Information processing method, information processing device, program, drive control device, and control system

Abstract

This information processing method is for optimizing a control parameter set in a drive system that executes an operation on the basis of a control signal input from a control device. In the method, an information processing device: acquires setting information for setting, from among operations executed by the drive system, an evaluation target operation serving as an evaluation target in optimization processing for optimizing the control parameter; and generates, on the basis of the setting information, an optimization program for causing the control device to execute control processing in the optimization processing.

Description

Information processing method, information processing apparatus, program, drive control apparatus, and control system

[0001] The present disclosure relates to an information processing method, an information processing apparatus, a program, a drive control apparatus, and a control system.

[0002] A method for generating control parameters according to the background art is disclosed in, for example, Patent Document 1.

[0003] In a system configuration in which the operation of a drive system is controlled by a control apparatus, there are cases where, for example when the control apparatus is a product manufactured by another company, the control apparatus cannot appropriately execute control processing for optimization processing of control parameters.

[0004] International Publication No. 2023 / 203933

[0005] An object of the present disclosure is to obtain an information processing method, an information processing apparatus, a program, a drive control apparatus, and a control system that enable a control apparatus to appropriately execute control processing for optimization processing of control parameters.

[0006] An information processing method according to an aspect of the present disclosure is an information processing method for optimizing control parameters set in a drive system that executes an operation based on a control signal input from a control apparatus, wherein an information processing apparatus acquires setting information for setting an evaluation target operation that is an evaluation target in optimization processing for optimizing the control parameter among operations executed by the drive system, and generates an optimization program for causing the control apparatus to execute control processing in the optimization processing based on the setting information.

[0007] According to the present disclosure, a control apparatus can appropriately execute control processing for optimization processing of control parameters based on an optimization program.

[0008] Figure 1 is a simplified diagram showing the configuration of a control parameter generation system according to an embodiment of the present disclosure. Figure 2 is a flowchart showing the optimization program generation process executed by the information processing unit. Figure 3 is a flowchart showing the optimization program generation process executed by the information processing unit. Figure 4 is a simplified diagram showing a first example of the program modification process. Figure 5 is a sequence diagram showing a first example of processing executed by the control device and the drive control device in the control parameter optimization process. Figure 6 is a simplified diagram showing a second example of the program modification process. Figure 7 is a sequence diagram showing a second example of processing executed by the control device and the drive control device in the control parameter optimization process.

[0009] (Knowledge forming the basis of this disclosure) Generally, the number of control parameters for a drive source used in a production device can exceed 50. Furthermore, the number of adjustment levels can exceed 100. For example, if a production device performs 80 operations, the number of control parameters for the drive source is 50, and the number of adjustment levels for the control parameters is 100 levels, the number of combinations is 100^50 × 80. The inventors have found that when generating control parameters for such a vast number of combinations, if a method using machine learning models or the like is used to search for appropriate control parameters, the search range is too wide, resulting in a phenomenon where it takes an enormous amount of time to find appropriate control parameters, or where it is impossible to reach appropriate control parameters no matter how much time is spent. Therefore, the inventors have diligently conducted experiments and studies to realize a parameter generation method that can efficiently generate appropriate control parameters even when generating control parameters for a vast number of combinations.

[0010] Through the above experiments and studies, the inventors found that instead of searching for appropriate control parameters for all of the vast number of combinations from the beginning, for example, if the production equipment performs 80 operations, the first step is to search for appropriate control parameters for only a portion of these 80 operations, for example, for combinations of just one operation, that is, for combinations of only a portion of the vast number of combinations. In the next step, the number of operations performed by the production equipment is increased, for example, for combinations of two operations, and appropriate control parameters are searched for using the search results from the first step as a starting point. In the next step, the number of operations performed by the production equipment is further increased, for example, for combinations of four operations, and appropriate control parameters are searched using the search results from the previous step as a starting point. By repeating this process and finally searching for appropriate control parameters for all 80 operation combinations, the inventors found that it is possible to generate appropriate control parameters for all 80 operation combinations more efficiently and reliably.

[0011] Based on this knowledge, the inventors conducted further experiments and studies, and arrived at the control parameter generation method and other related inventions described below.

[0012] Furthermore, in a drive system comprising a drive device such as a servo motor for driving a moving object and a drive control device such as a servo amplifier for controlling the drive device, a method has recently been proposed to optimize the control parameters set in the drive control device by searching for optimal control parameters using machine learning models.

[0013] The system related to the background technology involves an information processing device such as a personal computer performing a control parameter update process, and the information processing device then inputting control commands such as control commands and the updated control parameters to a drive control device, thereby performing a control parameter optimization process.

[0014] However, in a system configuration where the operation of the drive system is controlled by a control device such as a PLC, if the control device is a product of another company, modifying the operation of the control device requires changing the script of the control program, and performing this modification manually is difficult. As a result, there is a possibility that the control device may not be able to properly execute the control processing for optimizing the control parameters.

[0015] To solve these problems, the inventors have come up with the present disclosure based on the finding that an information processing device can generate an optimization program that causes a control device to execute control processing for optimization processing, thereby enabling the control device to execute appropriate control processing based on the optimization program.

[0016] Next, we will describe each aspect of this disclosure.

[0017] An information processing method according to a first aspect of the present disclosure is an information processing method for optimizing control parameters set in a drive system that performs an operation based on a control signal input from a control device, wherein the information processing device acquires setting information that sets an operation to be evaluated among the operations performed by the drive system, which is to be evaluated in an optimization process for optimizing the control parameters, and generates an optimization program based on the setting information that causes the control device to perform a control process in the optimization process.

[0018] According to the first embodiment, the control device can appropriately execute control processing for optimizing control parameters based on an optimization program.

[0019] In the second aspect of the information processing method of this disclosure, in the first aspect, the setting of the operation to be evaluated may include setting the start and end times of the evaluation period among the operations performed by the drive system.

[0020] According to the second embodiment, the optimization process of the control parameters can be appropriately performed by setting the start and end times of the evaluation period.

[0021] In the third aspect of the information processing method of this disclosure, in the second aspect, the operation performed by the drive system includes a movement operation that moves the object to be moved from an initial position to a target position, and a return operation that returns the object to be moved from the target position to the initial position, wherein the start time of the evaluation period is set before the start time of the movement operation, and the end time of the evaluation period is set after the completion time of the movement operation and before the start time of the return operation.

[0022] According to the third embodiment, the return operation can be excluded from the evaluation period while the movement operation can be included in the evaluation period, thereby enabling appropriate optimization of the control parameters.

[0023] In the information processing method according to the fourth aspect of this disclosure, in any one of the first to third aspects, the setting of the operation to be evaluated may include the setting of a representative operation that the drive system will perform in the optimization process, among the operations that the drive system can perform.

[0024] According to the fourth embodiment, by evaluating a representative operation, the optimization process of control parameters can be performed efficiently and appropriately.

[0025] In the information processing method according to the fifth aspect of this disclosure, in any one of the first to fourth aspects, the control processing performed by the control device based on the optimization program may include a process of outputting the control signal for causing the drive system to perform an operation multiple times until the optimization processing is completed.

[0026] According to the fifth embodiment, the control device repeatedly outputs control signals until the optimization process is completed, thereby enabling the optimization process of the control parameters to be performed appropriately.

[0027] In the information processing method according to the sixth aspect of this disclosure, in any one of the first to fifth aspects, the control processing performed by the control device based on the optimization program may include a process for acquiring operation condition information indicating the execution conditions for an operation to be performed by the drive system.

[0028] According to the sixth embodiment, the control device can easily determine the execution conditions for the operation to be performed by the drive system based on the acquired operating condition information.

[0029] In the information processing method according to the seventh aspect of this disclosure, in the sixth aspect, the operations that the drive system can perform include representative operations performed by the drive system in the optimization process and non-representative operations that the drive system does not perform in the optimization process, and the operation condition information may include operation designation information indicating whether the target operation to be performed by the drive system is the representative operation or the non-representative operation.

[0030] According to the seventh embodiment, the control device can easily determine whether the target operation is a representative operation or a non-representative operation based on the acquired operation specification information.

[0031] In the information processing method according to the eighth aspect of this disclosure, in the seventh aspect, the control processing performed by the control device based on the optimization program preferably includes processing to output the control signal relating to the target operation when the target operation is the representative operation, and processing to skip outputting the control signal relating to the target operation when the target operation is the non-representative operation.

[0032] According to the eighth aspect, the drive system performs representative operations and does not perform non-representative operations, thereby enabling efficient and appropriate optimization of control parameters.

[0033] In the ninth aspect of the present disclosure, the information processing method, in the seventh or eighth aspect, includes, in the operation performed by the drive system, a movement operation that moves the object to be moved from an initial position to a target position, and a return operation that returns the object to be moved from the target position to the initial position, and the control processing performed by the control device based on the optimization program preferably includes, when the object operation is the representative operation, a process that causes the drive system to wait for a predetermined period of time after the completion of the previous return operation and before the start of the movement operation relating to the object operation.

[0034] According to the ninth embodiment, the drive system can start the movement operation after the vibrations generated by the previous return operation have subsided, thereby enabling appropriate optimization of the control parameters.

[0035] In the information processing method according to the tenth aspect of this disclosure, in any one of the first to ninth aspects, the control processing performed by the control device based on the optimization program may include a process of registering a plurality of operations that can be set by the control signal to the drive system.

[0036] According to the tenth embodiment, by registering a plurality of operations that can be set by a control signal in the drive system, the drive system can teach the control device whether the target operation is a representative operation or a non-representative operation.

[0037] The information processing method according to the eleventh aspect of this disclosure preferably includes, in any one of the first to tenth aspects, a control process executed by the control device based on the optimization program, a process of sequentially outputting a plurality of control signals relating to a plurality of operations performed by the drive system, a process of acquiring timing specification information that specifies the output timing of each of the plurality of control signals, and a process of adjusting the output timing of each of the plurality of control signals based on the timing specification information.

[0038] According to the eleventh embodiment, with respect to the representative movement operation, the timing of the control signal output can be specified by timing specification information so that the movement operation starts after the vibration generated by the previous return operation has subsided, thereby enabling appropriate optimization of the control parameters. Furthermore, with respect to the non-representative movement operation, the control signal can be output immediately without any waiting process, thereby shortening the time required for optimization processing.

[0039] An information processing device according to a twelfth aspect of the present disclosure is an information processing device for optimizing control parameters set in a drive system that performs an operation based on a control signal input from a control device, and comprises a circuit configuration, the circuit configuration acquires setting information that sets an operation to be evaluated in an optimization process for optimizing the control parameters among the operations performed by the drive system, and generates an optimization program based on the setting information that causes the control device to perform a control process in the optimization process.

[0040] According to the twelfth embodiment, the control device can appropriately execute control processing for optimizing control parameters based on the optimization program.

[0041] A program according to a thirteenth aspect of this disclosure is a program for causing an information processing device to execute a process for optimizing control parameters set in a drive system that performs an operation based on a control signal input from a control device, wherein the process acquires setting information that sets an operation to be evaluated in an optimization process for optimizing the control parameters among the operations performed by the drive system, and generates an optimization program for causing the control device to execute a control process in the optimization process based on the setting information.

[0042] According to the 13th embodiment, the control device can appropriately execute control processing for optimizing control parameters based on the optimization program.

[0043] A drive control device according to a fourteenth aspect of the present disclosure is a drive control device for controlling a drive device that drives a moving object, and it acquires the control parameters from an information processing device that performs an update process for the control parameters in an optimization process for optimizing the control parameters set in the drive control device, acquires a control signal from a control device that performs a control process based on an optimization program generated by an information processing method according to the first aspect, and controls the drive device based on the control parameters and the control signal.

[0044] According to the fourteenth aspect, the control device can appropriately execute control processing for optimization processing of control parameters based on the optimization program. Further, the drive control device can appropriately control the drive device based on the control parameters acquired from the information processing device and the control signal acquired from the control device, thereby appropriately executing the optimization processing of the control parameters.

[0045] A control system according to a fifteenth aspect of the present disclosure includes: a control device that executes control processing based on an optimization program generated by the information processing method according to the first aspect; and the drive control device according to the fourteenth aspect.

[0046] According to the fifteenth aspect, the control device can appropriately execute control processing for optimization processing of control parameters based on the optimization program. Further, the drive control device can appropriately control the drive device based on the control parameters acquired from the information processing device and the control signal acquired from the control device, thereby appropriately executing the optimization processing of the control parameters.

[0047] The present disclosure can also be implemented as a program that causes a computer to execute each characteristic configuration included in such a method or apparatus, or as a system that operates according to the program. Needless to say, such a computer program can be distributed via a computer-readable non-transitory recording medium such as a CD-ROM or a communication network such as the Internet.

[0048] (Embodiment of the Present Disclosure) Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. Elements denoted by the same reference numerals in different drawings indicate the same or corresponding elements. In addition, the components, arrangement positions of components, connection forms, operation sequences, and the like shown in the following embodiments are examples, and are not intended to limit the present disclosure. The present disclosure is limited only by the claims. Therefore, among the components in the following embodiments, components not described in the independent claim representing the most generic concept of the present disclosure are not necessarily required to achieve the object of the present disclosure, but are described as constituting a more preferable embodiment.

[0049] Figure 1 is a simplified diagram showing the configuration of a control parameter generation system according to an embodiment of the present disclosure. The control parameter generation system comprises a control parameter generation device 1, a control device 2, and a drive system 3. The control parameter generation system optimizes the control parameters 31 by generating and updating the control parameters 31 set in the drive system 3.

[0050] The drive system 3 is, for example, a production device. The production device is a device used to produce equipment, and is a mounting device, processing device, machining device, or transport device, etc., for mounting, processing, working on, or transporting equipment. The production device is installed, for example, on a factory production line.

[0051] The drive system 3 performs operations based on the control signal S1 input from the control device 2. The drive system 3 is capable of performing multiple N operations. N is, for example, 80, but is not limited to this. The drive system 3 is not limited to a production device; it may be any other device capable of performing N operations.

[0052] The drive system 3 includes a drive control device 41, a drive device 42, a moving object 43, and a sensor 44.

[0053] The drive device 42 drives the object to be moved 43. The drive device 42 is, for example, a servo motor, a directional flow control valve for a fluid used to control a pneumatic artificial muscle arm, or a directional flow control valve for a fluid used to control a hydraulic arm. The servo motor may be a rotary motor or a linear motor.

[0054] The object to be moved 43 is an object driven by the drive device 42. If the drive device 42 is a servo motor, the object to be moved 43 is a head that transports the workpiece, or a nozzle attached to the head for picking up the workpiece. If the drive device 42 is a directional flow control valve, the object to be moved 43 is a pneumatic artificial muscle arm or a hydraulic arm.

[0055] The sensor 44 includes a position sensor that measures the position of the moving object 43, or a displacement sensor that measures the amount of movement of the moving object 43.

[0056] The drive control device 41 controls the operation of the drive device 42 by the drive signal S3. The drive control device 41 includes a storage unit 51. The storage unit 51 is configured using an HDD, SSD, or semiconductor memory, etc. For example, if the drive device 42 is a servo motor, the drive control device 41 is a servo amplifier.

[0057] The control device 2 is a higher-level controller such as a PLC (Programmable Logic Controller). The control device 2 controls the drive system 3 by inputting a control signal S1 to the drive control device 41, which indicates a command to move the object to be moved 43 to a predetermined target position. The command that the control device 2 inputs to the drive control device 41 may be a position command that indicates the position of the object to be moved 43, or a torque command that indicates the torque of the drive device 42.

[0058] The storage unit 51 stores the control parameters 31 generated and updated by the control parameter generation device 1. The drive control device 41 controls the drive device 42 with a drive signal S3 based on the control signal S1 input from the control device 2 and the control parameters 31 read from the storage unit 51. In other words, the drive control device 41 uses the control parameters 31 when controlling the drive device 42. The number of control parameters 31 is, for example, 50, but is not limited to this. It can also be considered that the control system 4, comprising the control device 2 and the drive control device 41, controls the drive device 42.

[0059] The control parameter generation device 1 is a personal computer, edge server, or cloud server, etc. The control parameter generation device 1 has an information processing unit 11, a storage unit 12, an input unit 13, a display unit 14, and a communication unit 15. The input unit 13 is configured using any input device such as a mouse, keyboard, or touch panel. The display unit 14 is configured using any display device such as a liquid crystal display or an organic EL display. The communication unit 15 is configured using a communication module corresponding to the method of communication with the control device 2 and the drive system 3.

[0060] The information processing unit 11 is configured using a circuit configuration such as an LSI and includes a processor such as a CPU. The information processing unit 11 includes an acquisition unit 21, a generation unit 22, an evaluation unit 23, an update unit 24, and an output unit 25, which are functions realized by the processor executing a program 35 read from a computer-readable non-volatile recording medium such as ROM. In other words, the program 35 is a program that causes the information processing unit 11, which is an information processing device mounted on the control parameter generation device 1, to function as an acquisition unit 21, a generation unit 22, an evaluation unit 23, an update unit 24, and an output unit 25. Details of the processing content executed by each processing unit will be described later. Note that the information processing unit 11 may be implemented within the control device 2 or within the drive system 3.

[0061] The storage unit 12 is configured using an HDD, SSD, or semiconductor memory, etc. The storage unit 12 stores control parameters 31, setting information 32, measurement data 33, estimation model 34, and program 35.

[0062] The control parameters 31 include parameters for adjusting the vibration frequency of the moving object 43, parameters for adjusting the speed of the moving object 43, parameters for adjusting the depth of the singularity in the vibration characteristics of the moving object 43, and parameters for adjusting the vibration amplitude of the moving object 43. When the drive control device 41 performs vibration damping control of the moving object 43, the control parameters 31 may include vibration damping frequency or filter coefficient. Furthermore, when the drive device 42 includes a servo motor and an encoder for detecting the rotational speed or rotational position of the servo motor, and the drive control device 41 performs feedback control based on the detection signal of the encoder, the control parameters 31 may include PID parameters such as servo gain. The control parameters 31 may include parameters that have a trade-off relationship with each other.

[0063] The setting information 32 is information for setting the operation to be evaluated among the operations performed by the drive system 3. The operation to be evaluated is the operation that is subject to evaluation by the evaluation unit 23 in the optimization process for optimizing the control parameters 31.

[0064] The setting information 32 includes period specification information for setting the evaluation period among the operations performed by the drive system 3. Setting the evaluation period includes setting the start and end times of the evaluation period. In other words, setting the operation to be evaluated includes setting the start and end times of the evaluation period among the operations performed by the drive system 3. The operations performed by the drive system 3 include an operation to move the object to be moved 43 from the initial position to the target position (hereinafter referred to as the "movement operation") and an operation to return the object to be moved 43 from the target position to the initial position (hereinafter referred to as the "return operation"). The start time of the evaluation period is set before the start time of the movement operation. The end time of the evaluation period is set after the completion time of the movement operation and before the start time of the return operation. Setting the evaluation period may be done by an operator operating the input unit 13 while looking at the setting screen displayed on the display unit 14, or it may be done automatically by the information processing unit 11 according to a predetermined rule.

[0065] Furthermore, the setting information 32 includes operation specification information for setting a representative operation from among all operations that the drive system 3 can perform. The representative operation is an operation that the drive system 3 performs in the optimization process of the control parameters 31. The setting information 32 may also include selection rules for selecting a representative operation. The selection rules include a rule for selecting at least one representative operation from among all N operations that the drive system 3 can perform. Note that the optimization process of the control parameters 31 may be performed in multiple stages, and the number of representative operations may increase as the stages progress. The selection rules may be set by an operator operating the input unit 13 while looking at the setting screen displayed on the display unit 14, or it may be performed automatically by the information processing unit 11 according to a predetermined rule.

[0066] The measurement data 33 is data showing the measured values ​​of a predetermined evaluation index measured by the sensor 44 during the execution of a representative operation. Multiple measurement data 33 are stored in the storage unit 12 to form a database. The evaluation index can be any index that can quantitatively evaluate the operation of the drive system 3, and in this embodiment, the settling time is used. The settling time is the time from when the moving object 43 starts to stop based on a command to move the moving object 43 to the target position until the moving object 43 reaches an acceptable position where it can be evaluated that it has reached the target position, that is, the time from the start of stopping to the settling time. Alternatively, the settling time is the time from when the moving object 43 starts to move based on a command to move the moving object 43 to the target position until the moving object 43 reaches an acceptable position where it can be evaluated that it has reached the target position, that is, the time from the start of movement to the settling time.

[0067] The sensor 44 measures the position of the moving object 43 in a time series during a representative operation and transmits communication data S4, which includes measurement data 33 indicating the measurement position, to the control parameter generation device 1. The communication unit 15 stores the measurement data 33 included in the received communication data S4 in the storage unit 12.

[0068] The estimation model 34 is a machine learning model for optimizing the control parameters 31. The update unit 24 uses the estimation model 34 to perform optimization, shortening the longest settling time among the settling times corresponding to each operation included in the representative operation. This updates the control parameters 31. Note that the target of optimization is not limited to the longest settling time, but may also be the average value of multiple settling times, or a predetermined number of settling times in descending order of length, or their average value.

[0069] For optimization, known algorithms such as Bayesian optimization algorithms, evolutionary strategy algorithms (CMA-ES), or genetic algorithms (GA) can be used.

[0070] Figures 2 and 3 are flowcharts showing the process of generating the optimization program P1 executed by the information processing unit 11.

[0071] First, in step SP11, the acquisition unit 21 acquires the original program P0 from the control device 2. The original program P0 is a control program that is pre-installed in the control device 2. The communication unit 15 receives communication data, including the original program P0, from the control parameter generation device 1. The acquisition unit 21 then acquires the original program P0 from the communication unit 15.

[0072] Next, in step SP12, the acquisition unit 21 acquires the setting information 32 by reading it from the storage unit 12.

[0073] Next, in step SP13, the generation unit 22 generates an optimized program P1 by modifying the original program P0 obtained in step SP11 based on the setting information 32 obtained in step SP12. The optimized program P1 is a program that causes the control device 2 to execute the control processing of the drive system 3 in the optimization processing of the control parameters 31.

[0074] Step SP13 includes steps SP131 and SP132.

[0075] First, in step SP131, the generation unit 22 generates the intermediate program P2 by adding labels to the original program P0 based on the setting information 32, which are used by the evaluation unit 23 to set the start and end times of the evaluation period. Note that the operation of adding labels to the original program P0 may also be performed by an operator operating the input unit 13 while viewing the editing screen displayed on the display unit 14.

[0076] Next, in step SP132, the generation unit 22 generates the optimization program P1A by adding conditions and processes to the intermediate program P2 based on the setting information 32. The optimization program P1A is a first example of the optimization program P1.

[0077] Figure 4 is a simplified diagram illustrating the first example of the program modification process.

[0078] In the original program P0, line L00 specifies the repetition of all operations, line L01 specifies the execution of a movement operation, and line L02 specifies the execution of a return operation.

[0079] In the intermediate program P2, the generation unit 22 adds line L11, which defines an evaluation start label indicating the start of the evaluation period, between lines L00 and L01. In other words, the generation unit 22 sets the start of the evaluation period to before the start of the movement operation. The generation unit 22 also adds line L12, which defines an evaluation end label indicating the end of the evaluation period, between lines L01 and L02. In other words, the generation unit 22 sets the end of the evaluation period to be after the completion of the movement operation and before the start of the return operation. In this embodiment, the movement operation and the return operation are distinguished by adding evaluation start labels and evaluation end labels before and after the movement operation, but this is not the only example. Any method that can distinguish between the movement operation and the return operation, such as adding flag information, may be used.

[0080] In the optimization program P1A, the generation unit 22 adds line L20, which defines the process for transmitting operation information, before line L00. The operation information is information indicating multiple operations of the drive system 3 that can be set by the control device 2 using the control signal S1. The generation unit 22 also adds line L21, which defines the conditions for repetition until the optimization process is completed, between line L20 and line L00. The generation unit 22 also adds line L22, which defines the process for acquiring operation specification information, between line L21 and line L00. The operation specification information is information indicating whether the target operation is a representative operation or a non-representative operation. The target operation is the operation that the control device 2 causes the drive system 3 to execute using the control signal S1. The generation unit 22 also adds line L23, which defines the conditions for the target operation to be a representative operation, between line L00 and line L11. Furthermore, the generation unit 22 adds line L24 between line L23 and line L11, which specifies a waiting process for a predetermined time to converge vibrations. The predetermined time may be a fixed value such as 5 seconds, or it may be a variable value that changes depending on the operation content or operation time of the previous recovery operation. Note that the generation unit 22 may also add line L24 between line L12 and line L02, not just between line L23 and line L11. In this case, the drive system 3 performs the waiting process not only before the start of the movement operation but also before the start of the recovery operation. Note that the operation specification information is an example of operation condition information that indicates the execution conditions of the operation that the control device 2 causes the drive system 3 to execute. The execution conditions of the operation may be dynamically changed according to the progress of optimization. In addition to the operation specification information, the operation condition information may also include the movement speed, or the conditions for re-operation in the event of a measurement error.

[0081] Referring to Figure 2, in step SP14, the output unit 25 outputs the optimization program P1 generated in step SP13. The communication unit 15 transmits the optimization program P1 received from the output unit 25 to the control device 2. The control device 2 installs the optimization program P1 received from the communication unit 15.

[0082] Figure 5 is a sequence diagram showing a first example of processing performed by the control device 2 and the drive control device 41 in the optimization process of the control parameter 31.

[0083] First, in process A1, the control device 2 transmits operation information to the drive control device 41 in order to register multiple operations that can be set by the control signal S1 with the drive system 3.

[0084] Next, in process A2, the drive control device 41 registers the operation information received from the control device 2 in process A1 into the storage unit 51.

[0085] In other words, the control process executed by the control device 2 based on the optimization program P1A includes the process of registering a plurality of operations that can be set by the control signal S1 with the drive system 3.

[0086] Next, in process A3, the control device 2 transmits a signal to the drive control device 41 requesting operation specification information.

[0087] Next, in process A4, the drive control device 41 transmits operation specification information to the control device 2. The control device 2 acquires the operation specification information by receiving it from the drive control device 41.

[0088] In other words, the control process executed by the control device 2 based on the optimization program P1A includes the process of acquiring operation specification information.

[0089] The control device 2 determines whether the target operation is a representative operation or a non-representative operation based on the operation specification information acquired in process A4.

[0090] If the target operation is a representative operation, then in process A5, the control device 2 performs a waiting process for a predetermined time. As a result of the control device 2 performing the waiting process, the drive system 3 also performs a waiting process corresponding to the predetermined time.

[0091] In other words, the control processing performed by the control device 2 based on the optimization program P1A includes, when the target operation is a representative operation, a process that causes the drive system 3 to wait for a predetermined period of time after the completion of the previous return operation and before the start of the movement operation related to the target operation.

[0092] Next, in process A6, the control device 2 transmits the control signal S1 for the movement included in the target operation to the drive control device 41.

[0093] In other words, the control process executed by the control device 2 based on the optimization program P1A includes the process of outputting a control signal S1 related to the target operation when the target operation is a representative operation.

[0094] Next, in process A7, the drive control device 41 executes a movement by controlling the drive device 42 with a drive signal S3 based on the control signal S1 received in process A6 and the control parameters 31 read from the storage unit 51. When the drive system 3 executes a movement, the sensor 44 transmits communication data S4, which includes measurement data 33, to the control parameter generation device 1. The communication unit 15 stores the measurement data 33 included in the communication data S4 received from the sensor 44 in the storage unit 12 and inputs it to the information processing unit 11. The acquisition unit 21 acquires the measurement data 33 from the communication unit 15. The evaluation unit 23 calculates an evaluation value of an evaluation index for the measurement data 33 acquired by the acquisition unit 21. In this embodiment, the evaluation unit 23 calculates the settling time based on the measurement data 33. The update unit 24 updates the control parameters 31 by performing optimization using the estimation model 34 to shorten the longest settling time among the one or more settling times calculated for one or more measurement data 33 related to the representative operation. The updated control parameters 31 from the update unit 24 are stored in the storage unit 12 and transmitted to the drive control device 41 by the communication unit 15. The drive control device 41 stores the received updated control parameters 31 in the storage unit 51.

[0095] Next, in process A8, the control device 2 transmits the control signal S1 for the return operation included in the target operation to the drive control device 41.

[0096] Next, in process A9, the drive control device 41 performs a return operation by controlling the drive device 42 with the drive signal S3 based on the control signal S1 received in process A8.

[0097] If the target operation is a non-representative operation, processes A5 through A9 will be skipped and not executed.

[0098] In other words, the control processing performed by the control device 2 based on the optimization program P1A includes a process to skip the output of the control signal S1 related to the target operation when the target operation is a non-representative operation.

[0099] Processes A5 to A9, which are executed when the target operation is a representative operation, or processes A5 to A9, which are skipped when the target operation is a non-representative operation, are repeatedly executed as a loop process for all operations that the drive system 3 can execute.

[0100] Furthermore, processes A3, A4, and the above loop process are repeatedly executed until the optimization process for the control parameter 31 is completed.

[0101] In other words, the control process executed by the control device 2 based on the optimization program P1A includes the process of repeatedly outputting a control signal S1 to cause the drive system 3 to perform an operation multiple times until the optimization process is completed.

[0102] The completion conditions for the optimization process may include setting a target value for the evaluation value, setting an upper limit on the number of iterations of the optimization process for all stages up to the present, or setting an upper limit on the execution time of the optimization process for all stages up to the present. For example, if a target value for the evaluation value is set as the completion condition for the optimization process, the information processing unit 11 determines that the completion condition is not met if the most recent evaluation value (longest settling time) exceeds the target value, and determines that the completion condition is met if the most recent evaluation value is less than or equal to the target value.

[0103] According to this embodiment, the control device 2 can appropriately execute the control processing for optimizing the control parameter 31 based on the optimization program P1.

[0104] Furthermore, according to this embodiment, by setting the start and end times of the evaluation period, the optimization process of the control parameter 31 can be appropriately executed.

[0105] Furthermore, according to this embodiment, the return operation can be excluded from the evaluation period while the movement operation can be included in the evaluation period, thereby enabling the optimization process of the control parameter 31 to be performed appropriately.

[0106] Furthermore, according to this embodiment, by evaluating a representative operation, the optimization process of the control parameter 31 can be performed efficiently and appropriately.

[0107] Furthermore, according to this embodiment, the control device 2 repeatedly outputs the control signal S1 until the optimization process is completed, thereby enabling the optimization process of the control parameter 31 to be executed appropriately.

[0108] Furthermore, according to this embodiment, the control device 2 can easily determine whether the target operation is a representative operation or a non-representative operation based on the acquired operation specification information.

[0109] Furthermore, according to this embodiment, since the drive system 3 performs representative operations and does not perform non-representative operations, the optimization process of the control parameters 31 can be performed efficiently and appropriately.

[0110] Furthermore, according to this embodiment, the drive system 3 can start the movement operation after the vibrations generated by the previous return operation have subsided, so that the optimization process of the control parameters 31 can be properly executed.

[0111] Furthermore, according to this embodiment, by registering a plurality of operations that can be set by the control signal S1 in the drive system 3, the drive system 3 can inform the control device 2 whether the target operation is a representative operation or a non-representative operation.

[0112] (Modification) The generation unit 22 may generate an optimization program P1B instead of an optimization program P1A. Optimization program P1B is a second example of optimization program P1.

[0113] Figure 6 is a simplified diagram illustrating a second example of the program modification process.

[0114] The original program P0 and the intermediate program P2 are the same as in the first example shown in Figure 4.

[0115] In the optimization program P1B, the generation unit 22 adds line L30, which defines the process for transmitting operation information, before line L00. The generation unit 22 also adds line L31, which defines the repetition conditions until the optimization process is completed, between line L30 and line L00. The generation unit 22 also adds line L32 between line L00 and line L11. Line L32 defines the process for adjusting the output timing of the control signal S1 related to movement. The generation unit 22 also adds line L33 between line L12 and line L02. Line L33 defines the process for acquiring timing specification information that specifies the output timing of the control signal S1 related to return operation. The generation unit 22 also adds line L34 between line L33 and line L02. Line L34 defines the process for adjusting the output timing of the control signal S1 related to return operation. The generation unit 22 also adds line L35 after line L02. Line L35 defines a process for acquiring timing specification information that specifies the output timing of the control signal S1 related to the movement operation included in the next target operation.

[0116] Figure 7 is a sequence diagram showing a second example of processing performed by the control device 2 and the drive control device 41 during the optimization process of the control parameter 31.

[0117] First, in process B1, the control device 2 transmits operation information to the drive control device 41 in order to register multiple operations that can be set by the control signal S1 with the drive system 3.

[0118] Next, in process B2, the drive control device 41 registers the operation information received from the control device 2 in process B1 into the storage unit 51.

[0119] If the target operation is a representative operation, processes B3 to B10 are executed.

[0120] In process B3, the control device 2 adjusts the output timing of the control signal S1 for the movement operation to be transmitted in process B4, based on the timing specification information received in process B10 or process B16 related to the previous target operation. In process B10 or process B16, the drive control device 41 determines whether the next target operation is a representative operation or a non-representative operation based on the setting information 32. If the next target operation is a representative operation, the drive control device 41 sets the output timing of the control signal S1 for the movement operation included in the next target operation to be after a predetermined time has elapsed from the current time for vibrations caused by the return operation to subside. If the next target operation is a non-representative operation, the drive control device 41 sets the output timing of the control signal S1 for the movement operation included in the next target operation to be an immediate timing that does not involve waiting for vibrations caused by the return operation to subside.

[0121] Next, in process B4, the control device 2 transmits the control signal S1 for the movement included in the target operation to the drive control device 41.

[0122] Next, in process B5, the drive control device 41 executes a movement by controlling the drive device 42 with a drive signal S3 based on the control signal S1 received in process B4 and the control parameters 31 read from the storage unit 51. When the drive system 3 executes a movement, the sensor 44 transmits communication data S4, including measurement data 33, to the control parameter generation device 1. The communication unit 15 stores the measurement data 33 included in the communication data S4 received from the sensor 44 in the storage unit 12 and inputs it to the information processing unit 11. The acquisition unit 21 acquires the measurement data 33 from the communication unit 15. The evaluation unit 23 calculates an evaluation value of the evaluation index for the measurement data 33 acquired by the acquisition unit 21. In this modified example, the evaluation unit 23 calculates the settling time based on the measurement data 33. The update unit 24 updates the control parameters 31 by performing optimization using the estimation model 34 to shorten the longest settling time among the one or more settling times calculated for one or more measurement data 33 related to the representative operation. The updated control parameters 31 from the update unit 24 are stored in the storage unit 12 and transmitted to the drive control device 41 by the communication unit 15. The drive control device 41 stores the received updated control parameters 31 in the storage unit 51.

[0123] Next, in process B6, the drive control device 41 sets the output timing of the control signal S1 for the return operation included in the target operation, and transmits timing specification information indicating the output timing to the control device 2. The output timing of the control signal S1 for the return operation may be a timing after a predetermined time has elapsed from the current time for vibrations caused by the movement operation to subside, or it may be an immediate timing without any waiting period for vibrations caused by the movement operation to subside.

[0124] Next, in process B7, the control device 2 adjusts the output timing of the return operation control signal S1 to be transmitted in process B8 based on the timing specification information received in process B6.

[0125] Next, in process B8, the control device 2 transmits the control signal S1 for the return operation included in the target operation to the drive control device 41.

[0126] Next, in process B9, the drive control device 41 performs a return operation by controlling the drive device 42 with the drive signal S3 based on the control signal S1 received in process B8.

[0127] Next, in process B10, the drive control device 41 sets the output timing of the control signal S1 for the movement operation included in the next target operation, and transmits timing specification information indicating the said output timing to the control device 2.

[0128] If the target operation is a non-representative operation, processes B11 to B16 are executed.

[0129] In process B11, the control device 2 adjusts the output timing of the control signal S1 for movement to be transmitted in process B12, based on the timing specification information received in process B10 or process B16 related to the previous target operation.

[0130] Next, in process B12, the control device 2 transmits the control signal S1 for the movement included in the target operation to the drive control device 41.

[0131] If the target operation is a non-representative operation, the drive control device 41 will skip the operation without executing the movement operation even if it receives the control signal S1 in process B12.

[0132] Next, in process B13, the drive control device 41 sets the output timing of the control signal S1 for the return operation included in the target operation, and transmits timing specification information indicating the output timing to the control device 2. The output timing of the control signal S1 for the return operation is an immediate timing without any waiting period for vibration convergence.

[0133] Next, in process B14, the control device 2 adjusts the output timing of the return operation control signal S1 to be transmitted in process B15 based on the timing specification information received in process B13.

[0134] Next, in process B15, the control device 2 transmits a control signal S1 for the return operation included in the target operation to the drive control device 41.

[0135] If the target operation is a non-representative operation, the drive control device 41 will skip the process B15 without executing the recovery operation even if it receives the control signal S1.

[0136] Next, in process B16, the drive control device 41 sets the output timing of the control signal S1 for the movement operation included in the next target operation, and transmits timing specification information indicating the said output timing to the control device 2.

[0137] Processes B3 to B10, which are executed when the target operation is a representative operation, or processes B11 to B16, which are executed when the target operation is a non-representative operation, are repeatedly executed as a loop process for all operations that the drive system 3 can perform.

[0138] Furthermore, the above loop processing related to all operations is repeatedly executed until the optimization process of the control parameter 31 is completed.

[0139] Thus, the control processing executed by the control device 2 based on the optimization program P1B includes processes B4, B8, B12, and B15 that sequentially output multiple control signals S1 related to multiple operations performed by the drive system 3. Furthermore, the control processing executed by the control device 2 based on the optimization program P1B includes processes B6, B10, B13, and B16 that acquire timing specification information specifying the output timing of each of the multiple control signals S1. Furthermore, the control processing executed by the control device 2 based on the optimization program P1B includes processes B3, B7, B11, and B14 that adjust the output timing of each of the multiple control signals S1 based on the timing specification information.

[0140] According to this modified version, for representative movement operations, the timing of the output of the control signal S1 can be specified by timing specification information so that the movement operation starts after the vibrations caused by the previous return operation have subsided, thereby enabling appropriate optimization of the control parameters 31. Furthermore, for non-representative movement operations, the control signal S1 can be output immediately without any waiting process, thereby shortening the time required for optimization processing.

[0141] The evaluation indicators may include evaluation indicators related to processing quality, evaluation indicators related to productivity, or both. Examples of evaluation indicators related to processing quality may include processing accuracy, shape error, defect rate, and dimensional error. Examples of evaluation indicators related to productivity may include settling time, processing time, and cycle time. Here, the information processing device may acquire the start and end times of the evaluation period for which the evaluation indicators should be calculated as setting information for setting the operation to be evaluated. This makes it possible to limit the evaluation target to, for example, the period from the start of processing to the end of processing, or the period from the start of positioning to the completion of settling, thereby enabling appropriate evaluation while suppressing the influence of unnecessary return operations and standby operations. The information processing device may also set a representative operation among multiple processing operations or transport operations that has a significant impact on the evaluation indicators. This makes it possible to optimize control parameters by prioritizing operations that strongly affect processing quality or productivity compared to the case where all operations are targeted, and to execute the optimization process efficiently.

[0142] (Combinable Configurations) The following describes a group of combinable configurations, including the configurations disclosed herein.

[0143] (First Configuration) The first aspect of the first configuration is an information processing method for supporting the management of an optimization process, wherein an information processing unit acquires schedule information indicating the schedule of the optimization process, generates a figure corresponding to each of at least one evaluation indicators applied to the optimization process, generates a schedule image by arranging the figures along a first direction which is the direction in which the time axis extends based on the schedule information, and outputs the schedule image.

[0144] In a second embodiment of the first configuration, the at least one evaluation index includes a first evaluation index and a second evaluation index different from the first evaluation index, and the information processing unit generates a first figure corresponding to the first evaluation index and a second figure corresponding to the second evaluation index in the generation of the figures, and when the time during which the first evaluation index is applied to the optimization process overlaps with the time during which the second evaluation index is applied, the arrangement of the figures arranges the first figure and the second figure side by side in a second direction intersecting the first direction.

[0145] In a third embodiment of the first configuration, the information processing unit further sets weights for the at least one evaluation index and determines the shape of the figure according to the weights.

[0146] In a fourth embodiment of the first configuration, the information processing unit further sets weights for the at least one evaluation index, changes the weights over time, and outputs a graph showing the changes in the weights.

[0147] In a fifth aspect of the first configuration, the information processing unit further outputs a preset showing candidate weight change functions that define the change in weights over time, and determines the weight change function by accepting an operation to select the preset.

[0148] In a sixth embodiment of the first configuration, the information processing unit further acquires essential condition information indicating essential conditions, sets the essential conditions in the optimization process based on the essential condition information, and the essential conditions include achieving the target of at least one evaluation indicator.

[0149] In the seventh embodiment of the first configuration, the information processing unit further determines whether the essential conditions have been met, and if the essential conditions have not been met, it lowers the evaluation value of the optimization process.

[0150] In the eighth embodiment of the first configuration, the at least one evaluation index includes a preceding evaluation index and a succeeding evaluation index applied to the optimization process after the preceding evaluation index, wherein the information processing unit further determines whether the target of the preceding evaluation index has been achieved in the optimization process to which the preceding evaluation index is applied, and if the target of the preceding evaluation index has been achieved, sets the achievement of the target of the preceding evaluation index as an essential condition for the succeeding optimization process to which the succeeding evaluation index is applied.

[0151] In the ninth embodiment of the first configuration, the at least one evaluation index includes a prior evaluation index and a subsequent evaluation index applied to the optimization process after the prior evaluation index, wherein the information processing unit further determines whether the target of the prior evaluation index has been achieved, and if the target of the prior evaluation index has been achieved, sets the achievement of the target of the prior evaluation index as an essential condition for the subsequent optimization process to which the subsequent evaluation index is applied, and sets the achievement of the target of the subsequent evaluation index as an additional condition for the subsequent optimization process.

[0152] In a tenth embodiment of the first configuration, the at least one evaluation index includes a prior evaluation index and a subsequent evaluation index applied to the optimization process after the prior evaluation index, wherein the information processing unit further sets the condition that the subsequent evaluation index satisfies the limit value if, as a result of the optimization process to which the prior evaluation index is applied, the prior evaluation index does not improve, is output, and the subsequent evaluation index satisfies the limit value.

[0153] In the eleventh embodiment of the first configuration, the information processing unit further assigns thumbnail information to the figure that represents the evaluation index to which the figure corresponds.

[0154] In a twelfth embodiment of the first configuration, the thumbnail information includes information indicating a target set for the at least one evaluation indicator.

[0155] In the thirteenth embodiment of the first configuration, the information processing unit further makes the display mode of the figure corresponding to at least one evaluation index currently applied to the optimization process different from the display mode of the figure corresponding to at least one evaluation index not currently applied to the optimization process.

[0156] In the fourteenth embodiment of the first configuration, the information processing unit outputs a schedule image in which a detail button is superimposed on the figure, and further outputs the details of the evaluation indicator corresponding to the figure, or the settings of the evaluation indicator corresponding to the figure, depending on whether the detail button is selected.

[0157] In the 15th embodiment of the first configuration, the information processing unit further receives an operation to select the figure and outputs details of the evaluation indicators corresponding to the selected figure, or the settings of the evaluation indicators corresponding to the selected figure.

[0158] In the sixteenth embodiment of the first configuration, the information processing unit further determines the size of the figure in the first direction according to the length of time for which the at least one evaluation index is applied to the optimization process.

[0159] In the seventeenth embodiment of the first configuration, the information processing unit further receives a resize instruction to change the size of the figure in the first direction, generates a resized figure by changing the size of the figure based on the resize instruction, and changes the length of time for which the evaluation index corresponding to the resized figure is applied to the optimization process according to the size of the resized figure in the first direction.

[0160] In the eighteenth embodiment of the first configuration, the information processing unit further receives branching condition information indicating branching conditions, and selects from a plurality of options the at least one evaluation index to be applied to the optimization process based on the branching conditions.

[0161] In the 19th embodiment of the first configuration, the plurality of options include a first option and a second option different from the first option, and the information processing unit further arranges a first option figure corresponding to the first option and a second option figure corresponding to the second option along a second direction intersecting the first direction in the schedule image, and displays a branching button on the schedule image to indicate that the schedule is branching.

[0162] In the 20th embodiment of the first configuration, the optimization process is a multi-objective optimization process in which a plurality of evaluation indicators are set, and the information processing unit further acquires the processing result of the multi-objective optimization process, calculates a Pareto solution based on the processing result, plots the processing result including the Pareto solution in a processing result display space, and outputs the processing result display space.

[0163] In a 21st embodiment of the first configuration, the information processing unit further receives a selection operation to select the processing result plotted in the processing result display space, and outputs details of the processing result selected in the selection operation.

[0164] In the 22nd embodiment of the first configuration, the information processing unit further determines a plotting target area when plotting a new processing result in the processing result display space, based on the processing result selected in the selection operation.

[0165] In the 23rd embodiment of the first configuration, the information processing unit further receives an arrangement change operation to change the arrangement of the figures in the first direction, and changes the order in which the optimization process is performed in accordance with the arrangement change operation.

[0166] In the 24th embodiment of the first configuration, the information processing unit further acquires sequence information indicating the order in which the at least one evaluation index is applied to the optimization process, and generates schedule information based on the sequence information in which each of the targets of the at least one evaluation index is satisfied in the order indicated by the sequence information.

[0167] In the 25th embodiment of the first configuration, the information processing unit further displays at least one of the following during the execution of the optimization process: a progress line indicating the progress of the optimization process, the estimated remaining operating time of the optimization process, and the number of operations, which is the number of times the production apparatus has been operated using the control parameters generated by the optimization process.

[0168] A 26th aspect of the first configuration is an information processing device for supporting the management of an optimization process, comprising a circuit configuration, the circuit configuration acquiring schedule information indicating the schedule of the optimization process, generating a figure corresponding to each of at least one evaluation index applied to the optimization process, generating a schedule image by arranging the figures along a first direction which is the direction in which the time axis extends based on the schedule information, and outputting the schedule image.

[0169] The 27th aspect of the first configuration is a program for causing an information processing device to execute a process for supporting the management of an optimization process, wherein the process acquires schedule information indicating the schedule of the optimization process, generates a figure corresponding to each of at least one evaluation index applied to the optimization process, generates a schedule image by arranging the figures along a first direction which is the direction in which the time axis extends based on the schedule information, and outputs the schedule image.

[0170] (Second Configuration) The first aspect of the second configuration is an information processing method for supporting the management of an optimization process, wherein an information processing unit acquires evaluation indicator information including a target for at least one evaluation indicator applied to the optimization process, acquires predicted data that satisfies the target for the at least one evaluation indicator based on the evaluation indicator information, and displays the predicted data.

[0171] In the second embodiment of the second configuration, the information processing unit, in acquiring the prediction data, acquires the original data from the original data storage unit, generates composite data by transforming the original data, and acquires the composite data as the prediction data.

[0172] In the third embodiment of the second configuration, the source data is waveform data showing the progression of a measurement signal over time, and in generating the composite data, the information processing unit performs at least one of the following: stretching the waveform data in the time axis direction, stretching the waveform data in the amplitude direction, and adding random noise.

[0173] In the fourth embodiment of the second configuration, the information processing unit acquires evaluation indicator information that indicates the target of each of the multiple evaluation indicators when acquiring the evaluation indicator information, and acquires prediction data that satisfies the target of each of the multiple evaluation indicators when acquiring the prediction data.

[0174] In a fifth embodiment of the second configuration, the information processing unit acquires evaluation indicator information that shows the respective targets of the multiple evaluation indicators when acquiring the evaluation indicator information, acquires prediction data that satisfies the respective targets of the multiple evaluation indicators and prediction data that satisfies the target of at least one of the multiple evaluation indicators when acquiring the prediction data, and displays the prediction data that satisfies the respective targets of the multiple evaluation indicators and prediction data that satisfies the target of at least one of the multiple evaluation indicators when displaying the prediction data.

[0175] In the sixth embodiment of the second configuration, the prediction data includes a position control waveform showing the change in the position of the object to be driven over time, or a torque control waveform showing the change in torque value over time.

[0176] In the seventh embodiment of the second configuration, the optimization process is a process for optimizing the control parameters in a device that performs an operation based on the control parameters.

[0177] An eighth aspect of the second configuration is an information processing device for supporting the management of an optimization process, comprising a circuit configuration, the circuit configuration acquiring evaluation index information including a target for at least one evaluation index applied to the optimization process, acquiring predicted data that satisfies the target for the at least one evaluation index based on the evaluation index information, and displaying the predicted data.

[0178] A ninth aspect of the second configuration is a program for causing an information processing device to perform a process to support the management of an optimization process, wherein the process acquires evaluation indicator information including a target for at least one evaluation indicator applied to the optimization process, acquires predicted data that satisfies the target for the at least one evaluation indicator based on the evaluation indicator information, and displays the predicted data.

[0179] (Third Configuration) The first aspect of the third configuration is an information processing method for supporting the management of an optimization process, wherein an information processing unit outputs question information indicating a question to the user regarding the optimization process, obtains answer information indicating an answer to the question information, and generates evaluation index information indicating at least one evaluation index to be applied to the optimization process based on the answer information.

[0180] In a second embodiment of the third configuration, the at least one evaluation index is a plurality of evaluation indexes, and the generation of the evaluation index information by the information processing unit includes determining the order in which the plurality of evaluation indexes are applied to the optimization process.

[0181] In a third embodiment of the third configuration, the output of the question information by the information processing unit includes displaying a plurality of waveform data showing the operating waveform of the device, and outputting question information that prompts the user to select a waveform data from the plurality of waveform data to be used as the target operating waveform for waveform improvement by the optimization process.

[0182] In a fourth embodiment of the third configuration, the output of the question information by the information processing unit includes displaying a plurality of waveform data showing the operating waveform of the device and outputting question information that prompts the user to select a waveform data from the plurality of waveform data to be accepted as an operating waveform during the waveform improvement process by the optimization process.

[0183] In a fifth embodiment of the third configuration, the output of the question information by the information processing unit includes displaying a plurality of waveform data showing the operating waveform of the device, and outputting question information that asks about the difficulty of waveform improvement by the optimization process for each of the plurality of waveform data.

[0184] In a sixth embodiment of the third configuration, the output of the question information by the information processing unit includes outputting question information that asks for the ranking of the difficulty levels of waveform improvement by the optimization process for each of the plurality of waveform data.

[0185] In the seventh embodiment of the third configuration, the information processing unit further acquires sequence information indicating the order in which the at least one evaluation index is applied to the optimization process, and generates schedule information based on the sequence information in which each of the targets of the at least one evaluation index is satisfied in the order indicated by the sequence information.

[0186] The eighth aspect of the third configuration is an information processing device for supporting the management of an optimization process, comprising a circuit configuration, the circuit configuration outputting question information indicating a question to the user regarding the optimization process, acquiring answer information indicating an answer to the question information, and generating evaluation index information indicating at least one evaluation index applied to the optimization process based on the answer information.

[0187] A ninth aspect of the third configuration is a program for causing an information processing device to execute a process for supporting the management of an optimization process, wherein the process outputs question information indicating a question to the user regarding the optimization process, obtains answer information indicating an answer to the question information, and generates evaluation index information indicating at least one evaluation index to be applied to the optimization process based on the answer information.

[0188] (Fourth Configuration) The first aspect of the fourth configuration is an information processing method for supporting the management of an optimization process, wherein an information processing unit displays superimposed data in which a modified figure is superimposed on at least one operation data indicating the operation of a device, acquires operation information indicating an operation to change the display manner of the modified figure, and changes the settings relating to the evaluation index applied to the optimization process based on the modified figure whose display manner has been changed.

[0189] In the second embodiment of the fourth configuration, the information processing unit acquiring the operation information includes acquiring deformation operation information indicating an operation to change the shape of the modified figure, acquiring movement operation information indicating an operation to move the position of the modified figure, and color change operation information indicating a change in the color of the modified figure, and the information processing unit changing the settings related to the evaluation index includes changing the settings related to the evaluation index based on at least one of the shape of the modified figure after deformation, the position of the modified figure after movement, and the color of the modified figure after color change.

[0190] In a third embodiment of the fourth configuration, the operation of the device is an operation in which the device moves an object to a target position, the evaluation index includes the sum of the accumulated values ​​of deviation time or position deviation amount for which the position deviation between the position of the object and the target position deviates from a reference range, the modified figure includes a reference range modified figure having a linear or curved shape, the information processing unit acquiring the deformation operation information includes acquiring deformation operation information indicating an operation to change the shape of the reference range modified figure, and the information processing unit changing the setting of the evaluation index includes changing the reference range based on the shape of the modified reference range modified figure.

[0191] In the fourth embodiment of the fourth configuration, the reference range changing figure has a linear shape, the information processing unit acquiring the operation information includes acquiring operation information indicating an operation to change at least one of the slope and intercept of the reference range changing figure, and the information processing unit changing the setting relating to the evaluation index includes changing the reference range based on at least one of the slope and intercept of the reference range changing figure.

[0192] In the fifth embodiment of the fourth configuration, the reference range changing figure includes an upper limit figure corresponding to the upper limit of the reference range and a lower limit figure corresponding to the lower limit of the reference range.

[0193] In a sixth embodiment of the fourth configuration, the operation of the device is an operation in which the device moves an object to a target position, the evaluation index includes the length of the settling time until the positional deviation between the position of the object and the target position converges to an acceptable range, the modified figure includes a settling time modified figure, the information processing unit acquiring the movement operation information includes acquiring movement operation information indicating an operation to move the position of the settling time modified figure, and the information processing unit changing the settings related to the evaluation index includes changing the target of the settling time based on the amount of movement of the settling time modified figure.

[0194] In a seventh embodiment of the fourth configuration, the operation of the device is an operation in which the device moves an object to a target position, the evaluation index includes the length of the settling time until the positional deviation between the position of the object and the target position converges to an acceptable range, the acceptable range includes a first acceptable range which is the acceptable range for a first period before the target settling time, and a second acceptable range which is the acceptable range for a second period after the target settling time, the evaluation index includes the sum of the accumulated values ​​of the deviation time or positional deviation amount for which the positional deviation between the position of the object and the target position deviates from the second acceptable range, the modified figure includes a second acceptable range modified figure, the acquisition of the movement operation information by the information processing unit includes acquiring movement operation information indicating an operation to move the position of the second acceptable range modified figure, and the setting of the evaluation index by the information processing unit includes changing the second acceptable range based on the amount of movement of the second acceptable range modified figure.

[0195] In the eighth aspect of the fourth configuration, the operation of the device is an operation in which the device moves an object to a target position, the at least one operation data includes a target position figure indicating the target position, the modified figure includes a gradient figure with different coloring patterns depending on the deviation from the target position figure, the coloring patterns correspond to the magnitude of the weight when calculating the evaluation value of the at least one operation data, the information processing unit acquiring the deformation operation information includes acquiring deformation operation information indicating an operation to change the shape of the gradient figure, and the information processing unit changing the setting of the evaluation index includes changing the magnitude of the weight based on the shape of the gradient figure after deformation.

[0196] In the ninth aspect of the fourth configuration, the at least one operation data is a plurality of operation data, and the information processing unit changing the settings relating to the evaluation index includes changing the evaluation criteria for the plurality of operation data, and the information processing unit further calculates the evaluation value for each of the plurality of operation data based on the changed evaluation criteria, and displays the operation data with the highest evaluation value among the plurality of operation data, or the top plurality of operation data with high evaluation values.

[0197] In the tenth embodiment of the fourth configuration, the information processing unit further superimposes the modified figure onto the operation data with the highest evaluation value, or onto the top multiple operation data with high evaluation values.

[0198] In the eleventh aspect of the fourth configuration, the information processing unit further generates an evaluation histogram showing the classification of the plurality of operation data according to the evaluation value of each of the plurality of operation data, and displays the evaluation histogram.

[0199] In the twelfth embodiment of the fourth configuration, the at least one operation data is a plurality of operation data, and the information processing unit changing the settings relating to the evaluation index includes changing the evaluation criteria for the plurality of operation data, and the information processing unit further calculates the evaluation value for each of the plurality of operation data based on the changed evaluation criteria, selects at least two of the plurality of operation data, and displays a display screen including the at least two operation data sorted in descending order of evaluation value.

[0200] In the thirteenth embodiment of the fourth configuration, the information processing unit further acquires first sequence information indicating the order of user evaluations for the at least two operation data selected by the information processing unit, determines whether the order indicated by the first sequence information matches the order of evaluations for the at least two operation data determined by the information processing unit, and outputs the determination result.

[0201] The 14th aspect of the fourth configuration is an information processing device for supporting the management of an optimization process, comprising a circuit configuration, the circuit configuration displays superimposed data in which a modified figure is superimposed on operation data indicating the operation of the device, acquires operation information indicating an operation to change the display mode of the modified figure, and changes the settings relating to evaluation indicators applied to the optimization process based on the modified figure whose display mode has been changed.

[0202] The 15th aspect of the fourth configuration is a program for causing an information processing device to execute a process for supporting the management of an optimization process, wherein the process displays superimposed data in which a modified figure is superimposed on operation data indicating the operation of the device, obtains operation information indicating an operation to change the display manner of the modified figure, and changes the settings relating to the evaluation index applied to the optimization process based on the modified figure whose display manner has been changed.

[0203] (Fifth Configuration) The first aspect of the fifth configuration is an information processing method for optimizing control parameters set in a drive system that performs an operation based on a control signal input from a control device, wherein the information processing device acquires setting information that sets an operation to be evaluated among the operations performed by the drive system, which is to be evaluated in the optimization process for optimizing the control parameters, and generates an optimization program based on the setting information that causes the control device to perform the control process in the optimization process.

[0204] In the second embodiment of the fifth configuration, the setting of the operation to be evaluated includes setting the start and end times of the evaluation period among the operations performed by the drive system.

[0205] In a third embodiment of the fifth configuration, the operation performed by the drive system includes a movement operation that moves the object to be moved from an initial position to a target position, and a return operation that returns the object to be moved from the target position to the initial position, wherein the start time of the evaluation period is set before the start time of the movement operation, and the end time of the evaluation period is set after the completion time of the movement operation and before the start time of the return operation.

[0206] In the fourth embodiment of the fifth configuration, the setting of the operation to be evaluated includes setting a representative operation that the drive system will perform in the optimization process, among the operations that the drive system can perform.

[0207] In a fifth embodiment of the fifth configuration, the control process performed by the control device based on the optimization program includes outputting the control signal for causing the drive system to perform an operation multiple times until the optimization process is completed.

[0208] In the sixth embodiment of the fifth configuration, the control process executed by the control device based on the optimization program includes a process for acquiring operating condition information indicating the execution conditions for an operation to be performed by the drive system.

[0209] In the seventh embodiment of the fifth configuration, the operations that the drive system can perform include representative operations performed by the drive system in the optimization process and non-representative operations that the drive system does not perform in the optimization process, and the operation condition information includes operation specification information indicating whether the target operation to be performed by the drive system is the representative operation or the non-representative operation.

[0210] In the eighth embodiment of the fifth configuration, the control processing performed by the control device based on the optimization program includes: a process of outputting the control signal relating to the target operation when the target operation is the representative operation; and a process of skipping the output of the control signal relating to the target operation when the target operation is the non-representative operation.

[0211] In the ninth embodiment of the fifth configuration, the operation performed by the drive system includes a movement operation that moves the object to be moved from an initial position to a target position, and a return operation that returns the object to be moved from the target position to the initial position, and the control processing performed by the control device based on the optimization program includes, when the object operation is the representative operation, a process that causes the drive system to wait for a predetermined period of time after the completion of the previous return operation and before the start of the movement operation related to the object operation.

[0212] In the tenth embodiment of the fifth configuration, the control process executed by the control device based on the optimization program includes a process of registering a plurality of operations that can be set by the control signal with the drive system.

[0213] In the eleventh embodiment of the fifth configuration, the control process performed by the control device based on the optimization program includes: a process of sequentially outputting a plurality of control signals relating to a plurality of operations performed by the drive system; a process of acquiring timing specification information that specifies the output timing of each of the plurality of control signals; and a process of adjusting the output timing of each of the plurality of control signals based on the timing specification information.

[0214] A twelfth aspect of the fifth configuration is an information processing device for optimizing control parameters set in a drive system that performs an operation based on a control signal input from a control device, comprising a circuit configuration, the circuit configuration acquiring setting information for setting an operation to be evaluated in an optimization process for optimizing the control parameters among the operations performed by the drive system, and generating an optimization program for causing the control device to perform a control process in the optimization process based on the setting information.

[0215] The thirteenth aspect of the fifth configuration is a program for causing an information processing device to execute a process for optimizing control parameters set in a drive system that performs an operation based on a control signal input from a control device, wherein the process acquires setting information that sets an operation to be evaluated in an optimization process for optimizing the control parameters among the operations performed by the drive system, and generates an optimization program for causing the control device to execute a control process in the optimization process based on the setting information.

[0216] The 14th aspect of the fifth configuration is a drive control device for controlling a drive device that drives a moving object, wherein the control device obtains the control parameters from an information processing device that performs an update process for the control parameters in an optimization process for optimizing the control parameters set in the drive control device, obtains a control signal from a control device that performs a control process based on an optimization program generated by the information processing method described in claim 1, and controls the drive device based on the control parameters and the control signal.

[0217] The 15th aspect of the fifth configuration comprises a control device that performs control processing based on an optimization program generated by the information processing method described in the first aspect of the fifth configuration, and a drive control device described in the 14th aspect of the fifth configuration.

[0218] This disclosure is broadly applicable to systems that generate control parameters, etc.

Claims

1. An information processing method for optimizing control parameters set in a drive system that performs an operation based on a control signal input from a control device, wherein the information processing device acquires setting information that sets an operation to be evaluated among the operations performed by the drive system, which is to be evaluated in an optimization process for optimizing the control parameters, and generates an optimization program based on the setting information that causes the control device to perform a control process in the optimization process.

2. The information processing method according to claim 1, wherein the setting of the operation to be evaluated includes setting the start and end times of the evaluation period among the operations performed by the drive system.

3. The information processing method according to claim 2, wherein the operation performed by the drive system includes a movement operation that moves the object to be moved from an initial position to a target position, and a return operation that returns the object to be moved from the target position to the initial position, the start time of the evaluation period is set before the start time of the movement operation, and the end time of the evaluation period is set after the completion time of the movement operation and before the start time of the return operation.

4. The information processing method according to claim 1, wherein the setting of the operation to be evaluated includes setting a representative operation to be performed by the drive system in the optimization process from among the operations that the drive system can perform.

5. The information processing method according to claim 1, wherein the control process performed by the control device based on the optimization program includes a process of outputting the control signal for causing the drive system to perform an operation multiple times until the optimization process is completed.

6. The information processing method according to claim 1, wherein the control processing performed by the control device based on the optimization program includes a process for acquiring operating condition information indicating the conditions for performing an operation to be performed by the drive system.

7. The information processing method according to claim 6, wherein the operations that the drive system can perform include representative operations performed by the drive system in the optimization process and non-representative operations that the drive system does not perform in the optimization process, and the operation condition information includes operation designation information indicating whether the target operation to be performed by the drive system is the representative operation or the non-representative operation.

8. The information processing method according to claim 7, wherein the control processing performed by the control device based on the optimization program includes: a process of outputting the control signal relating to the target operation when the target operation is the representative operation; and a process of skipping the output of the control signal relating to the target operation when the target operation is the non-representative operation.

9. The information processing method according to claim 7, wherein the operation performed by the drive system includes a movement operation that moves the object to be moved from an initial position to a target position, and a return operation that returns the object to be moved from the target position to the initial position, and the control processing performed by the control device based on the optimization program includes, when the object operation is the representative operation, a process that causes the drive system to wait for a predetermined period of time after the completion of the previous return operation and before the start of the movement operation relating to the object operation.

10. The information processing method according to claim 1, wherein the control process executed by the control device based on the optimization program includes a process of registering a plurality of operations that can be set by the control signal to the drive system.

11. The information processing method according to claim 1, wherein the control process executed by the control device based on the optimization program includes: a process of sequentially outputting a plurality of control signals relating to a plurality of operations performed by the drive system; a process of acquiring timing specification information that specifies the output timing of each of the plurality of control signals; and a process of adjusting the output timing of each of the plurality of control signals based on the timing specification information.

12. An information processing device for optimizing control parameters set in a drive system that performs an operation based on a control signal input from a control device, comprising a circuit configuration, the circuit configuration acquiring setting information for setting an operation to be evaluated among the operations performed by the drive system that is to be evaluated in an optimization process for optimizing the control parameters, and generating an optimization program for causing the control device to perform a control process in the optimization process based on the setting information.

13. A program for causing an information processing device to execute a process for optimizing control parameters set in a drive system that performs an operation based on a control signal input from a control device, wherein the process includes: acquiring setting information to set an operation to be evaluated in an optimization process for optimizing the control parameters among the operations performed by the drive system; and generating an optimization program for causing the control device to execute a control process in the optimization process based on the setting information.

14. A drive control device for controlling a drive device that drives a moving object, wherein the drive control device obtains the control parameters from an information processing device that performs an update process for the control parameters in an optimization process for optimizing the control parameters set in the drive control device, obtains a control signal from a control device that performs a control process based on an optimization program generated by the information processing method described in claim 1, and controls the drive device based on the control parameters and the control signal.

15. A control system comprising: a control device that performs control processing based on an optimization program generated by the information processing method described in claim 1; and a drive control device described in claim 14.

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