WO2024005136A1 - 制御パラメータの生成方法、プログラム、記録媒体、および、制御パラメータの生成装置 - Google Patents

制御パラメータの生成方法、プログラム、記録媒体、および、制御パラメータの生成装置 Download PDF

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Publication number
WO2024005136A1
WO2024005136A1 PCT/JP2023/024161 JP2023024161W WO2024005136A1 WO 2024005136 A1 WO2024005136 A1 WO 2024005136A1 JP 2023024161 W JP2023024161 W JP 2023024161W WO 2024005136 A1 WO2024005136 A1 WO 2024005136A1
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Prior art keywords
time
control parameter
evaluation index
index data
control
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English (en)
French (fr)
Japanese (ja)
Inventor
俊策 利弘
太一 佐藤
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Panasonic Intellectual Property Management Co Ltd
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Panasonic Intellectual Property Management Co Ltd
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Priority to JP2024530958A priority Critical patent/JPWO2024005136A1/ja
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Program-control systems
    • G05B19/02—Program-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of program data in numerical form
    • G05B19/4155—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of program data in numerical form characterised by program execution, i.e. part program or machine function execution, e.g. selection of a program
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D3/00—Control of position or direction
    • G05D3/12—Control of position or direction using feedback
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C3/00—Registering or indicating the condition or the working of machines or other apparatus, other than vehicles
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P29/00—Arrangements for regulating or controlling electric motors, appropriate for both AC and DC motors

Definitions

  • the present invention relates to a method of generating control parameters, and particularly to a method of generating control parameters used in production equipment.
  • an object of the present disclosure is to provide a control parameter generation method etc. that can generate appropriate control parameters.
  • a control parameter generation method includes generating a control parameter by a control parameter generation device, using the control parameter by a production device, using a sensor to check the state of the production device, and displaying at least a part of the control parameter by a display device. Generate control parameters.
  • the production device includes a servo motor, a control circuit that controls the servo motor, a memory that stores the control parameters used by the control circuit to control the servo motor, and a drive target driven by the servo motor. have things and.
  • the sensor detects the driven object after a time when the driven object reaches a permissible position where it can be evaluated that the driven object has reached the predetermined target position based on a command for changing the position of the driven object to a predetermined target position. Measures the position of an object and outputs measurement data representing the position.
  • the control parameter generation method includes the following method. Obtaining measurement data representing the position output from the sensor. Based on the measurement data, evaluation index data representing vibration of the driven object after a time when the driven object reaches the permissible position is generated in association with a generation time of the evaluation index data. Based on the evaluation index data, the control parameters are updated using a machine learning model that learns the relationship between the evaluation index data and the control parameters.
  • the updated control parameters are output to the production equipment for storage in the memory.
  • First time data indicating a first time when the vibration indicated by the evaluation index data exceeds a predetermined threshold value or a first number of updates of the control parameter up to the first time is output to the display device.
  • the evaluation index data generated up to the first time or the first number of updates is used. Resume updating control parameters.
  • a program according to another aspect of the present disclosure is a program for causing a computer of an information processing device connected to the production device to execute the control parameter generation method.
  • a recording medium is a recording medium on which a program for causing a computer of an information processing device connected to the production device to execute the control parameter generation method described above is recorded.
  • a control parameter generation device includes a control parameter generation device that is used by a production device, a sensor confirms a state of the production device, and a display device generates a control parameter that displays at least a part of the control parameter. It is a generation device.
  • the production device includes a servo motor, a first control circuit that controls the servo motor, a memory that stores control parameters used by the first control circuit to control the servo motor, and a servo motor that controls the servo motor.
  • the control parameter generation device further includes an input section, a second control circuit, and an output section.
  • the sensor detects the driven object after a time when the driven object reaches a permissible position where it can be evaluated that the driven object has reached the predetermined target position based on a command for changing the position of the driven object to a predetermined target position. Measures the position of an object and outputs measurement data representing the position.
  • the input unit acquires measurement data representing the position output from the sensor.
  • the second control circuit converts evaluation index data representing vibration of the driven object after a time when the driven object reaches the permissible position into a generation time of the evaluation index data.
  • the control parameters are updated using a machine learning model that is generated in association with each other and learns the relationship between the evaluation index data and the control parameters based on the evaluation index data.
  • the output unit outputs the updated control parameters to the production device for storage in the memory.
  • the output unit further outputs time data indicating a first time when the vibration indicated by the evaluation index data exceeds a predetermined threshold or a first number of updates of the allowable parameter up to the first time to the display device.
  • the second control circuit When the second control circuit is instructed to restart the update of the control parameters from the first time or from the first number of updates, the second control circuit further controls the control parameters from the first time or from the first number of updates until the first time or the first number of updates. The update of the control parameters is restarted from the evaluation index data generated in the above.
  • a control parameter generation device generates the control parameters
  • a production device uses a sensor with a processing device to check the state of the production device, and a display device displays at least one of the control parameters. Generate control parameters to display the section.
  • the production device includes a servo motor, a control circuit that controls the servo motor, a memory that stores the control parameters used by the control circuit to control the servo motor, and a drive target driven by the servo motor.
  • the sensor equipped with a processing device is configured to detect a time after a time when the driven object reaches an allowable position at which it can be evaluated that the driven object has reached the predetermined target position based on a command for changing the position of the driven object to a predetermined target position.
  • the position of the driven object is measured, and evaluation index data representing the vibration of the driven object after the time reached is output.
  • the control parameter generation method includes the following method. Evaluation index data representing vibration of the driven object after the time reached, which is output from the sensor with the processing device, is acquired in association with a generation time of the evaluation index data. Based on the evaluation index data, the control parameters are updated using a machine learning model that learns the relationship between the evaluation index data and the control parameters.
  • the updated control parameters are output to the production equipment for storage in the memory.
  • First time data indicating a first time when the vibration indicated by the evaluation index data exceeds a predetermined threshold or a first number of updates of the control parameter up to the first time is output to a display device in the generation system.
  • the evaluation index data obtained up to the first time or the first number of updates is used. Resume updating control parameters.
  • a program according to another aspect of the present disclosure is a program for causing a computer of an information processing device connected to the production device to execute the control parameter generation method.
  • a recording medium is a recording medium on which a program for causing a computer of an information processing device connected to the production device to execute the control parameter generation method described above is recorded.
  • a control parameter generation device is used in a production device, a sensor with a processing device checks the state of the production device, and a display device generates control parameters that display at least a part of the control parameters. , a control parameter generation device.
  • the production device includes a servo motor, a first control circuit that controls the servo motor, a memory that stores control parameters used by the first control circuit to control the servo motor, and a servo motor that controls the servo motor.
  • a driven object to be driven is used in a production device, a sensor with a processing device checks the state of the production device, and a display device generates control parameters that display at least a part of the control parameters.
  • the production device includes a servo motor, a first control circuit that controls the servo motor, a memory that stores control parameters used by the first control circuit to control the servo motor, and a servo motor that controls the servo motor.
  • the sensor equipped with a processing device is configured to detect a time after a time when the driven object reaches an allowable position at which it can be evaluated that the driven object has reached the predetermined target position based on a command for changing the position of the driven object to a predetermined target position.
  • the position of the driven object is measured, and evaluation index data representing the vibration of the driven object after the time reached is output.
  • the control parameter generation device includes an input section, a second control circuit, and an output section.
  • the input unit acquires evaluation index data representing vibration of the driven object after the time reached, which is output from the sensor with a processing device, in association with a generation time of the evaluation index data.
  • the second control circuit updates the control parameter based on the evaluation index data using a machine learning model that learns a relationship between the evaluation index data and the control parameter.
  • the output unit outputs the updated control parameters to the production device for storage in the memory.
  • the output unit further outputs time data indicating a first time when the vibration indicated by the evaluation index data exceeds a predetermined threshold or a first number of updates of the control parameter up to the first time to a display device.
  • the second control circuit is instructed to restart the update of the control parameters from the first time or from the first number of updates
  • the second control circuit further controls the control parameters from the first time or from the first number of updates until the first time or the first number of updates.
  • the update of the control parameters is restarted from the evaluation index data acquired in the above.
  • control parameter generation method program, recording medium, and control parameter generation device according to the above aspects of the present disclosure, appropriate control parameters can be generated.
  • FIG. 1 is a schematic diagram showing an overview of a control parameter generation system according to a first embodiment.
  • FIG. 2 is a block diagram showing the configuration of the control parameter generation system according to the first embodiment.
  • FIG. 3 is a schematic diagram showing an example of control parameters according to the first embodiment.
  • FIG. 4 is a schematic diagram showing an example of the transition of the positional deviation of the driven object with respect to the target position.
  • FIG. 5 is a data configuration diagram showing an example of measurement data according to the first embodiment.
  • FIG. 6 is a schematic diagram showing how the machine learning model according to the first embodiment outputs control parameters based on the result of learning the relationship between evaluation index data and control parameters.
  • FIG. 7 is a diagram illustrating an example of an image generated by the image generation unit according to the first embodiment.
  • FIG. 8 is a diagram illustrating an example of an image generated by the image generation unit according to the first embodiment.
  • FIG. 9 is a sequence diagram of the first control parameter adjustment process according to the first embodiment.
  • FIG. 10 is a diagram showing a flowchart of the first control parameter adjustment process according to the first embodiment.
  • FIG. 11 is a schematic diagram showing an overview of a control parameter generation system according to the second embodiment.
  • FIG. 12 is a block diagram showing the configuration of a control parameter generation system according to the second embodiment.
  • FIG. 13 is a sequence diagram of the second control parameter adjustment process according to the second embodiment.
  • FIG. 14 is a diagram showing a flowchart of the second control parameter adjustment process according to the second embodiment.
  • FIG. 15 is a schematic diagram showing an overview of the control parameter generation system according to the third embodiment.
  • FIG. 16 is a block diagram showing the configuration of a control parameter generation system according to the third embodiment.
  • FIG. 17 is a data configuration diagram showing an example of the data configuration of the adjustment history according to the third embodiment.
  • FIG. 18 is a data configuration diagram showing an example of the data configuration of a threshold determination history according to the third embodiment.
  • FIG. 19 is a diagram illustrating an example of an adjustment restart point designation image displayed by the display device according to the third embodiment.
  • FIG. 20 is a diagram showing part 1 of a flowchart of the third control parameter adjustment process according to the third embodiment.
  • FIG. 21 is a diagram showing a second flowchart of the third control parameter adjustment process according to the third embodiment.
  • FIG. 22 is a schematic diagram showing an overview of the control parameter generation system according to the fourth embodiment.
  • FIG. 17 is a data configuration diagram showing an example of the data configuration of the adjustment history according to the third embodiment.
  • FIG. 18 is a data configuration diagram showing an example of the data configuration of a threshold determination history according to the third
  • FIG. 23 is a block diagram showing the configuration of a control parameter generation system according to the fourth embodiment.
  • FIG. 24 is a diagram showing part 1 of a flowchart of the fourth control parameter adjustment process according to the fourth embodiment.
  • FIG. 25 is a diagram showing the second flowchart of the fourth control parameter adjustment process according to the fourth embodiment.
  • FIG. 26 is a block diagram showing the configuration of a generation device according to a modification.
  • FIG. 27 is a block diagram showing the configuration of a control parameter generation system according to a modification.
  • FIG. 28 is a diagram showing vibration waveforms of the production equipment.
  • control parameters used in production equipment equipped with a servo motor that drives a driven object have been manually adjusted.
  • the number of control parameters used in such production equipment may be as many as 80, and the number of parameters that actually need to be adjusted may range from 30 to 60.
  • the parameters to be adjusted differ depending on the drive target to be installed in the target production equipment, the application, etc.
  • Adjustment of such control parameters is necessary to suppress the generation of abnormal noise due to vibration, or to suppress the negative effect of vibration from the previous operation on the next operation when stopping an operation and starting the next operation. It is.
  • Patent Document 1 proposes adjusting such control parameters using a machine learning model.
  • skilled engineers adjust control parameters using all five human senses, such as checking abnormal noises by hearing and checking vibrations by sight and touch. Therefore, separate consideration is required as to what kind of data should be input to the machine learning model to effectively adjust the control parameters.
  • control parameters can be effectively adjusted by inputting the evaluation index data into a machine learning model.
  • the inventors investigated the cause of such a phenomenon and obtained the following findings.
  • the production equipment etc. to be adjusted may not be constantly monitored by humans. For this reason, during the period when control parameters are being adjusted, people walk around the production equipment, etc. to be adjusted, and large trucks, etc., drive on roads around factories, etc. where the production equipment, etc. to be adjusted are installed. Or, if the vibration of the production equipment, etc. to be adjusted is having an adverse effect on the adjustment of control parameters, due to the opening and closing of the entrance door of the room where the production equipment, etc. to be adjusted is installed. It turns out that there is.
  • Figure 28 is an example of the actual measurement data that served as the basis for the inventors to obtain the above knowledge.
  • Vibration waveform of the production equipment showing actual measurement data of the displacement of the production equipment measured by a laser displacement meter when the production equipment is traveling and actual measurement data of the displacement of the production equipment measured by the laser displacement meter when the production equipment is not traveling. It is.
  • the horizontal axis is the elapsed time
  • the vertical axis is the amplitude of the displacement of the production equipment.
  • the inventors discovered that when large trucks do not drive on the surrounding roads, even during a period when the amplitude of the production equipment is well within the threshold range, the surrounding roads are It was noticed that the vibration of the production equipment was not within the threshold when the truck was running. The inventors discovered that when the above-mentioned phenomenon occurs during the period when the control parameters are being adjusted, the vibration of the production equipment does not fall within the threshold range due to large trucks driving on the surrounding roads. It has been noticed that even after adjusting the control parameters, abnormal noises due to vibrations may still occur.
  • the inventors acquired and analyzed further measured data, and discovered that the vibration of production equipment does not fall within the threshold range due to people walking around the production equipment, and that the production equipment is not installed. It was confirmed that the vibration of the production equipment did not fall within the threshold range due to the opening and closing of the door at the entrance to the room. Furthermore, even if such a phenomenon occurs during the period when the control parameters are being adjusted, abnormal noises due to vibration may still occur even after the control parameters have been adjusted. I found out that there is.
  • a control parameter generation method includes a control parameter generation device that generates a control parameter, a production device that uses it, a sensor that confirms the state of the production device, and a display device that displays at least a part of the control parameter. Generate parameters.
  • the production device includes a servo motor, a control circuit that controls the servo motor, a memory that stores the control parameters used by the control circuit to control the servo motor, and a drive target driven by the servo motor. have things and.
  • the sensor detects the driven object after a time when the driven object reaches a permissible position where it can be evaluated that the driven object has reached the predetermined target position based on a command for changing the position of the driven object to a predetermined target position.
  • the control parameter generation method includes the following method. Obtaining measurement data representing the position output from the sensor. Based on the measurement data, evaluation index data representing vibration of the driven object after a time when the driven object reaches the permissible position is generated in association with a generation time of the evaluation index data. Based on the evaluation index data, the control parameters are updated using a machine learning model that learns the relationship between the evaluation index data and the control parameters. The updated control parameters are output to the production equipment for storage in the memory. First time data indicating a first time when the vibration indicated by the evaluation index data exceeds a predetermined threshold or a first number of updates of the control parameter up to the first time is output to a display device in the generation system. When an instruction is given to restart the update of the control parameters from the first time or the first number of updates, the evaluation index data generated up to the first time or the first number of updates is used. Resume updating control parameters.
  • control parameter generation method by updating the control parameters based on the evaluation index data indicating the vibration after the time when the permissible position has been reached, appropriate Control parameters can be generated.
  • control parameters can be adjusted from the evaluation index data generated up to the first time or the first update number of the control parameters.
  • the period for re-adjusting the control parameters can be shortened compared to when re-adjusting the control parameters from the beginning.
  • restarting the instructed update of the control parameters is from the first time among a plurality of times including the first time and the second time, or from the first update number and the second update.
  • the update of the control parameter may be restarted from the first update number among a plurality of update times including the number of update times.
  • First additional information indicating a first expected time required until parameter adjustment is completed is output.
  • the control parameter when restarting the update of the control parameter from the evaluation index data generated up to the second time or the second update number of the control parameter in association with the second time data is output.
  • the first predicted time and the second predicted time can be displayed on the display device.
  • the first predicted time may be shorter than the second predicted time.
  • control in the case of restarting the update of the control parameter from the evaluation index data generated up to the first time or the first number of updates of the control parameter in association with the first time data.
  • Third additional information indicating a first degree of improvement of the control parameter due to parameter adjustment is output. and the control parameter when restarting the update of the control parameter from the evaluation index data generated up to the second time or the second update number of the control parameter in association with the second time data.
  • Fourth additional information indicating the second degree of improvement of the control parameter due to adjustment may be output.
  • the first degree of improvement and the second degree of improvement can be displayed on the display device.
  • the first degree of improvement may be higher than the second degree of improvement.
  • the production device may include any one of a mounting device, a processing device, or a machining device.
  • control parameters can be generated for a production device that is any one of a mounting device, a processing device, or a machining device.
  • a program according to one aspect of the present disclosure is a program for causing a computer of an information processing device connected to the production device to execute the control parameter generation method.
  • the update of the control parameters can be restarted from the evaluation index data generated up to the first time or the first number of updates of the control parameters. This makes it possible to shorten the period for re-adjusting the control parameters compared to the case where the control parameters are re-adjusted from the beginning.
  • a recording medium is a recording medium on which a program for causing a computer of an information processing device connected to the production device to execute the control parameter generation method described above is recorded.
  • control parameters based on the evaluation index data indicating the vibration after the time when the permissible position has been reached, appropriate control parameters can be determined without the need of skilled engineers and in a relatively short time. can be generated.
  • the recording medium even if it is necessary to re-adjust the control parameters, the update of the control parameters is restarted from the evaluation index data generated up to the first time or the first number of updates of the control parameters. This makes it possible to shorten the period for re-adjusting the control parameters compared to the case where the control parameters are re-adjusted from the beginning.
  • a control parameter generation device includes a control parameter generation device that is used by a production device, a sensor confirms a state of the production device, and a display device generates a control parameter that displays at least a part of the control parameter. It is a generation device.
  • the production device includes a servo motor, a first control circuit that controls the servo motor, a memory that stores the control parameters used by the first control circuit to control the servo motor, and a memory that stores the control parameters used when the first control circuit controls the servo motor. and a driven object driven by.
  • the control parameter generation device further includes an input section, a second control circuit, and an output section.
  • the sensor detects the driven object after a time when the driven object reaches a permissible position where it can be evaluated that the driven object has reached the predetermined target position based on a command for changing the position of the driven object to a predetermined target position. Measures the position of an object and outputs measurement data representing the position.
  • the input unit acquires measurement data representing the position output from the sensor.
  • the second control circuit converts evaluation index data representing vibration of the driven object after a time when the driven object reaches the permissible position into a generation time of the evaluation index data.
  • the control parameters are updated using a machine learning model that is generated in association with each other and learns the relationship between the evaluation index data and the control parameters based on the evaluation index data.
  • the output unit outputs the updated control parameters to the production device for storage in the memory.
  • the output unit further outputs time data indicating a first time when the vibration indicated by the evaluation index data exceeds a predetermined threshold or a first number of updates of the control parameter up to the first time to the display device.
  • the second control circuit When the second control circuit is instructed to restart the update of the control parameters from the first time or from the first number of updates, the second control circuit further controls the control parameters from the first time or from the first number of updates until the first time or the first number of updates. The update of the control parameters is restarted from the evaluation index data generated in the above.
  • control parameters can be updated based on the evaluation index data indicating the vibration after the time when the driven object reaches the permissible position. , it is possible to generate appropriate control parameters.
  • control parameters generation device even if it is necessary to re-adjust the control parameters, the control parameters are updated from the evaluation index data generated up to the first time or the first number of updates of the control parameters. By restarting the adjustment, the period for re-adjusting the control parameters can be shortened compared to the case where the adjustment is re-adjusted from the beginning.
  • a control parameter generation device generates the control parameters
  • a production device uses a sensor with a processing device to check the state of the production device, and a display device displays at least one of the control parameters. Generate control parameters to display the section.
  • the production device includes a servo motor, a control circuit that controls the servo motor, a memory that stores the control parameters used by the control circuit to control the servo motor, and a drive target driven by the servo motor.
  • the sensor equipped with a processing device is configured to detect a time after a time when the driven object reaches an allowable position at which it can be evaluated that the driven object has reached the predetermined target position based on a command for changing the position of the driven object to a predetermined target position.
  • the position of the driven object is measured, and evaluation index data representing the vibration of the driven object after the time reached is output.
  • the control parameter generation method includes the following method. Evaluation index data representing vibration of the driven object after the time reached, which is output from the sensor with the processing device, is acquired in association with a generation time of the evaluation index data. Based on the evaluation index data, the control parameters are updated using a machine learning model that learns the relationship between the evaluation index data and the control parameters.
  • the updated control parameters are output to the production equipment for storage in the memory.
  • First time data indicating a first time when the vibration indicated by the evaluation index data exceeds a predetermined threshold or a first number of updates of the control parameter up to the first time is output to a display device in the generation system.
  • the evaluation index data obtained up to the first time or the first number of updates is used. Resume updating control parameters.
  • control parameter generation method by updating the control parameters based on the evaluation index data indicating the vibration after the time when the driven object reaches the permissible position, the , it is possible to generate appropriate control parameters.
  • control parameters are updated from the evaluation index data generated up to the first time or the first number of updates of the control parameters.
  • the period for re-adjusting the control parameters can be shortened compared to the case where the adjustment is re-adjusted from the beginning.
  • restarting the instructed update of the control parameters is from the first time among a plurality of times including the first time and the second time, or from the first update number and the second update.
  • the update of the control parameter may be restarted from the first update number among a plurality of update times including the number of update times.
  • First additional information indicating a first expected time required until parameter adjustment is completed is output.
  • the control parameter when restarting the update of the control parameter from the evaluation index data generated up to the second time or the second update number of the control parameter in association with the second time data is output.
  • the first predicted time and the second predicted time can be displayed on the display device.
  • the first predicted time may be shorter than the second predicted time.
  • control in the case of restarting updating of the control parameter from the evaluation index data acquired up to the first time or the first number of updates of the control parameter in association with the first time data.
  • Third additional information indicating a first degree of improvement of the control parameter due to parameter adjustment is output. and the control parameter when restarting the update of the control parameter from the evaluation index data generated up to the second time or the second update number of the control parameter in association with the second time data.
  • Fourth additional information indicating the second degree of improvement of the control parameter due to adjustment may be output.
  • the first degree of improvement and the second degree of improvement can be displayed on the display device.
  • the first degree of improvement may be higher than the second degree of improvement.
  • the evaluation index data may be generated in the sensor with a processing device based on the position of the driven object measured by the sensor with a processing device.
  • the evaluation value index data can be generated based on the position of the driven object measured by the sensor with the processing device.
  • the senor with a processing device may include an image processing device.
  • the evaluation value index data can be generated based on pixel processing.
  • the production device may include any one of a mounting device, a processing device, or a machining device.
  • control parameters can be generated for a production device that is any one of a mounting device, a processing device, or a machining device.
  • a program according to another aspect of the present disclosure is a program for causing a computer of an information processing device connected to the production device to execute the control parameter generation method.
  • the update of the control parameters can be restarted from the evaluation index data generated up to the first time or the first number of updates of the control parameters. This makes it possible to shorten the period for re-adjusting the control parameters compared to the case where the control parameters are re-adjusted from the beginning.
  • a recording medium is a recording medium on which a program for causing a computer of an information processing device connected to the production device to execute the control parameter generation method described above is recorded.
  • control parameters based on the evaluation index data indicating the vibration after the time when the permissible position has been reached, appropriate control parameters can be determined without the need of skilled engineers and in a relatively short time. can be generated.
  • the recording medium even if it is necessary to re-adjust the control parameters, the update of the control parameters is restarted from the evaluation index data generated up to the first time or the first number of updates of the control parameters. This makes it possible to shorten the period for re-adjusting the control parameters compared to the case where the control parameters are re-adjusted from the beginning.
  • a control parameter generation device is used in a production device, a sensor with a processing device checks the state of the production device, and a display device generates control parameters that display at least a part of the control parameters.
  • a control parameter generation device includes a servo motor, a first control circuit that controls the servo motor, a memory that stores the control parameters used by the first control circuit to control the servo motor, and a memory that stores the control parameters used when the first control circuit controls the servo motor. and a driven object driven by.
  • the sensor equipped with a processing device is configured to detect a time after a time when the driven object reaches an allowable position at which it can be evaluated that the driven object has reached the predetermined target position based on a command for changing the position of the driven object to a predetermined target position.
  • the position of the driven object is measured, and evaluation index data representing the vibration of the driven object after the time reached is output.
  • the control parameter generation device includes an input section, a second control circuit, and an output section.
  • the input unit acquires evaluation index data representing vibration of the driven object after the time reached, which is output from the sensor with a processing device, in association with a generation time of the evaluation index data.
  • the second control circuit updates the control parameter based on the evaluation index data using a machine learning model that learns a relationship between the evaluation index data and the control parameter.
  • the output unit outputs the updated control parameters to the production device for storage in the memory.
  • the output unit further outputs time data indicating a first time when the vibration indicated by the evaluation index data exceeds a predetermined threshold or a first number of updates of the control parameter up to the first time to a display device.
  • the second control circuit is instructed to restart the update of the control parameters from the first time or from the first number of updates
  • the second control circuit further controls the update of the control parameters from the first time or from the first number of updates until the first time or the first number of updates.
  • the update of the control parameters is restarted from the evaluation index data acquired in the above.
  • control parameter generation device by updating the control parameters based on the evaluation index data indicating the vibration after the time when the permissible position has been reached, appropriate Control parameters can be generated.
  • control parameters generation device even if it is necessary to re-adjust the control parameters, the control parameters are updated from the evaluation index data generated up to the first time or the first number of updates of the control parameters. By restarting the adjustment, the period for re-adjusting the control parameters can be shortened compared to the case where the adjustment is re-adjusted from the beginning.
  • This control parameter generation system is a system that generates control parameters used in a production device equipped with a servo motor that drives a driven object.
  • FIG. 1 is a schematic diagram showing an overview of a control parameter generation system 1 according to the first embodiment.
  • FIG. 2 is a block diagram showing the configuration of the control parameter generation system 1.
  • control parameter generation system 1 includes a generation device 10, a production device 20, and a sensor 30.
  • the production device 20 is a device used to produce equipment, and processes, mounts, transports, etc. the equipment.
  • the production device 20 is installed, for example, on a production line of a factory.
  • the production equipment 20 is, for example, an LED (light emitting diode) bonder, a mounting machine, a processing machine, a take-out robot, or the like.
  • the production device 20 includes a memory 21, a control circuit 22, a servo motor 23, and a driven object 24.
  • the operation of the servo motor 23 is controlled by the control circuit 22 and drives the object 24 to be driven.
  • the servo motor 23 may be, for example, a rotary motor or a linear motor.
  • the driven object 24 is an object driven by the servo motor 23.
  • the driven object 24 is, for example, a processing object to be processed in the production apparatus 20, a mounting object to be mounted, a conveyance object to be transported, and the like.
  • the driven object 24 may be, for example, an arm that holds objects handled in the production apparatus 20, or a tray that transports these objects.
  • the control circuit 22 controls the servo motor 23 by outputting a command to the servo motor 23 to position the driven object 24 at a predetermined target position.
  • the command that the control circuit 22 outputs to the servo motor 23 may be, for example, a position command that commands the position of the servo motor 23 or the driven object 24, or may be, for example, a torque command that commands the torque of the servo motor 23. There may be.
  • the control circuit 22 controls the servo motor 23 based on the control parameters stored in the memory 21. In other words, the control circuit 22 uses the control parameters stored in the memory 21 when controlling the servo motor 23.
  • the memory 21 stores control parameters used by the control circuit 22 to control the servo motor 23.
  • the control parameters stored in the memory 21 are the control parameters output from the generation device 10.
  • the senor 30 is arranged separately from the production device 20, it may be attached to the production device 20. Further, the sensor 30 may be an inspection device independent of the production device 20 or a part thereof.
  • FIG. 3 is a schematic diagram showing an example of control parameters stored in the memory 21.
  • the control parameters stored in the memory 21 include, for example, parameters a1 and a2 for adjusting the vibration frequency of the driven object 24, parameters b1 and b2 for adjusting the speed increase of the driven object 24, and parameters b1 and b2 for adjusting the speed of the driven object 24.
  • the parameters include parameters c1 and c2 for adjusting the depth of a singular point in the vibration characteristics of the object 24, parameters d1 and d2 for adjusting the vibration amplitude of the driven object 24, and the like.
  • control parameters include, for example, parameters b1 and b2 that adjust speed, parameters c1 and c2 that adjust the depth of singularity in vibration characteristics, and parameters d1 and d2 that adjust vibration amplitude.
  • the sensor 30 measures the position of the driven object 24. Then, the sensor 30 outputs to the generation device 10 measurement data representing the position of the driven object 24 after the time when the driven object 24 reaches an allowable position where it can be evaluated that the driven object 24 has reached a predetermined target position.
  • FIG. 4 is a schematic diagram showing an example of the transition of the positional deviation of the driven object 24 with respect to the target position when the production apparatus 20 drives the driven object 24 to the target position.
  • the horizontal axis indicates time
  • the vertical axis indicates the positional deviation of the driven object 24 with respect to the target position.
  • an allowable position refers to a position where the positional deviation from the target position is within the required accuracy.
  • the time when the driven object 24 reaches the permissible position (hereinafter also referred to as "settling time") at which it can be evaluated that the target position has been reached is the time when the driven object 24 reaches the permissible position. This refers to the time when the permissible position is finally reached (time sett_t in FIG. 4) when the permissible position does not deviate again after reaching the permissible position.
  • FIG. 5 is a data configuration diagram showing an example of measurement data output by the sensor 30.
  • the measurement data is, for example, data in which the elapsed time [ms] after the time when the permissible position is reached and the deviation amount [mm] from the target position are associated in one-to-one correspondence.
  • the generation device 10 generates control parameters (hereinafter also referred to as “updating control parameters") for updating the control parameters stored in the memory 21 (hereinafter also referred to as “stored control parameters"). More specifically, the generation device 10 sequentially acquires measurement data output from the sensor 30 as a result of the production device 20 driving the driven object 24 to the target position using the stored control parameters, and uses the acquired measurement data. Update control parameters are sequentially generated based on the data, and the generated update control parameters are sequentially output to the production apparatus 20.
  • the generation device 10 includes an input section 11, an output section 12, a control circuit 13, a machine learning model 14, an operation reception section 15, an image generation section 16, and a display section 17. Be prepared.
  • the generation device 10 is realized, for example, in a computer device including a processor, a memory, and an input/output interface, when the processor executes a program stored in the memory.
  • a computer device including a processor, a memory, and an input/output interface, when the processor executes a program stored in the memory.
  • a computer device is, for example, a personal computer.
  • the input unit 11 acquires the measurement data output from the sensor 30.
  • the input unit 11 may be, for example, an electronic component or an electronic circuit that inputs a signal.
  • the control circuit 13 generates evaluation index data indicating the vibration of the driven object 24 after the settling time based on the measurement data acquired by the input unit 11, and calculates the evaluation index data based on the generated evaluation index data.
  • the control parameters are updated using the machine learning model 14 that learns the relationship with the control parameters.
  • the evaluation index data generated by the control circuit 13 is any one of the following (1) to (3) or (4). That is, (1) The sum total of the area surrounded by the deviation waveform indicating the vibration of the driven object 24 after the settling time and the reference axis (hereinafter also referred to as “total area evaluation index data”). (2) Degree of variation in the deviation waveform indicating the vibration of the driven object 24 after the settling time (hereinafter also referred to as “dispersion degree evaluation index data”). (3) Effective value of the deviation waveform indicating the vibration of the driven object 24 after the settling time (hereinafter also referred to as “effective value evaluation index data”). or (4) the time from the time when the driven object 24 starts to be driven to the settling time (hereinafter also referred to as "settling time evaluation index data”). It is.
  • the evaluation index data generated by the control circuit 13 is specified by the user using the control parameter generation system 1.
  • the starting point sett_t of the integral interval is the settling time
  • the end point cal_e of the integral interval is the time set by the user. Note that although the explanation will be given here assuming that the starting point sett_t of the integral interval is the settling time, the starting point sett_t of the integral interval may be the settling time or any time after the settling time.
  • cal_e is, for example, the final position when the positional deviation of the driven object 24 with respect to the target position reaches within 1/10 of the required accuracy and then the positional deviation no longer deviates from within 1/10 of the required accuracy. It may be set at the time when the deviation reaches within 1/10 of the required accuracy, or for example, it may be set at the time when the number of data included in the measurement data acquired by the input unit 11 reaches a predetermined number. , it may be set to a time when a specified time has elapsed from the settling time.
  • the effective value evaluation index data generated by the control circuit 13 is calculated using the formula shown in (Formula 5).
  • the machine learning model 14 is a machine learning model that learns the relationship between evaluation index data and control parameters, and learns the relationship between evaluation index data and control parameters each time evaluation index data is sequentially input from the control circuit 13. It learns and sequentially outputs control parameters to the control circuit 13 based on the learning results.
  • the machine learning model 14 uses a Bayesian optimization algorithm to calculate evaluation index data and control parameters corresponding to the evaluation index data each time the evaluation index data is sequentially input from the control circuit 13. (hereinafter also referred to as "corresponding control parameters"), and outputs to the control circuit 13 the control parameters predicted to have the smallest evaluation index data based on the learning results.
  • FIG. 6 is a schematic diagram showing how the machine learning model 14 learns the relationship between evaluation index data and corresponding control parameters, and outputs the control parameters that are predicted to cause the smallest evaluation index data based on the learned results. It is a diagram.
  • the horizontal axis is the value of the control parameter
  • the vertical axis is the value of the evaluation index data.
  • the points plotted with circles indicate the values of the corresponding control parameters of the evaluation index data for each value of the evaluation index data input into the machine learning model 14 in the past.
  • the machine learning model 14 uses a Bayesian optimization algorithm to predict the relationship between evaluation index data and corresponding control parameters within a certain range, and uses the predicted relationship to A control parameter that is predicted to have the smallest evaluation index data is output.
  • the output unit 12 outputs the control parameters updated by the control circuit 13 to the production device 20 in order to store them in the memory 21.
  • the output unit 12 may be, for example, an electronic component or an electronic circuit that outputs a signal.
  • the operation accepting unit 15 accepts an input operation to the generating device 10 by a user using the control parameter generating system 1.
  • the operation receiving unit 15 may be, for example, an input device such as a button or a keyboard.
  • the display unit 17 displays images provided to the user who uses the control parameter generation system 1.
  • the display unit 17 may be, for example, a liquid crystal monitor, an organic EL (Electro Luminescence) monitor, or a CRT (Cathode Ray Tube) monitor.
  • the image generation unit 16 generates an image to be displayed on the display unit 17.
  • the image generation unit 16 may be, for example, a graphic board.
  • FIG. 7 is an example of an image generated by the image generation unit 16.
  • FIG. 7 shows how the control parameter generation system 1 sends evaluation index data generated by the control circuit 13 to a user who uses the control parameter generation system 1 when starting a first control parameter adjustment process to be described later.
  • This is an example of an image (hereinafter also referred to as "evaluation index data designation image") that prompts the user to specify whether or not to use the evaluation index data.
  • the generation device 10 displays an evaluation index data designation image on the display unit 17, thereby prompting the user to designate settling time evaluation index data as the evaluation index data generated by the control circuit 13. , or any one of total area evaluation index data, variation degree evaluation index data, and effective value evaluation index data (hereinafter, these three evaluation index data are also referred to as "vibration evaluation index data"). Encourage one person to specify one.
  • the user specifies the settling time evaluation index data as the evaluation index data, for example, by placing a check next to "settling time” in the evaluation index data designation image.
  • the user can select area sum evaluation index data as evaluation index data by checking the box next to "vibration” and putting a circle next to "area” in the evaluation index data specification image.
  • the user can select the degree of variation evaluation index data as evaluation index data by checking the box next to "vibration” and putting a circle next to "dispersion” in the evaluation index data specification image.
  • the user can select the effective value as evaluation index data by checking the box next to "vibration” and putting a circle next to "RMS (effective value)" in the evaluation index data specification image.
  • RMS effective value
  • the user can, for example, check the boxes next to "Settling time” and "Vibration" in the evaluation index data specification image to select settling time evaluation index data and vibration as evaluation index data.
  • the control circuit 13 may set the value of the settling time evaluation index data to be the sum of the value of the settling time evaluation index data and the value of the vibration evaluation index data.
  • vibration evaluation index data, and the value of the evaluation index data may be the sum of the values obtained by multiplying each of the values by a predetermined weighting coefficient.
  • FIG. 8 is an example of an image generated by the image generation unit 16.
  • FIG. 8 shows that while the control parameter generation system 1 is executing the first control parameter adjustment process, which will be described later, a user using the control parameter generation system 1 is asked to perform the first control parameter adjustment process.
  • This is an example of an image that presents the status of the value of evaluation index data (hereinafter also referred to as a "situation presentation image").
  • the horizontal axis is the number of control parameters sequentially output by the generating device 10
  • the vertical axis is the value of evaluation index data corresponding to each of the control parameters sequentially output by the generating device 10.
  • the solid line indicates the transition of the minimum value of the evaluation index data corresponding to the control parameter output by the generation device 10.
  • the interruption icon indicates, for example, that the value of the evaluation index data corresponding to the control parameter output by the generation device 10 has become sufficiently small as a result of the user visually confirming the situation presentation image, so that the first control parameter is no longer used. This icon allows you to interrupt the first control parameter adjustment process by clicking the interrupt icon when it is determined that there is no need to continue the adjustment process.
  • the restart icon indicates, for example, that the first control parameter adjustment process is performed because the value of the evaluation index data corresponding to the control parameter output by the generation device 10 has not become sufficiently small as a result of the user viewing the situation presentation image. This icon allows you to continue the first control parameter adjustment process by clicking the restart icon when it is determined that it is necessary to continue the process.
  • the control parameter generation system 1 executes a first control parameter adjustment process that adjusts the control parameters stored in the memory 21 to appropriate values.
  • the first control parameter adjustment process is started, for example, when a user using the control parameter generation system 1 performs an operation on the generation device 10 to start the first control parameter adjustment process.
  • FIG. 9 is a sequence diagram of the first control parameter adjustment process
  • FIG. 10 is a flowchart of the first control parameter adjustment process.
  • the generation device 10 starts a predetermined program for executing the first control parameter adjustment process (step S10).
  • the output unit 12 When the predetermined program is started, the output unit 12 outputs the initial values of the control parameters to the memory 21 (step S15). At this time, the output unit 12 may, for example, output an initial value of the control parameter consisting of a predetermined value, or may output an initial value of the control parameter consisting of a value specified by the user. Alternatively, for example, the initial value of the control parameter may be output, which is a value calculated by a calculation method specified by the user.
  • the memory 21 stores the control parameters output from the output unit 12 (step S20). Then, the control circuit 22 generates a command to position the driven object 24 to a predetermined target position based on the control parameters stored in the memory 21 and outputs it to the servo motor 23. Thereby, the control circuit 22 controls the servo motor 23 (step S25). Then, the servo motor 23 drives the driven object 24 based on the command output from the control circuit 22 (step S30).
  • the sensor 30 measures the position of the driven object 24 (step S35), and moves the driven object 24 to an allowable position where it can be evaluated that it has reached a predetermined target position. Measurement data representing the position of the driven object 24 after the time reached is output to the input unit 11 . Then, the input unit 11 acquires the measurement data output from the sensor 30 (step S40).
  • the control circuit 13 When the input unit 11 acquires the measurement data, the control circuit 13 generates evaluation index data indicating the vibration of the driven object 24 after the settling time based on the measurement data (step S45). Then, the control circuit 13 checks whether the generation of evaluation index data satisfies a predetermined condition (step S50).
  • the predetermined conditions include, for example, the condition that the number of times the evaluation index data has been updated (that is, the number of times it has been generated) has reached a predetermined number, the condition that a predetermined time has elapsed since the start of adjustment of the control parameters, and the like.
  • the predetermined number of times and the predetermined time may be determined in advance, or may be specified by the user using the control parameter generation system 1.
  • step S50 if the generation of evaluation index data does not satisfy the predetermined condition (step S50: No), the control circuit 13 outputs the generated evaluation index data to the machine learning model 14. Then, the machine learning model 14 learns the relationship between the evaluation index data and the corresponding control parameter (step S55), and outputs the control parameter that is predicted to have the smallest value of the evaluation index data. Then, the control circuit 13 updates the control parameters previously output by the output unit 12 with the control parameters newly output from the machine learning model 14 (step S60). Then, the output unit 12 transmits the control parameters newly updated by the control circuit 13 to the memory 21 (step S65).
  • step S65 the control parameter generation system 1 proceeds to the process of step S20, and repeats the process from step S20 onwards.
  • step S50 if the generated evaluation index data satisfies the predetermined condition (step S50: Yes), the control parameter generation system 1 ends the first control parameter adjustment process.
  • control parameter generation system 1 configured as described above repeatedly generates control parameters by executing the first control parameter adjustment process until the generation of evaluation index value data satisfies a predetermined condition. Adjust the control parameters.
  • control parameter generation system 1 appropriate control parameters can be generated in a relatively short time without the need for skilled engineers.
  • the control parameter generation system 1 was an example of a system in which the sensor 30 measures the position of the driven object 24 and outputs measurement data, and the generation device 10 acquires the measurement data output from the sensor 30.
  • the sensor with the processing device according to the second embodiment measures the position of the driven object 24 and outputs evaluation index data.
  • the generation device according to Embodiment 2 is an example of a system that acquires evaluation index data output from the sensor with a processing device according to the second embodiment.
  • control parameter generation system according to Embodiment 2, the same components as those in control parameter generation system 1 are given the same reference numerals as those in control parameter generation system 1, and the detailed explanation thereof will be omitted. The differences from System 1 will be mainly explained.
  • FIG. 11 is a schematic diagram showing an overview of a control parameter generation system 1A according to the second embodiment.
  • FIG. 12 is a block diagram showing the configuration of the control parameter generation system 1A.
  • the control parameter generation system 1A differs from the control parameter generation system 1 according to the first embodiment in that the generation device 10 is changed to a generation device 10A, and the sensor 30 is changed to a sensor with a processing device 30A. configured. Further, as shown in FIG. 12, the generation device 10A is configured by changing the input unit 11 from the generation device 10 to an input unit 11A, and changing the control circuit 13 to a control circuit 13A.
  • the sensor 30A with a processing device measures the position of the driven object 24. Then, the processing device-equipped sensor 30A generates measurement data representing the position of the driven object 24 after the time when the driven object 24 reaches a permissible position where it can be evaluated that the driven object 24 has reached a predetermined target position. Furthermore, the sensor with processing device 30A generates evaluation index data indicating the vibration of the driven object 24 after the settling time based on the generated measurement data, and outputs the generated evaluation index data to the generation device 10A.
  • the sensor with processing device 30A is, for example, a computer device including a sensing device that measures the position of the driven object 24, a processor, a memory, and an input/output interface, in which the processor executes a program stored in the memory. It is realized by Such a computer device is, for example, a personal computer (personal computer).
  • the processing device-equipped sensor 30A may include, for example, an image processing device.
  • the sensor with processing device 30A may measure the position of the driven object 24 by performing image processing on the image of the driven object 24 using an image processing device, for example.
  • processing device-equipped sensor 30A is arranged separately from the production device 20, it may be attached to the production device 20. Further, the processing device-equipped sensor 30A may be an inspection device independent of the production device 20 or a part thereof.
  • the input unit 11A acquires the evaluation index data output from the sensor with processing device 30A.
  • the control circuit 13A updates the control parameters using the machine learning model 14 that learns the relationship between the evaluation index data and the control parameters based on the evaluation index data acquired by the input unit 11A.
  • the control parameter generation system 1A performs a second control parameter adjustment process in which a part of the process is changed from the first control parameter adjustment process according to the first embodiment.
  • FIG. 13 is a sequence diagram of the second control parameter adjustment process
  • FIG. 14 is a flowchart of the second control parameter adjustment process.
  • the second control parameter adjustment process includes the process from step S110 to step S165.
  • the process from step S110 to step S130 and the process from step S150 to step S165 are the process from step S10 to step S30 in the first control parameter adjustment process, respectively.
  • the process is similar to the process from step S50 to step S65.
  • step S135 the processing from step S135 to step S145 will be mainly described.
  • the sensor with processing device 30A measures the position of the driven object 24 (step S135), and the time when the driven object 24 reaches an allowable position at which it can be evaluated that it has reached a predetermined target position. Measurement data representing the subsequent position of the driven object 24 is generated. Then, the sensor with processing device 30A generates evaluation index data indicating the vibration of the driven object 24 after the settling time based on the generated measurement data (step S140), and inputs the generated evaluation index data to the input section 11A. Output to. Then, the input unit 11A obtains the evaluation index data output from the processing device-equipped sensor 30A (step S145).
  • step S145 Upon completion of the process in step S145, the control parameter generation system 1A proceeds to the process in step S150.
  • step S150 if the generation of evaluation index data satisfies the predetermined conditions (step S150: Yes), the control parameter generation system 1A ends the second control parameter adjustment process.
  • control parameter generation system 1A having the above configuration can generate evaluation index value data by executing the second control parameter adjustment process.
  • Control parameters are adjusted by repeatedly generating control parameters until predetermined conditions are met.
  • control parameter generation system 1A can generate appropriate control parameters in a relatively short period of time without requiring a skilled engineer.
  • the control parameter generation system adjusts the control parameters by repeatedly generating the control parameters until the generation of the evaluation index data satisfies a predetermined condition, and then the adjusted evaluation index data is adjusted.
  • This is an example of a system in which control parameters can be readjusted from a point specified by the user if the user using the control parameter generation system is not satisfied with the result.
  • control parameter generation system according to Embodiment 3, the same components as those in control parameter generation system 1 are given the same reference numerals as those already explained, and detailed explanation thereof will be omitted. The differences from System 1 will be mainly explained.
  • FIG. 15 is a schematic diagram showing an overview of the control parameter generation system 1B according to the third embodiment.
  • FIG. 16 is a block diagram showing the configuration of the control parameter generation system 1B.
  • the control parameter generation system 1B is configured by changing the generation device 10 from the control parameter generation system 1 according to Embodiment 1 to a generation device 10B, and adding a display device 40.
  • the display device 40 is provided independently of the generation device 10B.
  • the generation device 10B is configured by changing the output unit 12 from the generation device 10 to an output unit 12B and changing the control circuit 13 to a control circuit 13B.
  • the display device 40 may be included as a part of the display section 17.
  • the display device 40 and the display section 17 may be the same. In a case where the display device 40 is included as part of the display unit 17, for example, the display unit 17 may include a plurality of display devices, and the display device 40 may be one of them. Further, information shown by the display device 40 may be displayed on the display unit 17.
  • the control circuit 13B performs operations similar to those performed by the control circuit 13, and further performs the following operations.
  • the control circuit 13B repeatedly generates control parameters using the control parameter generation system 1B until the generation of evaluation index data satisfies a predetermined condition. After the control parameters have been adjusted in this way, the user using the control parameter generation system 1B can control the control parameters from the first time or from the first update number of the control parameters up to the first time. When an instruction is given to restart updating of the parameters, updating of the control parameters is restarted from the evaluation index data generated up to the first time or the first number of updates.
  • control circuit 13B When generating evaluation index data, the control circuit 13B generates the evaluation index data in association with the generation time of the evaluation index data. Then, the control circuit 13B updates the adjustment history based on the generated evaluation index data and the generation time of the evaluation index data.
  • FIG. 17 is a data configuration diagram showing an example of the data configuration of the adjustment history updated by the control circuit 13B.
  • the adjustment history is configured by associating, for example, the number of updates, a time stamp, the best evaluation value, and the control parameter value at the time of the best evaluation value.
  • the number of updates is the number of times the control circuit 13B has generated the control parameters, that is, the number of times the control circuit 13B has updated the control parameters after the control parameter generation system 1B starts adjusting the control parameters.
  • the time stamp is the generation time of the evaluation index data when the control circuit 13B generated the evaluation index data the number of times indicated by the corresponding number of updates.
  • the best evaluation value is the value of the best evaluation index data (here, the minimum (the value of the evaluation index data).
  • the control parameter value at the time of the best evaluation value is the value of the control parameter when the control circuit 13B calculates the corresponding best evaluation value.
  • control circuit 13B After generating the evaluation index data, the control circuit 13B determines whether the vibration of the driven object 24 indicated by the generated evaluation index data exceeds a predetermined threshold. Then, the control circuit 13B updates the threshold determination history based on the results of the investigation.
  • FIG. 18 is a data configuration diagram showing an example of the data configuration of the threshold determination history updated by the control circuit 13B.
  • the threshold determination history is configured by associating, for example, the number of updates, a timestamp, a ratio to the threshold, and a determination result.
  • the number of updates and the time stamp are the same as the number of updates and the time stamp in the adjustment history shown in FIG.
  • the ratio to the threshold is the ratio of the vibration of the driven object 24 indicated by the evaluation index data to the predetermined threshold when the evaluation index data is generated the number of times indicated by the corresponding number of updates.
  • the determination result is information that indicates "True” when the ratio to the corresponding threshold value exceeds 1, and indicates “False” when the ratio does not exceed 1.
  • the determination result is, for example, a 1-bit signal that has a logical value of "1" when the ratio to the corresponding threshold value exceeds 1, and has a logical value of "0" when it does not exceed 1.
  • control circuit 13B determines that the vibration of the driven object 24 indicated by the generated evaluation index data exceeds a predetermined threshold, the control circuit 13B performs control when restarting the update of the control parameters from the time when the evaluation index data is generated.
  • the estimated time required from when the parameter adjustment is restarted until the control parameter adjustment is completed, that is, from when the control parameter adjustment is restarted until the generation of evaluation index data satisfies a predetermined condition is calculated.
  • the control circuit 13B determines that the predetermined threshold has been exceeded from the time when the control parameter adjustment was started.
  • the expected time may be calculated by subtracting the elapsed time up to the time when the determined evaluation index data was generated from the predetermined time. For example, when the condition is that the number of updates of the evaluation index data has reached a predetermined number, the control circuit 13B controls the number of updates that generated the evaluation index data determined to have exceeded a predetermined threshold from the predetermined number of times.
  • the expected time may be calculated by multiplying the number of times obtained by subtracting the number by the time required for each update when the evaluation value index data is repeatedly updated.
  • control circuit 13B determines that the vibration of the driven object 24 indicated by the generated evaluation index data exceeds a predetermined threshold value, the control circuit 13B resumes updating the control parameters from the time when the evaluation index data is generated. , calculate the degree of improvement of the control parameters.
  • control circuit 13B calculates the improvement degree such that, for example, the larger the vibration of the driven object 24 indicated by the generated evaluation index data, the higher the improvement degree, and the smaller the vibration, the lower the improvement degree. You can also use it as
  • the output unit 12B performs the same operations as the output unit 12, and further performs the following operations.
  • the output unit 12B outputs to the display device 40 one or more times when the vibration of the driven object 24 indicated by the evaluation index data exceeds a predetermined threshold, or one or more time data indicating one or more times of updating.
  • the output unit 12B outputs one or more time data to the display device 40 by outputting the adjustment history and the threshold determination history to the display device 40.
  • the output unit 12B outputs a plurality of pieces of additional information calculated by the control circuit 13B in association with each of the one or more pieces of time data when updating the control parameters is restarted from the time point corresponding to the time data. , is output to the display device 40.
  • These plural pieces of additional information include additional information indicating the expected time required from when the control parameter adjustment is restarted until the control parameter adjustment is completed, and additional information indicating the degree of improvement of the control parameters.
  • the display device 40 generates and displays an image based on the data and information output from the output unit 12B.
  • the display device 40 then receives input from a user using the control parameter generation system 1B based on the displayed image.
  • FIG. 19 is an example of an image displayed by the display device 40.
  • FIG. 19 is an example of an image (hereinafter also referred to as "adjustment restart point designation image") that prompts the user using the control parameter generation system 1B to specify the adjustment restart point when readjusting the control parameters. ing.
  • the horizontal axis is the number of updates of the control parameters or the elapsed time (adjustment time) since the start of adjustment of the control parameters, and the vertical axis is the best evaluation value.
  • the broken line in FIG. 19 is a virtual line indicating the transition of the best evaluation value when the control parameter adjustment progresses ideally, and is not actually displayed in the adjustment restart point designation image.
  • the user can display candidates for the adjustment restart time point (three black circles in FIG. 19) on the adjustment restart point designation image by checking the box next to "Adjustment restart setting" in the adjustment restart point designation image. can be done.
  • each of the adjustment restart time candidates corresponds to a time when the vibration of the driven object 24 indicated by the evaluation index data generated by the control circuit 13B exceeds a predetermined threshold value.
  • the user can check the degree of improvement calculated by the control circuit 13B corresponding to each of the adjustment restart time point candidates by, for example, placing a check next to "display expected degree of improvement" in the adjustment restart point designation image. (“Expected level of improvement: High,” “Expected level of improvement: Low,” and “Expected level of improvement: Medium” in FIG. 19) can be displayed on the adjustment restart point designation image.
  • the user can check the expected adjustment time next to the adjustment restart point designation image, for example, to calculate the expected time (calculated by the control circuit 13B) corresponding to each of the adjustment restart point candidates. "3 hours,” “2 hours 30 minutes,” and “2 hours 10 minutes” in FIG. 19 can be displayed in the adjustment restart point designation image.
  • the user can specify the adjustment restart time point, for example, by clicking on one of the displayed adjustment restart time point candidates on the adjustment restart time point designation image.
  • the user can designate the adjustment restart point by referring to the degree of improvement and estimated time displayed in the adjustment restart point designation image.
  • the user can refer to the degree of improvement displayed in the adjustment restart point designation image and designate the adjustment reproduction time point corresponding to the degree of improvement that shows the highest value.
  • the control parameters when the control parameters are readjusted, it is expected that the control parameters will be improved to the highest degree of improvement.
  • the user can refer to the estimated time displayed in the adjustment restart point designation image and designate the adjustment restart point corresponding to the expected time that shows the shortest value.
  • the control parameters are readjusted, it is expected that the control parameters will be improved in the shortest possible time.
  • the adjustment restart time point designation image indicates that the vibration of the driven object 24 indicated by the evaluation index data, estimated at the adjustment restart time point, exceeds a predetermined threshold value for each candidate for the adjustment restart time point.
  • the cause may also be displayed.
  • the control circuit 13B determines, for example, the cause of the vibration of the driven object 24 indicated by the evaluation index data exceeding a predetermined threshold, based on the characteristics of the vibration of the driven object 24 indicated by the evaluation index data.
  • the cause of the vibration of the driven object 24 indicated by the evaluation index data estimated by the control circuit 13B to exceed a predetermined threshold may include, for example, Vibrations of the production equipment 20 caused by the running of the truck (corresponding to "device vibration caused by the truck" in FIG. 19) may be included.
  • the above causes include vibration of the production equipment 20 due to a passenger car driving near the factory where the production equipment 20 is installed (corresponding to "There is equipment vibration due to a passenger car” in FIG. 19); Vibrations caused by people entering and leaving the living room (corresponding to "entering and leaving” in FIG. 19) may also be included.
  • control circuit 13B acquires information such as the amplitude, period, and duration of the vibration of the driven object 24 from an external system of the control parameter generation system 1B, or when the production device 20 is installed. log information of people entering and leaving the living room, and based on the acquired information, estimate the cause of the vibration of the driven object 24 indicated by the evaluation index data exceeding a predetermined threshold. You can also use it as
  • the control circuit 13B stores in advance a table in which values such as amplitude, period, and duration of the vibration of the driven object 24 are associated with the phenomena that cause the vibration, and the control circuit 13B stores in advance a table in which values such as amplitude, period, and duration of vibration of the driven object 24 are associated with phenomena that cause the vibration. Based on the acquired information on the amplitude, period, duration, etc. of the vibration of the driven object 24 and the table, the phenomenon causing the vibration is identified. By doing so, the cause of the vibration of the driven object 24 indicated by the evaluation index data exceeding a predetermined threshold value may be estimated.
  • the user can readjust the parameters by, for example, clicking the "Resume Adjustment” button on the adjustment restart point specified image.
  • the control parameter generation system 1B performs a third control parameter adjustment process in which a part of the process is changed from the first control parameter adjustment process according to the first embodiment.
  • the third control parameter adjustment process includes the process from step S210 to step S295.
  • the process from step S210 to step S240 and the process from step S250 to step S265 are the process from step S10 to step S40 in the first control parameter adjustment process, respectively.
  • the process is similar to the process from step S50 to step S65.
  • step S245 to step S249 the processing from step S270 to step S295 will be mainly described.
  • step S240 the control circuit 13B generates evaluation index data indicating the vibration of the driven object 24 after the settling time based on the measurement data in association with the generation time of the evaluation index data (step S245). Then, the control circuit 13B updates the adjustment history based on the generated evaluation index data and the generation time of the evaluation index data (step S246).
  • control circuit 13B After generating the evaluation index data, the control circuit 13B determines whether the vibration of the driven object 24 indicated by the generated evaluation index data exceeds a predetermined threshold. Then, the control circuit 13B updates the threshold determination history based on the results of the investigation (step S247).
  • step S248 If it is determined that the vibration of the driven object 24 indicated by the evaluation index data exceeds the predetermined threshold (step S248: Yes), the control circuit 13B calculates the expected time and the degree of improvement (step S249).
  • step S248 If it is not determined that the vibration of the driven object 24 indicated by the evaluation index data exceeds the predetermined threshold (step S248: No), and if the process of step S249 is completed, the control parameter generation system 1B performs step The process advances to S250.
  • step S250 if the generation of the evaluation index data satisfies a predetermined condition (step S250: Yes), the output unit 12B outputs a message that the vibration of the driven object 24 indicated by the evaluation index data exceeds a predetermined threshold value.
  • One or more time data indicating one or more times exceeded or one or more times of updating are output to the display device 40 together with additional information indicating the expected time and additional information indicating the degree of improvement (step S270). Then, the display device 40 generates and displays an adjustment restart point designation image based on these data and information (step S271).
  • the display device 40 After displaying the adjustment restart point designation image, the display device 40 accepts input by the user using the control parameter generation system 1B based on the displayed adjustment restart point designation image (step S275).
  • step S280 If the input received by the display device 40 is an input specifying the adjustment restart point when readjusting the control parameters (step S280: YES), the control circuit 13B controls the learning of the machine learning model 14. The degree is rewound to the specified adjustment restart point (step S285). Further, the control circuit 13B rewinds the adjustment history and the threshold value determination history to the specified adjustment restart time (step S290). Then, the control circuit 13B updates the control parameters to the specified values at the time of restarting the adjustment (step S295).
  • step S295 the control parameter generation system 1B proceeds to the process of step S265.
  • step S280 if the input received by the display device 40 is not an input specifying the adjustment restart point when readjusting the control parameters (step S280: No), the control parameter generation system 1B , the third control parameter adjustment process ends.
  • the control parameter generation system 1B was an example of a system in which the sensor 30 measures the position of the driven object 24 and outputs measurement data, and the generation device 10B acquires the measurement data output from the sensor 30.
  • the sensor with the processing device according to the fourth embodiment measures the position of the driven object 24 and outputs evaluation index data.
  • the generation device according to Embodiment 4 is an example of a system that acquires evaluation index data output from the sensor with a processing device according to the fourth embodiment.
  • control parameter generation system according to Embodiment 4, the same components as those in the control parameter generation system 1B will be given the same reference numerals as they have already been explained, and detailed explanation thereof will be omitted. The explanation will focus on the differences from system 1B.
  • FIG. 22 is a schematic diagram showing an overview of the control parameter generation system 1C according to the fourth embodiment.
  • FIG. 23 is a block diagram showing the configuration of the control parameter generation system 1C.
  • the control parameter generation system 1C differs from the control parameter generation system 1B according to the third embodiment in that the generation device 10B is changed to a generation device 10C, and the sensor 30 is changed to a sensor with a processing device 30C. configured. Further, as shown in FIG. 23, the generation device 10C is configured by changing the input section 11 from the generation device 10B to an input section 11C, and changing the control circuit 13B to a control circuit 13C.
  • the sensor with processing device 30C performs the same operations as the sensor with processing device 30A, and further performs the following operations.
  • the processing device equipped sensor 30C When the sensor with processing device 30C generates evaluation index data, it generates the evaluation index data in association with the generation time of the evaluation index data. Then, when outputting the generated evaluation index data to the generation device 10C, the processing device equipped sensor 30C outputs the generation time of the generated evaluation index data in association with the evaluation index data.
  • the input unit 11C performs the same operations as the input unit 11, and further performs the following operations.
  • the input unit 11C acquires the evaluation index data output from the sensor with processing device 30C in association with the generation time of the evaluation index data.
  • the control circuit 13C performs the same operations as the control circuit 13B, and further performs the following operations.
  • the control circuit 13C When the input unit 11C does not acquire the measurement data from the sensor with processing device 30C and acquires the evaluation index data in association with the generation time of the evaluation index data, the control circuit 13C generates the evaluation index data based on the measurement data. Instead of generating the evaluation index data in association with the generation time of the evaluation index data, the evaluation index data acquired by the input unit 11C is acquired in association with the generation time of the evaluation index data.
  • the control parameter generation system 1C performs a fourth control parameter adjustment process in which a part of the process is changed from the third control parameter adjustment process according to the third embodiment.
  • the fourth control parameter adjustment process includes the process from step S310 to step S395.
  • the process from step S310 to step S330 and the process from step S347 to step S395 are the process from step S210 to step S230 in the third control parameter adjustment process, respectively.
  • the process is similar to the process from step S247 to step S295.
  • step S335 the processing from step S335 to step S346 will be mainly described.
  • the sensor with processing device 30C measures the position of the driven object 24 (step S335), and determines the time when the driven object 24 reaches an allowable position at which it can be evaluated that it has reached a predetermined target position. Measurement data representing the subsequent position of the driven object 24 is generated. Then, based on the generated measurement data, the processing device-equipped sensor 30C generates evaluation index data indicating the vibration of the driven object 24 after the settling time in association with the generation time of the evaluation index data (step S340 ), the generated evaluation index data is outputted to the input unit 11C in association with the generation time of the evaluation index data.
  • the input unit 11C obtains the evaluation index data output from the sensor with processing device 30C in association with the generation time of the evaluation index data (step S345). Then, the control circuit 13C updates the adjustment history based on the acquired evaluation index data and the generation time of the evaluation index data (step S346).
  • control parameter generation system 1C proceeds to the process in step S347.
  • the vibration of the driven object 24 indicated by the evaluation index data is Resume updating the control parameters from the evaluation index data at the time or number of updates specified by the user using the control parameter generation system 1C among the one or more times when the threshold value of .
  • the generation device 10 was described as being realized by one computer device. However, the generation device 10 does not necessarily need to be implemented by one computer device as long as it can implement similar functions.
  • the generation device 10 may be realized by, for example, a plurality of computer devices that can communicate with each other.
  • FIG. 26 is a block diagram showing an example of the configuration of the generation device 10 in a case where the generation device 10 is realized by a plurality of computer devices that can communicate with each other.
  • the generation device 10 includes (1) an input section 11, an output section 12, an operation reception section 15, an image generation section 16, a display section 17, and a communication section 18. (2) a second computer device 110 including a control circuit 13, a machine learning model 14, and a communication unit 19; and (3) a communication unit 18 and a communication unit 19 are communicably connected. It may also be realized by a network 120 that supports
  • the first computer device 100 may be, for example, a personal computer (personal computer), and the second computer device 110 may be a server.
  • a personal computer personal computer
  • the second computer device 110 may be a server.
  • control parameter generation system 1 has (i) a tolerance that allows the sensor 30 to measure the position of the driven object 24 and evaluate that the driven object 24 has reached a predetermined target position; The description has been made assuming that the configuration is such that the measurement data representing the position of the driven object 24 after the time when it reaches the position is output, and (ii) the input unit 11 acquires the measurement data output from the sensor 30.
  • control parameter generation system 1 is an example, and the control parameter generation system 1 is configured such that the input unit 11 determines that the drive object 24 has reached a permissible position after the time when the driven object 24 has reached a permissible position where it can be evaluated that the driven object 24 has reached a predetermined target position.
  • the configuration is not necessarily limited to the above configuration as long as measurement data representing the position of the driven object 24 can be acquired.
  • FIG. 27 is a block diagram showing the configuration of a control parameter generation system 1D that is an example of another configuration of the control parameter generation system 1 and does not include the sensor 30.
  • the servo motor 23 has a built-in sensor that detects the motor position (for example, if the servo motor 23 is a rotary motor, the rotational position of the servo motor 23). Then, the servo motor 23 outputs an encoded value representing the motor position of the servo motor 23 detected by the built-in sensor. That is, the production device 20D outputs an encoded value.
  • Such a sensor that detects the position of the motor is generally also referred to as an encoder.
  • servo motors usually have a built-in encoder.
  • the position of the servo motor 23 represented by this encoded value has a one-to-one correspondence with the position of the driven object 24. Therefore, the encoded value output by the servo motor 23 represents the position of the servo motor 23 and also represents the position of the driven object 24. Therefore, it can be said that the sensor built into the servo motor 23 also detects the position of the driven object 24 and outputs an encoded value representing the position of the driven object 24.
  • the input unit 11 acquires the encoded value output from the servo motor 23 as measurement data.
  • the general or specific aspects of the present disclosure may be realized in a system, device, method, integrated circuit, program, or non-transitory recording medium such as a computer-readable CD-ROM. Further, the present invention may be realized by any combination of systems, devices, methods, integrated circuits, programs, and non-transitory recording media. For example, the present disclosure may be implemented as a program for causing a computer device to execute the processing performed by the generation device.
  • the production devices 20 and 20D of the present disclosure may include the generation devices 10 and 10A to 10C.
  • the production apparatuses 20 and 20D of the present disclosure may include the control parameter generation systems 1 and 1A to 1D.
  • the display device 40 may be arranged integrally with the generation devices 10, 10A to 10C. Further, the display device 40 may be incorporated into the production equipment 20, 20D.
  • the sensor 30 and the sensors 30A and 30C with processing devices may be installed and arranged in the production apparatus 20, or may be arranged independently of the production apparatus 20. Further, the sensor 30 and the sensors with processing devices 30A and 30C may be installed and arranged in the generation devices 10 and 10A to 10C.
  • the production devices 20 and 20D of the present disclosure are not limited to devices that produce products, but may include equipment, plants, and factories that produce products.
  • the control parameter generation systems 1, 1A to 1D of the present disclosure can also be applied to equipment, equipment, plants, warehouses, or factories that produce products.
  • the present disclosure can be applied to a conveyance device in addition to the production devices 20 and 20D.
  • the present disclosure can be widely used in systems that generate control parameters, etc.
  • Control parameter generation system 10 10A, 10B, 10C Generation device 11, 11A, 11C Input section 12, 12B Output section 13, 13A, 13B, 13C Control circuit 14 Machine learning model 15 Operation reception Section 16 Image generation section 17 Display section 18, 19 Communication section 20, 20D Production device 21 Memory 22 Control circuit 23 Servo motor 24 Drive target 30 Sensor 30A, 30C Sensor with processing device 40 Display device 100 First computer device 110 No. 2 computer equipment 120 network

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PCT/JP2023/024161 2022-07-01 2023-06-29 制御パラメータの生成方法、プログラム、記録媒体、および、制御パラメータの生成装置 Ceased WO2024005136A1 (ja)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018151215A1 (ja) * 2017-02-20 2018-08-23 株式会社安川電機 制御装置及び制御方法
JP2020148624A (ja) * 2019-03-13 2020-09-17 沖電気工業株式会社 信号処理装置、プログラム及び方法
WO2021053784A1 (ja) * 2019-09-19 2021-03-25 三菱電機株式会社 モータ制御装置及びモータ制御方法

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018151215A1 (ja) * 2017-02-20 2018-08-23 株式会社安川電機 制御装置及び制御方法
JP2020148624A (ja) * 2019-03-13 2020-09-17 沖電気工業株式会社 信号処理装置、プログラム及び方法
WO2021053784A1 (ja) * 2019-09-19 2021-03-25 三菱電機株式会社 モータ制御装置及びモータ制御方法

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