CN111552202A - Load simulation method, device and system and process controller - Google Patents
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Abstract
The embodiment of the invention discloses a load simulation method, a device, a system and a process controller. The method comprises the following steps: receiving M load data points from an upper computer; determining an interpolation function based on the M load data points; sampling N load data points from the interpolation function; generating a driver control instruction based on the N load data points; where N is greater than M, and both M and N are positive integers. According to the embodiment of the invention, the load data amount is increased through interpolation processing, the driver control instruction generated based on the load data is more continuous, the output of the motor connected with the driver is smoother, and the problem of jump of the motor output is effectively alleviated.
Description
Technical Field
The present invention relates to the field of simulation technologies, and in particular, to a load simulation method, apparatus, system, and process controller.
Background
Simulation (Simulation), generally speaking, is based on experiments or training, and aims at real or abstract systems, transactions or processes to build a model to characterize key characteristics (key characteristics) or behaviors and functions thereof, and to systematize and formulate the model so as to simulate the key characteristics. The load simulation system can simulate respective load parameters in an actual system, such as the output of a simulated load force or a simulated load torque through the motor.
The current load simulation system mainly comprises a computer, a Programmable Logic Controller (PLC), a motor driver and a motor. The load curve is planned on a computer, and data on the load curve is transmitted to the PLC through a communication mode such as Ethernet (Ethernet). Then, the PLC converts the data into a control command for controlling the motor driver, which then drives the motor output load based on the control command.
However, since the communication method such as Ethernet transmits discretized data and the amount of data is small, the command output from the PLC to the motor driver is not continuous, and the output of the motor driven by the motor driver may jump.
Disclosure of Invention
The embodiment of the invention provides a load simulation method, a device, a system and a process controller.
The technical scheme of the embodiment of the invention is as follows:
a method for load simulation, the method being applied to a process controller (technology controller), the method comprising:
receiving M load data points from an upper computer;
determining an interpolation function based on the M load data points;
sampling N load data points from the interpolation function, wherein N is greater than M, and both M and N are positive integers;
determining a driver control command based on the N load data points.
Therefore, in the embodiment of the invention, the interpolation processing is executed for the received load data with less number, so that more load data can be acquired, and the generated drive control instruction is more continuous and smooth, thereby slowing down or overcoming the jump problem of the motor output.
In one embodiment, the determining an interpolation function based on the M load data points comprises at least one of:
determining a Lagrangian interpolation polynomial based on the M load data points;
determining a newton interpolation polynomial based on the M load data points;
determining a hermitian interpolation polynomial based on the M load data points;
a cubic spline interpolation function is determined based on the M load data points.
Therefore, the embodiment of the invention can adopt a plurality of interpolation modes and has wide application.
In one embodiment, the determining an interpolation function based on the M load data points comprises: calling a motion control module; inputting the M load data points into the motion control module; enabling the motion control module to determine an interpolation function based on the M load data points; wherein the motion control module is built into or has an accessible connection with the process controller.
Therefore, the embodiment of the invention can realize the fast interpolation by calling the motion control module which is internally arranged in the process controller or has accessible connection with the process controller and utilizing the existing interpolation algorithm in the motion control module, thereby reducing the cost.
In one embodiment, the N load data points comprise the M load data points.
Therefore, the embodiment of the invention can preferentially utilize the original data and improve the simulation accuracy.
A load simulation device, which is applied to a process controller, comprises:
the receiving module is used for receiving M load data points from the upper computer;
an interpolation module to determine an interpolation function based on the M load data points;
a sampling module for sampling N load data points from the interpolation function, wherein N is greater than M, and both M and N are positive integers;
an instruction generation module to determine a driver control instruction based on the N load data points.
Therefore, in the embodiment of the invention, the interpolation processing is executed for the received load data with less number, so that more load data can be acquired, and the generated drive control instruction is more continuous and smooth, thereby slowing down or overcoming the jump problem of the motor output.
In one embodiment, the interpolation module is configured to perform at least one of:
determining a Lagrangian interpolation polynomial based on the M load data points;
determining a newton interpolation polynomial based on the M load data points;
determining a hermitian interpolation polynomial based on the M load data points;
a cubic spline interpolation function is determined based on the M load data points.
Therefore, the embodiment of the invention can adopt a plurality of interpolation modes and has wide application.
In one embodiment, further comprising:
a motion control module built into or having an accessible connection with the process controller;
the interpolation module is used for calling the motion control module; inputting the M load data points into the motion control module; enabling the motion control module to determine an interpolation function based on the M load data points.
Therefore, the embodiment of the invention can realize the fast interpolation by calling the motion control module which is internally arranged in the process controller or has accessible connection with the process controller and utilizing the existing interpolation algorithm in the motion control module, thereby reducing the cost.
A load simulation system, comprising:
the upper computer is used for generating a load curve;
the process controller is used for receiving M load data points in the load curve from the upper computer; determining an interpolation function based on the M load data points; sampling N load data points from the interpolation function, wherein N is greater than M, and both M and N are positive integers; determining a driver control command based on the N load data points;
a driver to drive the motor based on the driver control command.
Therefore, the embodiment of the invention executes interpolation processing aiming at the received load data with less number, and can acquire more load data, so that the generated drive control instruction is more continuous and smooth, thereby slowing down or overcoming the jump problem of the motor output.
A process controller, comprising:
a memory;
a processor;
wherein the memory has stored therein an application executable by the processor for causing the processor to perform the load simulation method as defined in any one of the above.
The embodiment of the invention also provides a process controller with a memory-processor architecture, which can slow down or overcome the problem of jump of motor output.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, implements a load simulation method as in any one of the above.
Embodiments of the present invention also provide a computer-readable storage medium having a memory-processor architecture that can mitigate or overcome the problem of a jump in motor output.
Drawings
FIG. 1 is an exemplary flow chart of a load simulation method of the present invention.
Fig. 2 is a schematic diagram of load data transmission according to the present invention.
Fig. 3 is an exemplary block diagram of the load simulation apparatus of the present invention.
Fig. 4 is an exemplary block diagram of a process controller of the present invention.
FIG. 5 is an exemplary block diagram of a load simulation system of the present invention.
FIG. 6 is an exemplary schematic of a load design curve in a power plant scenario based on the present invention.
FIG. 7 is an exemplary schematic diagram of a load actual curve in a power plant scenario based on the present invention.
Wherein the reference numbers are as follows:
Detailed Description
In order to make the technical scheme and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the detailed description and specific examples, while indicating the scope of the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention.
For simplicity and clarity of description, the invention will be described below by describing several representative embodiments. Numerous details of the embodiments are set forth to provide an understanding of the principles of the invention. It will be apparent, however, that the invention may be practiced without these specific details. Some embodiments are not described in detail, but rather are merely provided as frameworks, in order to avoid unnecessarily obscuring aspects of the invention. Hereinafter, "including" means "including but not limited to", "according to … …" means "at least according to … …, but not limited to … … only". In view of the language convention of chinese, the following description, when it does not specifically state the number of a component, means that the component may be one or more, or may be understood as at least one.
FIG. 1 is an exemplary flow chart of a load simulation method of the present invention. The method is applied to a process controller.
The process controller is a controller for implementing various process control application scenarios. For example, the process controller may be implemented as a PID controller for controlling physical quantities of pressure, tension, temperature, etc., or as a motion controller for converting a predetermined control scheme, a programmed command into a desired mechanical motion, implementing precise position control, speed control, acceleration control, torque or force control of the mechanical motion, etc.
As shown in fig. 1, the method includes:
step 101: the process controller receives M load data points from the upper computer.
Here, smooth load curves have been planned in advance in an upper computer (e.g., various types of microcomputers) based on various mathematical tools. For example, the horizontal axis of the load curve may be a time axis, and the vertical axis is a load parameter (such as load force, load torque, etc.) to be simulated.
The process controller obtains data in the load curve from the upper computer through a communication protocol based on a wired interface or a wireless interface. For example, the communication protocol may be implemented as an ethernet communication protocol, preferably TCP/IP protocol.
Because the data transmission process between the upper computer and the process controller is a discretization process, M load data points on the load curve are actually received by the process controller. Each load data point may include a lateral axis value (e.g., a time value) and a longitudinal axis value (e.g., a load force, a load torque, etc.). The specific value of M may be determined by the cycle time of the communication protocol between the host computer and the process controller. The shorter the cycle period of the communication protocol is, the larger the specific numerical value of M is; the longer the cycle period of the communication protocol, the smaller the specific value of M.
Preferably, the wired interface between the upper computer and the process controller comprises at least one of: a universal serial bus interface, a controller area network interface, a serial port, etc.; the wireless interface between the upper computer and the process controller comprises at least one of the following components: infrared interface, near field communication interface, bluetooth interface, zigbee interface, wireless broadband interface, and the like.
The above exemplary description describes a typical example of an interface between an upper computer and a process controller, and those skilled in the art will appreciate that this description is merely exemplary and is not intended to limit the scope of embodiments of the present invention.
Step 102: the process controller determines an interpolation function based on the M load data points.
Here, the process controller determines an interpolation function based on the M load data points. Specifically, the process controller interpolates the continuous function over the M load data points such that the continuous curve passes through all of the M load data points.
In one embodiment, determining the interpolation function based on the M load data points comprises at least one of:
(1) determining a Lagrange interpolation polynomial based on the M load data points; (2) determining a Newton interpolation polynomial based on the M load data points; (3) determining an Hermite interpolation polynomial based on the M load data points; (4) determining a cubic spline interpolation function based on the M load data points, and so on.
While specific examples of determining an interpolation function have been described above for purposes of illustration, those skilled in the art will appreciate that this description is illustrative only and is not intended to limit the scope of embodiments of the present invention.
In one embodiment, determining an interpolation function based on the M load data points in step 102 includes: calling a motion control module; inputting the M load data points into a motion control module; enabling the motion control module to determine an interpolation function based on the M load data points; wherein the motion control module is built into or has an accessible connection with the process controller. The motion control module comprises a cam algorithm used for controlling the motor, and the cam algorithm comprises an interpolation function. The process controller may utilize interpolation functionality included in the cam algorithm to achieve fast interpolation by invoking the motion control module.
Therefore, the embodiment of the invention can realize fast interpolation calculation by directly calling the interpolation function in the motion control module without additionally setting the interpolation function, thereby saving the cost.
Step 103: the process controller samples N load data points from the interpolation function; where N is greater than M, and both M and N are positive integers.
Here, the process controller samples N load data points from the interpolation function, where each load data point may include a horizontal axis value (e.g., a time value) and a vertical axis value (e.g., a load force, a load torque, etc.). Wherein N is larger than M, and the specific value of N can be set by the user. When the specific value of N is larger, more load data points can be obtained, but the sampling time is correspondingly increased; when the specific value of N is smaller, fewer load data points are obtained, but the sampling time is correspondingly reduced.
In one embodiment, the N load data points comprise M load data points. Therefore, the embodiment of the invention can preferentially utilize the original data and improve the simulation accuracy.
Step 104: the process controller generates a driver control instruction based on the N load data points.
Here, the process controller determines a driver control command for controlling the driver based on the N load data points. The specific process of the process controller determining the driver control command based on the N load data points includes: (1) and an input sampling stage: the process controller writes the N load data points into the input status register in sequence in a predetermined scanning mode, immediately closes the data input, and enters a program execution stage. (2) And a program execution stage: the process controller scans and executes each instruction according to the sequence stored by the user program instruction, corresponding operation is executed aiming at each load data point, the operation result is written into the output state register, and all the contents in the output state register are changed along with the execution of the program. (3) And an output refreshing stage: when all the instructions are executed, the process controller generates a driver control instruction which can be used for controlling the driver based on the on-off state of the output state register.
It can be seen that the number of load data points (i.e., N) at which the driver control instructions are generated is greater than the number of load data points (i.e., M) received, and thus the driver control instructions are more continuous, and thus the output of the motor driven by the driver is smoother.
Fig. 2 is a schematic diagram of load data transmission according to the present invention. In fig. 2:
the first diagram from left to right is a smooth load curve planned in the microcomputer, wherein the horizontal axis (X axis) of the load curve is a time axis, and the vertical axis (Y axis) is a load parameter to be simulated. The smoothed load curve, after being transmitted to the process controller, will be discretized into a number of load data points.
The second sub-graph in left-to-right order is a schematic diagram of interpolation processing. It can be seen that the continuous function is interpolated on the basis of the load data points received by the process controller so that the final continuous curve passes through all the load data points.
The third sub-graph in the left-to-right sequence is a schematic diagram of the sampling process. Therefore, a large number of load data points can be sampled from the continuous curve after the interpolation processing. Then, based on the sampled load data points, driver control instructions for controlling the driver may be generated. The driver may drive the motor output based on the driver control command.
The fourth sub-diagram from left to right is a schematic diagram of the motor output. Therefore, the load curve finally output by the motor is smooth and is close to the load curve planned in the microcomputer.
Based on the above description, it can be understood that the number of load data points in the embodiment of the present invention is significantly increased, so that the driver control instruction generated based on the load data is more continuous, and the problem of jump of the motor output is effectively alleviated.
For example, in the data transmission phase between the upper computer and the process controller, the process controller may receive one load data point every 10 milliseconds (ms) based on the TCP/IP protocol, and may receive 100 load data points in one second. After determining the interpolation function based on the 100 load data points, 10000 load data points can be sampled from the interpolation function, wherein each load data point corresponds to a pulse sequence for controlling the driver. The 10000 load data points can be used by the process controller to generate a driver control command comprising 10000 pulse trains and send the 10000 pulse trains to the motor driver in one second based on an industrial control bus (e.g., Profinet IO, EtherCAT, etc.) that can guarantee real-time performance. The motor driver controls the motor to output 10000 load values in time sequence, thereby realizing smooth motor output.
While embodiments of the present invention have been described in detail with reference to specific control scenarios as examples, those skilled in the art will appreciate that such descriptions are merely exemplary and are not intended to limit the scope of embodiments of the present invention.
Based on the above description, the embodiment of the invention further provides a load simulation device.
Fig. 3 is an exemplary block diagram of the load simulation apparatus of the present invention. The apparatus 300 is applied to a process controller.
As shown in fig. 3, the apparatus 300 includes:
a receiving module 301, configured to receive M load data points from an upper computer;
an interpolation module 302 for determining an interpolation function based on the M load data points;
a sampling module 303 for sampling N load data points from the interpolation function, where N is greater than M, and M and N are both positive integers;
an instruction generation module 304 for determining a driver control instruction based on the N load data points.
In one embodiment, the interpolation module 302 is configured to perform at least one of the following: determining a Lagrange interpolation polynomial based on the M load data points; determining a newton interpolation polynomial based on the M load data points; determining an hermitian interpolation polynomial based on the M load data points; a cubic spline interpolation function is determined based on the M load data points, and so on.
In one embodiment, further comprising: a motion control module 305 built into or having an accessible connection with a process controller; wherein the interpolation module 302 is used for calling the motion control module 305; inputting the M load data points into the motion control module 305; the enable motion control module 305 determines an interpolation function based on the M load data points.
Based on the above description, the embodiments of the present invention also provide a process controller having a memory-processor structure.
Fig. 4 is an exemplary block diagram of a process controller of the present invention.
As shown in fig. 4, the motion controller 400 includes: a memory 401; a processor 402; in which a memory 401 has stored therein an application program executable by the processor 402 for causing the processor 402 to perform the load simulation method as described in any of the above.
The memory 401 may be embodied as various storage media such as an Electrically Erasable Programmable Read Only Memory (EEPROM), a Flash memory (Flash memory), and a Programmable Read Only Memory (PROM). The processor 402 may be implemented to include one or more central processors or one or more field programmable gate arrays that integrate one or more central processor cores. In particular, the central processor or central processor core may be implemented as a CPU or MCU or DSP, etc.
The embodiment of the invention also provides a load simulation system. FIG. 5 is an exemplary block diagram of a load simulation system of the present invention.
As shown in fig. 5, the load simulation system 500 includes:
the upper computer 501 is used for generating a load curve;
a process controller 502 for receiving M load data points in a load curve from the upper computer 501; determining an interpolation function based on the M load data points; sampling N load data points from an interpolation function, wherein N is greater than M, and both M and N are positive integers; determining a driver control command based on the N load data points;
a driver 503 for driving the motor based on the driver control instruction.
FIG. 6 is an exemplary schematic diagram of a load design curve in a power plant scenario based on the present invention. FIG. 7 is an exemplary schematic diagram of a load actual curve in a power plant scenario based on the present invention. It can be seen that fig. 6 is substantially identical to the curves of fig. 7, enabling smooth simulation with high accuracy.
It should be noted that not all steps and modules in the above flows and structures are necessary, and some steps or modules may be omitted according to actual needs. The execution order of the steps is not fixed and can be adjusted as required. The division of each module is only for convenience of describing adopted functional division, and in actual implementation, one module may be divided into multiple modules, and the functions of multiple modules may also be implemented by the same module, and these modules may be located in the same device or in different devices.
The hardware modules in the various embodiments may be implemented mechanically or electronically. For example, a hardware module may include a specially designed permanent circuit or logic device (e.g., a special purpose processor such as an FPGA or ASIC) for performing specific operations. A hardware module may also include programmable logic devices or circuits (e.g., including a general-purpose processor or other programmable processor) that are temporarily configured by software to perform certain operations. The implementation of the hardware module in a mechanical manner, or in a dedicated permanent circuit, or in a temporarily configured circuit (e.g., configured by software), may be determined based on cost and time considerations.
The present invention also provides a machine-readable storage medium storing instructions for causing a machine to perform a method as described herein. Specifically, a system or an apparatus equipped with a storage medium on which a software program code that realizes the functions of any of the embodiments described above is stored may be provided, and a computer (or a CPU or MPU) of the system or the apparatus is caused to read out and execute the program code stored in the storage medium. Further, part or all of the actual operations may be performed by an operating system or the like operating on the computer by instructions based on the program code. The functions of any of the above-described embodiments may also be implemented by writing the program code read out from the storage medium to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion unit connected to the computer, and then causing a CPU or the like mounted on the expansion board or the expansion unit to perform part or all of the actual operations based on the instructions of the program code.
Examples of the storage medium for supplying the program code include floppy disks, hard disks, magneto-optical disks, optical disks (e.g., CD-ROMs, CD-R, CD-RWs, DVD-ROMs, DVD-RAMs, DVD-RWs, DVD + RWs), magnetic tapes, nonvolatile memory cards, and ROMs. Alternatively, the program code may be downloaded from a server computer or the cloud by a communication network.
"exemplary" means "serving as an example, instance, or illustration" herein, and any illustration, embodiment, or steps described as "exemplary" herein should not be construed as a preferred or advantageous alternative. For the sake of simplicity, the drawings are only schematic representations of the parts relevant to the invention, and do not represent the actual structure of the product. In addition, in order to make the drawings concise and understandable, components having the same structure or function in some of the drawings are only schematically illustrated or only labeled. In this document, "a" does not mean that the number of the relevant portions of the present invention is limited to "only one", and "a" does not mean that the number of the relevant portions of the present invention "more than one" is excluded. In this document, "upper", "lower", "front", "rear", "left", "right", "inner", "outer", and the like are used only to indicate relative positional relationships between relevant portions, and do not limit absolute positions of the relevant portions.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A method (100) for load simulation, the method (100) being applied to a process controller, the method (100) comprising:
receiving M load data points from an upper computer (101);
determining an interpolation function (102) based on the M load data points;
sampling N load data points from the interpolation function, where N is greater than M, and M and N are both positive integers (103);
a driver control command is generated based on the N load data points (104).
2. The load simulation method (100) according to claim 1, wherein the determining an interpolation function (102) based on the M load data points comprises at least one of:
determining a Lagrangian interpolation polynomial based on the M load data points;
determining a newton interpolation polynomial based on the M load data points;
determining a hermitian interpolation polynomial based on the M load data points;
a cubic spline interpolation function is determined based on the M load data points.
3. The load simulation method (100) according to claim 1,
the determining an interpolation function (102) based on the M load data points comprises: calling a motion control module; inputting the M load data points into the motion control module; enabling the motion control module to determine an interpolation function based on the M load data points; wherein the motion control module is built into or has an accessible connection with the process controller.
4. The load simulation method (100) of claim 1, wherein the N load data points comprise the M load data points.
5. A load simulation apparatus (300), the apparatus (300) being adapted for use in a process controller, the apparatus (300) comprising:
a receiving module (301) for receiving M load data points from an upper computer;
an interpolation module (302) for determining an interpolation function based on the M load data points;
a sampling module (303) for sampling N load data points from the interpolation function, where N is greater than M, and both M and N are positive integers;
an instruction generation module (304) to generate a driver control instruction based on the N load data points.
6. The load simulating device (300) of claim 5,
the interpolation module (302) is configured to perform at least one of:
determining a Lagrangian interpolation polynomial based on the M load data points;
determining a newton interpolation polynomial based on the M load data points;
determining a hermitian interpolation polynomial based on the M load data points;
a cubic spline interpolation function is determined based on the M load data points.
7. The load emulating device (300) of claim 5, further comprising:
a motion control module (305) built into or having an accessible connection with the process controller;
wherein the interpolation module (302) is configured to invoke the motion control module (305); inputting the M load data points into the motion control module (305); enabling the motion control module (305) to determine an interpolation function based on the M load data points.
8. A load simulation system (500), comprising:
the upper computer (501) is used for generating a load curve;
a process controller (502) for receiving M load data points in a load curve from an upper computer (501); determining an interpolation function based on the M load data points; sampling N load data points from the interpolation function, wherein N is greater than M, and both M and N are positive integers; determining a driver control command based on the N load data points;
a driver (503) for driving the motor based on the driver control instruction.
9. A process controller (400), comprising:
a memory (401);
a processor (402);
wherein the memory (401) has stored therein an application executable by the processor (402) for causing the processor (402) to perform the load simulation method (100) as claimed in any one of claims 1 to 4.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a load simulation method according to any one of claims 1 to 4.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000029534A (en) * | 1998-07-08 | 2000-01-28 | Kobe Steel Ltd | Controller |
| CN103699013A (en) * | 2013-09-28 | 2014-04-02 | 北京工业大学 | Method for effectively improving speed and precision of in-loop real-time simulation of motor hardware |
| US20170346433A1 (en) * | 2016-05-25 | 2017-11-30 | University Of Connecticut | Systems and methods of optimizing operation efficiency of a motor drive |
| CN107450471A (en) * | 2017-08-31 | 2017-12-08 | 华中科技大学 | A kind of method that cutter path parameter arc length is realized based on cubic PH curve interpolation |
| CN109760063A (en) * | 2019-03-15 | 2019-05-17 | 京东方科技集团股份有限公司 | Control method, device, equipment and the storage medium of parallel robot |
| CN111030552A (en) * | 2019-12-09 | 2020-04-17 | 常州节卡智能装备有限公司 | Synchronous control method of servo driver and servo driver |
-
2020
- 2020-06-02 CN CN202010489805.2A patent/CN111552202A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2000029534A (en) * | 1998-07-08 | 2000-01-28 | Kobe Steel Ltd | Controller |
| CN103699013A (en) * | 2013-09-28 | 2014-04-02 | 北京工业大学 | Method for effectively improving speed and precision of in-loop real-time simulation of motor hardware |
| US20170346433A1 (en) * | 2016-05-25 | 2017-11-30 | University Of Connecticut | Systems and methods of optimizing operation efficiency of a motor drive |
| CN107450471A (en) * | 2017-08-31 | 2017-12-08 | 华中科技大学 | A kind of method that cutter path parameter arc length is realized based on cubic PH curve interpolation |
| CN109760063A (en) * | 2019-03-15 | 2019-05-17 | 京东方科技集团股份有限公司 | Control method, device, equipment and the storage medium of parallel robot |
| CN111030552A (en) * | 2019-12-09 | 2020-04-17 | 常州节卡智能装备有限公司 | Synchronous control method of servo driver and servo driver |
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Application publication date: 20200818 |