A Synchronous Control Method for 3D Ceramic Printing Based on STM32H7 Chip

Abstract

This invention relates to a synchronous control method for 3D ceramic printing based on the STM32H7 chip. The STM32H7 chip serves as the control center for the motion mechanism in 3D ceramic printing, synchronously controlling the motion of two motors. The method includes: sampling the rotational speeds of the two motors to obtain the speeds ω1 of the first motor and ω2 of the second motor; and determining the following error e based on the proportional relationship between the two motor speeds. 12 According to the following error e 12 The speed compensator output e1 of the first motor is obtained by performing feedforward fuzzy PI control on the first motor. The evaluated speed following error ε1 of the first sub-motor is obtained based on the speed ω1 of the first motor and the speed evaluation function. The speed compensator output e1, the evaluated speed following error ε1, and the speed ω1 of the first motor are input into a fuzzy PID controller for fuzzy PID control, resulting in a control signal u1 to control the speed of the first sub-motor. This enables the rapid fabrication of large-size, highly complex ceramic structural components for the aerospace field.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of 3D ceramic printing, and particularly relates to a 3D ceramic printing synchronous control method based on an STM32H7 chip. BACKGROUND

[0002] Digital light processing ceramic 3D printing technology provides an opportunity for the rapid production of complex ceramic devices in the fields of aviation, medicine and chemical industry due to its advantages of fast forming speed, high precision and good quality. The difficulty in coordinating the forming quality and efficiency is the main factor restricting the development of this technology. It is necessary to develop this new preparation method to effectively shorten the manufacturing cycle of aerospace structural parts, realize the preparation of large-size high-complexity ceramic structural parts, and meet the rapid development of new generation aircraft and their harsh high-temperature environment requirements.

[0003] Using STM32H7 as the control center can reduce the CPU workload by more than 90% for processing the instructions of the host computer software and controlling the actions of the components, and the image display effect is good to ensure the rapid analysis, processing and calculation of printing information. Since the printing size is large and the required power is large during printing, dual-motor driving is adopted. At present, the control structure mainly used in the speed synchronous control system of multiple motors is the traditional deviation coupling control structure. The key to the outstanding control effect of the traditional deviation coupling control structure compared with other control structures is the addition of the speed deviation compensator structure, but the traditional deviation coupling control structure only considers the speed deviation information between the controlled sub-motor system and other sub-motor systems. This information does not contain the information of the speed difference between other sub-motor systems and the speed following error of other sub-motor systems. When the speed following error of other sub-motor systems is relatively large, the time required for the speed controller of this sub-motor system to eliminate its own speed following error is also relatively long, which will also cause a large synchronization error between the sub-motor systems. SUMMARY

[0004] In view of the above analysis, the embodiments of the present application aim to provide a 3D ceramic printing synchronous control method based on an STM32H7 chip to solve the problems of slow speed and poor forming quality of large-size high-complexity ceramic structural parts during the printing process.

[0005] The purpose of the present application is mainly realized by the following technical solutions:

[0006] The present application provides a 3D ceramic printing synchronous control method based on an STM32H7 chip, wherein the STM32H7 chip is the motion mechanism control center of the 3D ceramic printing and synchronously controls the motion of dual motors.

[0007] Sampling the rotation speed of the double motor to obtain the first motor speed ω1 and the second motor speed ω2;

[0008] According to the proportional relationship of the double motor speed, determining the following error e 12 ;

[0009] According to the following error e 12 , the first motor is subjected to fuzzy PI control to obtain the speed compensator output e1 of the first motor;

[0010] According to the speed ω1 of the first motor, the speed evaluation function , the evaluation speed following error ε1 of the first motor is obtained;

[0011] The speed compensator output e1 of the first motor, the evaluation speed following error ε1 of the first motor and the speed ω1 of the first motor are input into a fuzzy PID controller for fuzzy PID control to obtain a control signal u1 for controlling the speed of the first motor.

[0012] Further, the following error e 12 is determined according to the following formula:

[0013] e 12 = ω1 / λ1- ω2 / λ2

[0014] Wherein, λ1 is the synchronous proportional coefficient of the first motor; λ2 is the synchronous proportional coefficient of the second motor.

[0015] Further, the first motor is subjected to fuzzy PI control according to the following error e 12 to obtain the speed compensator output e1, and the formula is as follows:

[0016] e1= K 12 *e 12 +I 12 ∫e 12 *dt

[0017] Wherein, K 12 is the proportional increment of the first motor relative to the second motor; I 12 is the integral increment of the first motor relative to the second motor.

[0018] Further, the proportional increment K 12 of the first motor relative to the second motor and the integral increment I 12 of the first motor relative to the second motor are determined by the speed deviation level of the first motor and the second motor; wherein, the speed deviation level of the first motor and the second motor includes: positive large deviation, positive small deviation, zero deviation, negative small deviation, negative large deviation.

[0019] Further, the evaluation speed follows the error ε1, whose formula is as follows:

[0020]

[0021] Wherein, ω1 is the speed of the first motor; is the speed evaluation.

[0022] Further, the speed evaluation whose formula is as follows:

[0023]

[0024] Wherein, a i is the weighting coefficient; i is the motor serial number, taking the value of 1 or 2.

[0025] Further, the input of the fuzzy PID controller is the deviation value e, and the initial control parameters of the fuzzy PID controller are corrected by using the deviation value e and the deviation change rate ec, to obtain the corrected control parameters;

[0026] The control signal u1 is obtained by using the corrected control parameters and an amplification coefficient K1 for amplifying the deviation value e.

[0027] Further, the deviation value e, whose formula is as follows:

[0028] e = e1 + ε1 - ω1

[0029] Wherein, e1 is the speed compensator output of the first motor; ε1 is the evaluation speed following error of the first motor; ω1 is the speed of the first motor;

[0030] The deviation change rate ec is the differential of the deviation value e, denoted as

[0031] Further, the control parameters include the proportional coefficient k p , the integral coefficient k i and the differential coefficient k d .

[0032] The correction of the initial control parameters of the fuzzy PID controller by using the deviation value e and the deviation change rate ec to obtain the corrected control parameters, includes:

[0033] According to the deviation level of the deviation value e and the deviation change rate ec, the dynamic value of the control parameters is determined;

[0034] The corrected control parameters are the total value of the initial control parameters and the dynamic value of the control parameters.

[0035] Furthermore, the dynamic value of the control parameter is determined based on the deviation level of the deviation value e and the deviation change rate ec, wherein:

[0036] Determine the proportionality coefficient K p When the dynamic value is defined, the deviation levels of the deviation value e and the deviation change rate ec include: large positive deviation, small positive deviation, zero deviation, small negative deviation, and large negative deviation.

[0037] Determine the integral coefficient K i and differential coefficient K d When the dynamic value is obtained, the deviation level of the deviation value e includes: positive large deviation, positive small deviation, zero deviation, negative small deviation, and negative large deviation; the deviation level of the deviation change rate ec includes: positive small deviation, zero deviation, negative small deviation, and negative large deviation.

[0038] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0039] 1. This invention uses an STM32H7 chip as the motion control center for 3D ceramic printing to synchronously control the movement of dual motors and process instructions from the host computer software. This can reduce the CPU workload by more than 90%, and provide excellent image display. This ensures rapid analysis, processing, and calculation of printed information, effectively shortening the manufacturing cycle of aerospace structural components and enabling the preparation of large-size, highly complex ceramic structural components.

[0040] 2. The dual-motor speed control of the present invention adopts an improved deviation coupling control structure and introduces feedforward PI control. When the load changes suddenly during the operation of the motor, targeted compensation is performed to achieve synchronization between the motors while maintaining good dynamic and static performance of the motors.

[0041] 3. This invention provides real-time correction of speed fluctuations in dual motors through dynamic compensation, combined with a speed evaluation function. The difference between the reference value and the motor feedback speed is used for fuzzy PID control, and finally used as the control signal for the motor driver to achieve high-precision synchronous control.

[0042] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0043] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0044] Figure 1 This is a schematic diagram of the structure of a 3D ceramic printing control system according to an embodiment of the present invention;

[0045] Figure 2 This is a structural block diagram of the 3D ceramic printing control system in an embodiment of the present invention;

[0046] Figure 3 This is a schematic diagram of the STM32H7 chip configuration information in an embodiment of the present invention;

[0047] Figure 4 This is a flowchart illustrating the 3D ceramic printing process in an embodiment of the present invention.

[0048] Figure 5 This is a schematic diagram of a synchronous control method for 3D ceramic printing based on an STM32H7 chip in an embodiment of the present invention.

[0049] Figure 6 This is a schematic diagram of the dual-motor control speed compensation structure in an embodiment of the present invention;

[0050] Figure 7 This is a schematic diagram of fuzzy PID control in an embodiment of the present invention. Detailed Implementation

[0051] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0052] One specific embodiment of the present invention discloses a 3D ceramic printing control system that coordinates high quality and high efficiency molding based on digital light processing technology. For example... Figure 1 As shown, the 3D ceramic printing control system includes a host computer system, a multi-optical engine system, and a motion mechanism system.

[0053] Specifically, the host computer system is a PC-based host computer and a form program with a human-computer interaction interface; the optomechanical system is a DLP-based optomechanical control system; the motion mechanism system includes a motion mechanism control system, a scraper motion mechanism, a screen plate motion mechanism, a settling block motion mechanism, and a slurry tank motion mechanism.

[0054] Furthermore, such as Figure 2As shown, the motion mechanism control system consists of a microcontroller, a drive controller, and sensors. The microcontroller connects to a host computer via a network port and uses an STM32H7 chip as the control center, processing instructions from the host computer software and controlling the actions of the components. The sensors include a level sensor, limit switches, and a temperature sensor. The sensors feed back signals to the microcontroller, which processes the signals and then transmits them to the Z-axis servo drivers for the mesh plate, X-axis scraper, Z-axis slurry tank, and Z-axis sedimentation block. The motion mechanism control system uses a self-developed hardware platform with rich interfaces, low cost, and stable reliability.

[0055] Specifically, the microcontroller controller hardware platform features 24 digitally isolated inputs, 12 digitally isolated outputs, 4 relay outputs (expandable), 2 CAN interfaces (1 interface controlling 4 servo motors via the CANopen protocol), 1 interface for communication with level and limit sensors, 1 Ethernet interface implementing TCP / IP and UDP protocols via the LWIP protocol stack for communication with the host computer interface, and 3 serial interfaces (2 RS232 and 1 RS485) for communication with other sensors. This ensures high system integration and centralized control.

[0056] Furthermore, such as Figure 3 As shown, the STM32H7 chip internally uses a Cortex-M7 microprocessor with a main frequency of 480MHz, paired with a dual-core Cortex-M4 240MHz-2400Coremark, 1027DMIPS double-precision floating-point operation, 16KB L1 cache, 64KB ITCM and 128KB DTCM fast access memory, a maximum bus speed of 240MHz, 2MB internal Flash and 1MB distributed SRAM. The STM32H7 chip features a powerful core Chrom-ART Accelerator and MJPEG codec, which can reduce the CPU workload by more than 90%, providing excellent image display quality to ensure rapid analysis, processing and calculation of printed information.

[0057] Furthermore, the printing process of the 3D ceramic printing control system is as follows: Figure 4 As shown, after the printing equipment is powered on, each motion mechanism completes its initialization and zero-return action. The host computer establishes a communication link with the main control system and the optomechanical system. After successful linking, the scraper stroke and the speed of each motion mechanism are set. Simultaneously, the power density, exposure time, and correction magnification X and Y of the optomechanical system are set, and then the SLC slice file is sent to the optomechanical system. The SLC slice file is a data storage file format proposed for obtaining data after layering and slicing a rapid prototyping 3D model.

[0058] Furthermore, the screen uses a scooping method to pick up the material during the printing process. After clicking to start printing, the screen movement mechanism descends into the paste tank to scoop up the material. After scooping, the screen rises to a set distance, the squeegee performs a cutting process, and the optical engine performs exposure processing according to a specific image. After exposure, the screen continues to descend into the paste tank to scoop up the material, and then rises again to the optical engine exposure position. After the squeegee performs a cutting process, the optical engine performs exposure again according to a specific layer. This cycle repeats until printing is complete.

[0059] It should be noted that the motion trajectory of the mesh plate is calculated using the following formula:

[0060] P setdown =P0 + 65536 * P d +65536*C d *T h

[0061] P setup =P0+65536*n*T h

[0062] Among them, P setdown P is the distance the stencil descends. setup P is the distance the stencil rises; P0 is the initial position of the stencil after power-on; P d The base position for the page layout to drop; C d For the reciprocating rise counter of the stencil; T h The thickness of each layer of the printed model is denoted as n; n is an integer, calculated based on experimental values ​​of slurry depth, and in this embodiment, n is taken as 10.

[0063] In this embodiment, an STM32H7 chip is used as the control center, and the printing size is 500*500mm. Since printing requires a large amount of power, the traditional single-motor drive for stencil movement cannot meet the needs of the 3D ceramic printing system in this embodiment. Therefore, a dual-motor drive for stencil movement is required for printing.

[0064] Furthermore, in the dual-motor synchronous control system, when the speed of one sub-motor system changes due to external disturbances such as sudden load changes, the controllers of the other motors will also receive information about this speed change, thus the system has good synchronization performance. However, this sub-motor system does not receive information about the asynchrony between the speeds of the other sub-motors, nor does it include information about the speed following errors of the other sub-motors.

[0065] Furthermore, while traditional deviation-coupled control structures offer superior control performance compared to other structures, the key lies in the addition of a speed deviation compensator. However, traditional deviation-coupled control structures only consider the speed deviation information between the controlled sub-motor system and other sub-motor systems. This information does not include information about the asynchrony between the speeds of other sub-motors or their speed following errors. When the speed following error of other sub-motor systems is significant, the time required for the speed controller of that sub-motor system to eliminate its own speed following error is also relatively long, which can also lead to large synchronization errors between the sub-motor systems.

[0066] Therefore, another embodiment of the present invention discloses a synchronous control method for 3D ceramic printing based on an STM32H7 chip, which improves upon the shortcomings of traditional deviation-coupled control structures. The control approach involves subtracting the speed feedback of one sub-motor system from the speed feedback of other sub-motor systems, using the resulting deviation as the speed compensation value for that sub-motor system. This ensures that all sub-motor systems have the same speed output, improving the synchronous control performance of the system. The STM32H7 chip serves as the control center for the motion mechanism of the 3D ceramic printing, synchronously controlling the motion of the two motors. Specifically, the control center synchronously controls the motion of the two motors as follows: Figure 5 As shown, it includes:

[0067] Step S1: Sample the rotational speeds of the two motors to obtain the speeds ω1 of the first motor and ω2 of the second motor; the STM32H7 chip acts as the motion mechanism control center to sample the rotational speeds of the two motors.

[0068] Furthermore, if all motors operate synchronously, then according to Figure 6 For the structure shown, the speed relationship between the two motors must meet the following conditions:

[0069] ω1=λ1ω *

[0070] ω2=λ2ω *

[0071] That is, the proportional relationship of the speeds of the two motors is ω1 / ω2=λ1 / λ2; where λ1 is the synchronization proportional coefficient of the first motor; and λ2 is the synchronization proportional coefficient of the second motor.

[0072] Step S2: Determine the following error e based on the proportional relationship of the speeds of the two motors. 12 for:

[0073] e 12 =ω1 / λ1-ω2 / λ2

[0074] It should be noted that, in order for all motors to operate synchronously, the following relationship must be satisfied: The following relationship must be met to ensure that the following relationship is met:

[0075]

[0076] Step S3, based on the following error e 12 The speed compensator output e1 of the first motor is obtained by performing feedforward fuzzy PI control on the first motor.

[0077] In this embodiment, the speed compensation compensator is particularly important when implementing motor control. During the operation of multiple motors, when the load changes abruptly, the differences in the operating parameters of each motor will lead to inconsistent speeds. To eliminate the asynchrony caused by speed fluctuations, targeted compensation is required. This type of motor interference is analyzed and fedforward control is introduced. When interference occurs, it is eliminated through fuzzy PI control, achieving synchronization between motors while maintaining good dynamic and static performance.

[0078] Specifically, the speed compensator outputs e1 in the first motor subsystem, and its formula is as follows:

[0079] e1 = K 12 *e 12 +I 12 ∫e 12 *dt

[0080] Among them, K 12 The proportional increment of the first motor relative to the second motor; I 12 This is the integral increment of the first motor relative to the second motor.

[0081] Furthermore, the proportional increment K of the first motor relative to the second motor 12 The integral increment I of the first motor relative to the second motor 12 The speed deviation levels of the first motor and the second motor are determined by the following: positive large deviation, positive small deviation, zero deviation, negative small deviation, and negative large deviation.

[0082] Specifically, the proportional increment K 12 With integral increment I 12 The possible values ​​are shown in Table 1:

[0083] Table 1 Proportional Increment K 12 With integral increment I 12 The value of

[0084]

[0085] Step S4, based on the speed ω1 of the first motor and the speed evaluation function The evaluation speed following error ε1 of the first sub-motor is obtained.

[0086] Specifically, define an evaluation function that can characterize the speed of all motors:

[0087]

[0088] Among them, a i is the weighting coefficient; i is the i-th motor, in this embodiment i = 1, 2.

[0089] Specifically, the evaluation function is a function related to the speed of each motor, which can effectively characterize the speed of all motors. In this embodiment, the evaluation function is related to the speed of each motor and is a function that can effectively characterize the speed of all motors. For example, when the weighting coefficients a1 = 1 / 2 and a2 = 1 / 2, then...

[0090] The formula for evaluating the speed following error ε1 of the first motor is as follows:

[0091]

[0092] It should be noted that in control systems, the actual errors and their rates of change are typically considered, followed by a series of data adjustments. Since fixed gain only includes the motor's moment of inertia, significant load fluctuations will result in corresponding errors. Fluctuations in the speed of any one motor will interfere with the speeds of the others, indicating a constantly changing state. In this embodiment, a fuzzy PID controller replaces the fixed gain. If motor fluctuations occur, the fuzzy PID controller will take effect, quickly reducing the following errors between motors and bringing them towards a stable state, approaching zero.

[0093] Step S5, as follows Figure 7 As shown, the speed compensator output e1 of the first motor, the evaluation speed following error ε1 of the first sub-motor, and the speed ω1 of the first motor are input into the fuzzy PID controller for fuzzy PID control, and the resulting control signal u1 is used to control the speed of the first sub-motor.

[0094] Specifically, in step S51, the input of the fuzzy PID controller is the deviation value e. The initial control parameters of the fuzzy PID controller are corrected using the deviation value e and the deviation change rate ec to obtain the corrected control parameters.

[0095] Furthermore, the deviation value e is calculated using the following formula:

[0096] e = e1 + ε1 - ω1

[0097] Where e1 is the output of the speed compensator of the first motor; ε1 is the evaluation speed following error of the first motor; ω1 is the speed of the first motor;

[0098] The rate of change of deviation ec is the derivative of the deviation value e, denoted as The rate of change of deviation includes a continuously changing independent variable and an indication of future control trends.

[0099] It should be noted that, as Figure 6 The control principle of fuzzy PID, as shown, involves fuzzifying the precise values ​​of the deviation e and the rate of change of deviation ec. These values ​​are then incorporated into the corresponding universe of discourse through membership functions and assigned fuzzy linguistic values. Fuzzy inference is then performed using fuzzy rules, and finally, the results are defuzzified using a proportional factor to obtain the control parameter K. p K i and K d .

[0100] Specifically, the control parameter K p The proportional control coefficient is used to accelerate the system's response speed and improve its control accuracy; control parameter K i This represents the integral adjustment coefficient, used to eliminate residuals; control parameter K d This represents the differential adjustment coefficient, used to improve the dynamic performance of the system.

[0101] Furthermore, to ensure the global stability of the control system under the fuzzy self-tuning PID control law, fuzzy adjustment K should be used. p K i and K d The deviation strategy involves obtaining the initial PID parameters K before implementing control. p0 K i0 and K d0 In this embodiment, K p0 K i0 and K d0 The values ​​are 20, 1, and 0.5 respectively. During control, the dynamic values ​​ΔK of the three parameters of the PID controller are continuously calculated based on the deviation value e and the rate of change of deviation ec. p ΔK i and ΔK d Finally, the PID control parameters are calculated using the following formula:

[0102] K p =K p0 +ΔK p

[0103] K i =K i0+ΔK i

[0104] K d =K d0 +ΔK d

[0105] Specifically, determine the proportionality coefficient K. p When considering the dynamic value, the deviation levels of the deviation value e and the deviation change rate ec include: large positive deviation, small positive deviation, zero deviation, small negative deviation, and large negative deviation; in this embodiment, the dynamic value ΔK p The reference values ​​are shown in Table 2:

[0106] Table 2K p Dynamic value reference

[0107]

[0108] Furthermore, the integral coefficient K is determined. i When the dynamic value is defined, the deviation level of the deviation value e includes: large positive deviation, small positive deviation, zero deviation, small negative deviation, and large negative deviation; the deviation level of the deviation change rate ec includes: small positive deviation, zero deviation, small negative deviation, and large negative deviation; in this embodiment, the dynamic value ΔK i The reference values ​​are shown in Table 3:

[0109] Table 3K i Dynamic value reference

[0110]

[0111] Furthermore, the differential coefficient K is determined. d When the dynamic value is defined, the deviation level of the deviation value e includes: large positive deviation, small positive deviation, zero deviation, small negative deviation, and large negative deviation; the deviation level of the deviation change rate ec includes: small positive deviation, zero deviation, small negative deviation, and large negative deviation; in this embodiment, the dynamic value ΔK d The reference values ​​are shown in Table 4:

[0112] Table 4K d Dynamic value reference

[0113]

[0114] Step S52: Use the corrected control parameters and the amplification factor K1 to amplify the deviation value e to obtain the control signal u1.

[0115] Specifically, the amplification factor K1 is a proportional coefficient obtained through experiments; for small deviation values ​​e of the motor, adding the amplification factor makes it easier to detect and correct errors.

[0116] In step S53, the control signal u1 controls the speed of the first sub-motor, so that the mesh plate motors achieve synchronization.

[0117] Finally, the speed synchronization motors are made to track the given reference speed through the controllers of each sub-motor system, thereby improving the control performance of the mesh plate and ensuring that the mesh plate motion mechanism can reach the designated position in real time, synchronously and with high precision.

[0118] This invention uses an STM32H7 as the motion control center, employing dual motors to drive the stencil for printing, ensuring rapid analysis, processing, and calculation of the printed information. The dual-motor speed control utilizes an improved deviation-coupled control structure, introducing feedforward PI control. During motor operation, when sudden load changes occur, targeted compensation is performed to achieve synchronization between the motors while maintaining good dynamic and static performance. For speed fluctuations in the dual motors, real-time correction is achieved through dynamic compensation, combined with a speed evaluation function. The difference between the reference value and the motor feedback speed is used for fuzzy PID control, and the result is ultimately used as the control signal for the motor driver, achieving high-precision synchronous control. This can effectively shorten the manufacturing cycle of aerospace structural components and enable the fabrication of large-size, highly complex ceramic structural components.

[0119] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A 3D ceramic printing synchronization control method based on an STM32H7 chip, characterized by, The STM32H7 chip is a motion mechanism control center of the 3D ceramic printing, and synchronously controls double motor motions. Sampling the rotating speed of the double motors to obtain the first motor speed and the second motor speed ; determining a following error according to a proportional relationship of the double-motor speed ; wherein the following error , and the formula is as follows: ； wherein, is the synchronization proportionality coefficient of the first motor; is the synchronization proportionality coefficient of the second motor; According to the following error The first motor is fed forward fuzzy PI control to obtain the speed compensator output of the first motor ; wherein the speed compensator output of the first motor The formula is as follows: ； wherein, is a proportional increment of the first motor relative to the second motor; is an integral increment of the first motor relative to the second motor; According to the speed of the first motor , a speed evaluation function , an evaluation speed following error of the first sub-motor ; wherein the evaluation speed following error is calculated according to the following formula: ； wherein is the speed of the 1st motor; is the speed evaluation; the speed compensator output of the first motor the evaluation speed follow-up error of the first sub-motor the speed of the first motor input a fuzzy PID controller to perform fuzzy PID control to obtain a control signal control the speed of the first sub-motor 2. The method of claim 1, wherein, a proportional increment of the first motor relative to the second motor an integral increment of the first motor relative to the second motor determined by a first motor and second motor speed deviation level; wherein the first motor and second motor speed deviation level includes: positive large deviation, positive small deviation, zero deviation, negative small deviation, negative large deviation.

3. The method of claim 1, wherein, The speed evaluation which is formulated as follows: wherein, is a weighting factor; i is a motor number, taking a value of 1 or 2.

4. The method of claim 1, wherein, The input of the fuzzy PID controller is a deviation value The initial control parameter of the fuzzy PID controller is corrected by using the deviation value and a deviation change rate to obtain a corrected control parameter using the modified control parameter and the deviation value amplification coefficient control signal .

5. The method of claim 4, wherein, the bias value which is given by the formula: wherein, is the speed compensator output for the first motor; is the evaluation speed follow-up error for the first motor; is the speed of the first motor; the rate of change of the deviation is the derivative of the deviation value , denoted by .

6. The method of claim 5, wherein, The control parameters include a proportional coefficient , an integral coefficient , and a differential coefficient ​ the bias value and a bias change rate correcting the initial control parameters of the fuzzy PID controller to obtain corrected control parameters, comprising: determining a dynamic value of the control parameter based on the deviation value and a rate of change of the deviation of the deviation level The corrected control parameter is a total value of the initial control parameter and the dynamic value of the control parameter.

7. The method of claim 6, wherein, said deviation value and a deviation change rate a deviation level, and determining a dynamic value of said control parameter, wherein: determining the proportional coefficient determining the dynamic value of the proportional coefficient determining the deviation level of the deviation value and the deviation change rate include: positive large deviation, positive small deviation, zero deviation, negative small deviation, negative large deviation; determining the dynamic value of the integral coefficient and the differential coefficient The deviation level of the deviation value includes positive large deviation, positive small deviation, zero deviation, negative small deviation, negative large deviation; the deviation level of the deviation change rate includes positive small deviation, zero deviation, negative small deviation, negative large deviation.

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