative large, negative medium, negative small, zero, positive small, positive medium, positive large]

[0086] That is: NB, NM, NS, ZO, PS, PM, PB

[0087] So: Quantization factor

[0088]

[0089] Get the quantization factor K e and K ec After that, the error e and the error change rate ec are converted into the quantized error E and the error change rate Ec. The conversion formulas are shown in equations (3) and (4).

[0090]

[0091] Among them, INT[] represents the rounding operation.

[0092] Then, the corresponding fuzzy subsets are set according to the quantized error E, error change rate Ec and the fuzzy domain of Kp, Ki, Kd.

[0093] The fuzzy domain of Kp, Ki, Kd is [-1, 1], so the corresponding fuzzy subsets

[0094] Kp'={negative large (NB), negative medium (NM), negative small (NS), zero (ZO), positive small (PS), positive medium (PM), positive large (PB)}

[0095] Ki'={negative large (NB), negative medium (NM), negative small (NS), zero (ZO), positive small (PS), positive medium (PM), positive large (PB)}

[0096] Kd'={negative large (NB), negative medium (NM), negative small (NS), zero (ZO), positive small (PS), positive medium (PM), positive large (PB)}.

[0097] Among them, negative big corresponds to -1 in the fuzzy domain, negative middle represents -2 / 3, negative small represents -1 / 3, zero represents 0, positive small represents 1 / 3, positive middle represents 2 / 3, and positive big represents 1.

[0098] The mathematical expression for determining the triangular form of the membership function is as follows:

[0099]

[0100] Among them, a represents the abscissa of the left endpoint of the triangle membership function, b represents the abscissa of the right endpoint of the triangle membership function, and c is the abscissa of the vertex of the triangle membership function.

[0101] 4. Establish fuzzy control rules

[0102] Fuzzy conditional propositions are in the form of if A and B then C, D and E. Using IF-then statements, there are 7 sections with 49 rules in total. For example, the format is:

[0103] IfE is NB and EC is NB then X is PB andY is NB andZ is PS,

[0104] IfE is NB and EC is NM then X is PB and Y is NB and Z is NS etc.

[0105] The fuzzy rule control tables are shown in Table 1, Table 2 and Table 3.

[0106] Table 2ΔKp fuzzy rule control table

[0107] EC\E NB NM NS ZO PS PM PB NB PB PB PM PM PS ZO ZO NM PB PB PM PS PS ZO NS NS PM PM PM ZO ZO NS NS ZO PM PS PS NS NS NM NM PS PS PS ZO NS NS NM NM PM ZO ZO NS NM NM NM NB PB ZO NS NM NM NM NB NB

[0108] Table 3 ΔKi fuzzy rule control table

[0109] EC\E NB NM NS ZO PS PM PB NB PB PB NM NM NS ZO ZO NM PB PB NM NS NS ZO ZO NS PM PM NS NS ZO PS PS ZO PM PS NS ZO PS PM PM PS PS PS ZO PS PS PM PB PM ZO ZO PS PS PM PM PB PB ZO NS PS PM PM PB PB

[0110] Table 4 ΔKd fuzzy rule control table

[0111] EC\E NB NM NS ZO PS PM PB NB PS PS NB NB NB NM PS NM NS NS NB NM NM NS ZO NS NB NB NM NM NS NS ZO ZO NB NM NS NS NS NS ZO PS NB NM ZO ZO ZO ZO ZO PM NM NS PS PS PS PS PB PB PS ZO PM PM PS PS PB

[0112] The scaling factor is expressed as:

[0113]

[0114] In the formula, u H 、u L is the maximum and minimum value of the proportional gain Kp, integral gain ki and differential gain kd; y is the domain of the proportional gain Kp, integral gain ki and differential gain kd.

[0115] Then we get the expression of output signal U:

[0116]

[0117] That is, the correction coefficients corresponding to the proportional gain, reference gain and differential gain are obtained respectively.

[0118] It also includes the process of PID self-tuning correction:

[0119] kp=kp'+Δkp

[0120] ki=kp'+Δki

[0121] kd=kd'+Δkd

[0122] In the formula, kp', kp', kd' are the proportional gain, reference gain and differential gain before correction; Δkp, Δki, Δkd are the correction coefficients;

[0123] The correction is completed by substituting the correction coefficient determined based on the error e of the actual weighing value and the error change rate ec into the formula.

[0124] The overall process of the present invention is: system start → sampling and filtering → sampling time is up → whether e and ec are out of range → find e and ec, and perform fuzzy processing according to the above design route → find Δkp and other increments according to simulation data → calculate kp and other increments → fuzzy PID tuning → end → control setting heavyweight sorting module operation.

[0125] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0126] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A high-precision weighing system based on PLC control, characterized in that: include: Pressure sensor, weighing module, PLC controller, set weight class sorting module; Pressure sensor, weighing module, PLC controller, set weight class sorting module are connected in sequence; The pressure sensor converts the weight of the product to be measured into a voltage signal through vertical displacement and sends it to the weighing module; The weighing module amplifies and converts the received voltage signal in sequence to obtain a digital signal corresponding to the pressure signal, and transmits it to the PLC controller; The PLC controller uses the fuzzy PID algorithm to analyze and process the digital signal to obtain the weight information and transmit it to the corresponding set weight level sorting module; The weight-level sorting module is set to receive weight information, and when the displacement signal matches the corresponding sorting-level discharge port, the corresponding solenoid valve is controlled to switch on and off to cause the rotating cylinder to move the product to be tested to the corresponding storage basket.

2. A high-precision weighing system based on PLC control according to claim 1, characterized in that: The pressure sensor is a resistive sensor with a resistance strain gauge as a conversion element. The hardware structure consists of an elastic element, a resistance strain gauge, a conversion circuit and a shell. The working principle is that when the elastic element is deformed by external pressure, the strain gauge attached to it is deformed along with it, causing the strain resistance to change, thereby measuring the current pressure value.

3. A high-precision weighing system based on PLC control according to claim 1, characterized in that: The weighing module includes a pre-amplifier circuit, an AD conversion circuit, and a control chip circuit; The pre-amplifier circuit amplifies the collected voltage signal; AD conversion circuit, converting the amplified voltage signal into a digital signal; The control chip circuit receives the digital signal from the AD conversion circuit, performs data preprocessing operations, and sends the processed digital signal to the PLC controller.

4. A high-precision weighing system based on PLC control according to claim 1, characterized in that: Based on the structural characteristics of the CS5532 chip, an AD conversion circuit is designed; the analog power supply VA+=+5V, VA-=0V, the digital power supply VD+=+3.3V, and the reference voltage VREF use a stable external 3.3V power supply; the C1 and C2 pins are connected to the connection capacitor of the 22nF gain amplifier to suppress the amplifier potential increase and noise, the A0 and A1 pins are the analog logic output terminals of the chip, the OSC1 and OSC2 pins are respectively connected to the two ends of the 4.9125M external crystal oscillator circuit to provide an accurate clock for the system; the serial output pins CS, SDI, SDO, and SCLK are respectively connected to the NSS, MOSI, MISO, and SCK pins of the SPI bus of the AD control chip to communicate with the peripherals, where CS is the chip select pin, which controls the serial port to be enabled and is valid at a low level, SDI is the data input terminal, SDO is the data output terminal, and SCLK is the clock input terminal, which controls the shift of the A / D serial port data.

5. The high-precision weighing system based on PLC control according to claim 1 is characterized in that: The specific principle of the PLC controller using fuzzy PID algorithm to analyze and process digital signals is: S1, obtaining the initial preset weight value of the weighing module and the actual weighing value after the product to be tested is put down, and obtaining the error e and the error change rate ec between the preset weight value and the actual weighing value; S2. According to the error e and the error change rate ec, the control rule of the fuzzy adaptive algorithm is adopted to obtain the proportional gain Kp, the integral gain ki and the differential gain kd in the PID controller; S3, setting the actual domain of error e and error change rate ec, obtaining the quantization factor to convert the error e and error change rate ec of the actual weighing value into the quantized error E and error change rate Ec; S4, then set the corresponding fuzzy subset according to the domain of the quantized error E, error change rate Ec, proportional gain Kp, integral gain ki and differential gain kd; S5, determine the membership function, and determine the fuzzy control based on the membership function, find the fuzzy relationship R, and determine the fuzzy output signal; S6. The fuzzy output signal is clarified through the maximum membership method and converted into a clear output signal U.

6. A high-precision weighing system based on PLC control according to claim 5, characterized in that: It also includes the process of PID self-tuning correction: kp=kp′+Δkp ki=kp′+Δki kd=kd′+Δkd In the formula, kp', kp', kd' are the proportional gain, reference gain and differential gain before correction; Δkp, Δki, Δkd are the correction coefficients; The correction is completed by substituting the correction coefficient determined based on the error e of the actual weighing value and the error change rate ec into the formula.

7. A high-precision weighing system based on PLC control according to claim 5, characterized in that: The quantization factor is: In the formula, e L Represents the minimum value of the error, e H Indicates the maximum value of the error; Indicates the minimum value of the error change rate, It represents the maximum value of the error change rate; m and n represent the width of the domain of error and error change rate respectively.

8. The high-precision weighing system based on PLC control according to claim 5 is characterized in that: The membership function is in triangular form, and its mathematical expression is as follows: Among them, a represents the abscissa of the left endpoint of the triangle membership function, b represents the abscissa of the right endpoint of the triangle membership function, and c is the abscissa of the vertex of the triangle membership function.

9. The high-precision weighing system based on PLC control according to claim 5 is characterized in that: The proportional factor is expressed as: In the formula, u H 、u L is the maximum and minimum value of proportional gain Kp, integral gain ki and differential gain kd; y is the domain of proportional gain Kp, integral gain ki and differential gain kd.

Images