Parameter Automatic Adjustment Device, Parameter Automatic Adjustment System, and Parameter Automatic Adjustment Method

Abstract

The present disclosure relates to a technology for automatically and efficiently searching for an equipment control parameter. One aspect of the present disclosure relates to an automatic parameter adjustment device comprising: a plurality of equipment models obtained by modeling equipment; a control parameter setting unit that sets a plurality of first control parameters to be used for the plurality of equipment models in a first trial, and a second control parameter to be used for the equipment in the first trial; and a comparison unit that compares the results of operating the plurality of equipment models by the plurality of first control parameters in the first trial with the result of operating the real equipment by the second control parameter in the first trial. The control parameter setting unit selects a control parameter to be used in a second trial on the basis of the first result of comparing the results of operating the equipment models in the first trial with the result of operating the real equipment in the first trial.

Description

Technical Field

[0001] The present disclosure relates to a parameter automatic adjustment device, a parameter automatic adjustment system, and a parameter automatic adjustment method.

Background Art

[0002] In production equipment used in factories, etc., such as component mounters, assembly robots, etc., a plurality of servo control motors are combined and complex and sophisticated operation control is performed. In such devices, the operation of the controlled object is controlled according to a large number of control parameters. In order to obtain desired performance, the user empirically adjusts the control parameters.

[0003] The process of adjusting such control parameters becomes more difficult as the operating conditions become diverse and complex and the number of parameters increases, and a great deal of labor and time are required. Therefore, there is an increasing demand for automating these adjustment processes.

[0004] For this reason, techniques for modeling the production equipment to be controlled and extracting candidates for parameters to be adjusted using simulation have been disclosed.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] However, when the number of control parameters reaches several tens to several hundreds, the number of combinations becomes enormous, and it takes a very long time to sequentially operate parameter optimization by simulation and optimization with an actual machine.

[0007] In addition, if the operating range in the actual machine is limited to a narrow range from the candidates of the control parameters extracted by simulation, it becomes less robust to disturbances due to the actual machine installation environment, and it may become difficult to converge to the optimal value. For example, it may become difficult to search for appropriate control parameters due to the modeling error of the equipment model and the evaluation error of the actual machine.

[0008] The present disclosure contributes to providing a technique for efficiently and automatically searching for control parameters for equipment.

Means for Solving the Problems

[0009] One aspect of the present disclosure relates to a parameter automatic adjustment device having: a plurality of equipment models obtained by modeling equipment; a control parameter setting unit that sets a plurality of first control parameters to be used for a first trial for the plurality of equipment models and sets a second control parameter to be used for the first trial for the equipment; and a comparison unit that compares the model operation results in the first trial of the plurality of equipment models with the first control parameters and the actual machine operation results in the first trial of the equipment with the second control parameter, wherein the control parameter setting unit selects a control parameter to be used in a second trial based on a first comparison result between the model operation result in the first trial and the actual machine operation result in the first trial. Another aspect of the present disclosure relates to a parameter automatic adjustment method executed by a computer, the method including: setting a plurality of first control parameters to be used for a first trial for a plurality of equipment models obtained by modeling equipment and setting a second control parameter to be used for the first trial for the equipment; comparing the model operation results in the first trial of the plurality of equipment models with the first control parameters and the actual machine operation results in the first trial of the equipment with the second control parameter; and selecting a control parameter to be used in a second trial based on a first comparison result between the model operation result in the first trial and the actual machine operation result in the first trial.

[0010] Note that these general or specific aspects may be implemented in a system, method, integrated circuit, computer program, or recording medium, or may be implemented in any combination of a system, device, method, integrated circuit, computer program, and recording medium.

Advantages of the Invention

[0011] According to the above aspects of the present disclosure, it is possible to provide a technique for efficiently and automatically searching for control parameters for equipment.

[0012] Further advantages and effects in one aspect of the present disclosure will be apparent from the specification and drawings. Such advantages and / or effects are provided by some embodiments and the features described in the specification and drawings, respectively, but not all of them are necessarily provided in order to obtain one or more of the same features.

Brief Description of the Drawings

[0013]

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[0014] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. Note that the embodiments described below are examples, and the present disclosure is not limited to the following embodiments.

[0015] Hereinafter, embodiments of the present disclosure will be described in detail with appropriate reference to the drawings. However, more detailed descriptions than necessary may be omitted. For example, detailed descriptions of well-known matters and duplicate descriptions of substantially the same configurations may be omitted. This is to avoid making the following description unnecessarily redundant and to facilitate understanding by those skilled in the art.

[0016] Note that the accompanying drawings and the following description are provided to enable those skilled in the art to fully understand the present disclosure, and are not intended to limit the subject matter described in the claims.

[0017] First, with reference to FIG. 1, a parameter automatic adjustment system according to an embodiment of the present disclosure will be described. FIG. 1 shows an example of a parameter automatic adjustment system according to an embodiment of the present disclosure.

[0018] As shown in FIG. 1, the parameter automatic adjustment system 100 includes a user interface (UI) unit 101, a parameter automatic adjustment device 102, equipment 103, and a sensor 104. The parameter automatic adjustment system 100 adjusts control parameters so that a predetermined operation of the equipment 103 such as a component mounter satisfies a predetermined performance (for example, position accuracy, settling time, vibration, noise, noise, power consumption, etc.).

[0019] The UI unit 101 is implemented by UI devices such as a display, a keyboard, a mouse, etc., receives adjustment items (e.g., operating conditions, desired performance, priority parameters, etc.) from the user, and transfers the received adjustment items to the parameter automatic adjustment device 102.

[0020] As will be described in more detail below, the parameter automatic adjustment device 102 determines the search range of the control parameters for the facility 103 based on the adjustment items received from the user, and outputs candidate control parameters.

[0021] The facility 103 is a mounting machine such as a production facility, and executes a predetermined operation based on the control parameters set by the parameter automatic adjustment device 102.

[0022] The sensor 104 detects the operation result (e.g., performance value related to the operation, etc.) of the facility 103 that operates according to the set control parameters, and transfers the operation result to the parameter automatic adjustment device 102.

[0023] Then, the parameter automatic adjustment device 102 evaluates the set control parameters based on the performance value obtained from the sensor, and determines the next control parameter to be set for the facility 103 based on the evaluation result. In this way, the parameter automatic adjustment device 102 repeats the above-described control parameter adjustment process to optimize the control parameters (these series of operations are called trials). Also, the parameter automatic adjustment device 102 displays the adjustment status of this control parameter to the user via the UI unit 101.

[0024] In this way, the parameter automatic adjustment system 100 presents the user with the control parameters that have obtained a predetermined performance as the adjustment result, and sets them for the facility 103.

[0025] Note that each of the illustrated blocks may be implemented in one device or in different devices. For example, the facility 103 may be implemented as one device including the UI unit 101, the parameter automatic adjustment device 102, and the sensor 104. Alternatively, the parameter automatic adjustment device 102 may be implemented on the cloud, the UI unit 101 may be implemented on the user's local PC (Personal Computer), smartphone, tablet, etc., and each block may be configured to be connected by a communication network (not shown). Also, a plurality of facilities 103 and / or sensors 104 may be installed.

[0026] Furthermore, the UI unit 101 and / or the parameter automatic adjustment device 102 not only set the adjustment items input from the user, but also operate and control the GUI (Graphical User Interface) of the existing adjustment software for manually adjusting the parameters of the conventional facility 103 by using RPA (Robotic Process Automation) that automatically controls using image recognition or the like, and may perform setting of control parameters and acquisition of operation results. Thereby, parameter automatic adjustment can be performed even on the conventional facility 103 that does not have a dedicated communication interface.

[0027] Next, with reference to FIGS. 2 and 3, the parameter automatic adjustment device 102 according to an embodiment of the present disclosure will be described. FIG. 2 shows an example of the functional configuration of the parameter automatic adjustment device 102 according to an embodiment of the present disclosure.

[0028] As shown in FIG. 2, the parameter automatic adjustment device 102 includes a parallel search unit 201, an actual machine parameter search unit 202, a control parameter setting unit 203, a facility model 204, a comparison unit 205, and a model update unit 206.

[0029] The parallel search unit 201 uses a plurality of equipment models 204 of the equipment 103 to execute an operation simulation of the equipment 103 and search for control parameters. Specifically, the parallel search unit 201 searches for combinations of control parameters that can obtain desired performance based on the constraints of the adjustment items set via the UI unit 101, and outputs candidate control parameters to the control parameter setting unit 203. For example, the selection of control parameter candidates may be performed based on the simulation results output from the equipment model 204.

[0030] The actual machine parameter search unit 202 causes the equipment 103 to execute a physical operation and searches for control parameters based on the actual machine operation results. Specifically, the actual machine parameter search unit 202 searches for combinations of control parameters that can obtain desired performance based on the constraints of the adjustment items set via the UI unit 101, and outputs candidate control parameters to the control parameter setting unit 203. For example, the selection of control parameter candidates may be performed based on the actual machine operation results detected by the sensor 104.

[0031] The control parameter setting unit 203 selects trial control parameters from the plurality of candidate parameters obtained from the parallel search unit 201 and the actual machine parameter search unit 202, and sets the selected control parameters for the equipment model 204 and the equipment 103. For example, the selection of control parameters may be performed based on the output result of the comparison unit 205.

[0032] A plurality of equipment models 204 are configured by modeling the operation of equipment 103 and are capable of executing simulations. The same or different control parameters may be set for each equipment model 204. Also, the plurality of equipment models 204 may be the same or may be different. Various methods can be used to model the operation of equipment 103. For example, the equipment model 204 may be based on a mathematical model using a transfer function and / or a differential equation, a structural analysis model using a CAD model, a multi-physics, a multi-body dynamics model, etc. It is possible to simulate performance indicators such as operation time, movement accuracy, and vibration using the equipment model 204. Alternatively, the equipment model 204 may be based on a machine learning model that predicts and outputs the actual machine operation results of equipment 103 for the input parameters. Alternatively, the equipment model 204 may be a hybrid model combining these. Various known machine learning methods may be applied. For example, the equipment model 204 may be a hybrid model combining these. Deep learning using a neural network that applies various known machine learning methods to generate a time series pattern may be used. Also, a plurality of equipment models 204 may be prepared and the simulations of these equipment models 204 may be executed in parallel. Thereby, a plurality of control parameters and / or constraint conditions can be evaluated simultaneously, and the search time for the control parameters can be reduced.

[0033] The comparison unit 205 compares the model operation result of the equipment model 204 with the actual machine operation result output from the sensor 104. Specifically, the comparison unit 205 compares the operation result of the equipment model 204 for the control parameters set by the control parameter setting unit 203 with the operation result of the equipment 103, and executes the selection of the control parameters in the next trial and the update determination of the equipment model 204. The output regarding the selection of the control parameters is notified to the control parameter setting unit 203, and the output regarding the update of the equipment model is notified to the model update unit 206.

[0034] The model update unit 206 updates the facility model 204 based on the output from the comparison unit 205. Specifically, the model update unit 206 adjusts the internal parameters of the facility model 204 so that the operation with the same control parameters substantially matches that of the facility 103. In this way, the model update unit 206 can reflect the operation in the actual installation environment of the facility 103, individual differences, etc. in the operation of the facility model 204, and improve the accuracy and efficiency of control parameter search.

[0035] For example, the status of these internal blocks may be output to the UI unit 101 as adjustment status and notified to the user.

[0036] Note that various known algorithms can be used for parameter search. For example, heuristic algorithms such as Bayesian optimization, genetic algorithms, particle swarm optimization, mathematical programming methods, and various solutions in combinatorial optimization may be used.

[0037] Also, information regarding the search space may be shared between the parallel search unit 201 and the actual machine parameter search unit 202. For example, the current search range information, past search history, etc. may be exchanged.

[0038] Here, the parameter automatic adjustment device 102 is realized by any computing device such as a server or a personal computer, and may have, for example, a hardware configuration as shown in FIG. 3. For example, the parameter automatic adjustment device 102 includes a storage device 111, a processor 112, a user interface (UI) device 113, and a communication device 114 that are interconnected via a bus B.

[0039] The programs or instructions for implementing various functions and processes described later in the parameter automatic adjustment device 102 may be downloaded from any external device via a network or the like, or may be provided from a removable storage medium such as a CD-ROM (Compact Disk-Read Only Memory) or a flash memory. The storage device 111 is realized by a random access memory, a flash memory, a hard disk drive, etc., and stores files, data, etc. used for the execution of the installed programs or instructions together with the installed programs or instructions. The storage device 111 may include a non-transitory storage medium.

[0040] The processor 112 may be realized by one or more CPUs (Central Processing Units), GPUs (Graphics Processing Units), processing circuitry, etc. that may be composed of one or more processor cores, and according to the programs, instructions, data such as parameters used to execute the program or instruction stored in the storage device 111, etc., executes various functions and processes of the parameter automatic adjustment device 102 described later. The user interface (UI) device 113 may be composed of input devices such as a keyboard, a mouse, a camera, a microphone, output devices such as a display, a speaker, a headset, a printer, input / output devices such as a touch panel, etc., and realizes an interface between the user and the parameter automatic adjustment device 102. For example, the user operates the parameter automatic adjustment device 102 by operating a GUI (Graphical User Interface) displayed on the display or the touch panel with a keyboard, a mouse, etc. The communication device 114 is realized by various communication circuits that execute communication processing with external devices, communication networks such as the Internet, a LAN (Local Area Network), etc.

[0041] However, the above-described hardware configuration is merely an example, and the parameter automatic adjustment device 102 according to the present disclosure may be implemented by any other suitable hardware configuration.

[0042] Next, with reference to FIGS. 4 and 5, adjustment items according to an embodiment of the present disclosure will be described. FIG. 4 shows an example of the data configuration of the adjustment items of the operating condition parameter 301 according to an embodiment of the present disclosure, and FIG. 5 shows an example of the data configuration of the adjustment items of the control condition parameter 302 according to an embodiment of the present disclosure. Note that the illustrated adjustment items are merely examples, and appropriate adjustment items may be set according to the facility 103 to be set.

[0043] As shown in FIGS. 4 and 5, the adjustment items are composed of M operating conditions, and parameters are set for each operating condition. The operating conditions here refer to, for example, operation patterns decomposed into partial operations such as the operation of the arm and the component mounting operation.

[0044] The operating condition parameter 301 defines the desired operation of the facility 103 and, in the illustrated embodiment, is composed of C condition parameters and T target performance parameters. The condition parameters may be, for example, the moving direction, the moving distance, the acceleration time, the limit value of the acceleration, etc. The target performance parameters may be, for example, the settling time of the positioning, the position error, the amount of overshoot such as vibration, etc.

[0045] The control condition parameter 302 defines the setting range of the control parameters of the facility 103 and, in the illustrated embodiment, is composed of P control parameters and T performance weight parameters. The control parameters may be, for example, numerical data such as the resonance frequency, the time constant, and the control gain of the control filter, the setting range, the setting unit (step), and the discrete value set that can be set in the facility 103 such as the filter configuration mode setting, etc. The performance weight parameter may be, for example, a parameter for setting how much weight is given to each item of the target performance for evaluation.

[0046] Control parameters selected from these input data are set for the equipment model 204 and the equipment 103, and a predetermined operation is executed according to the set control parameters. Then, the performance value of the operation result is measured.

[0047] The evaluation parameter 303 is an evaluation value when performing parameter search, and is a value obtained by weighting each output result when control parameters are set for M operating conditions with performance weight parameters. For example, when the target performance is satisfied under all operating conditions, the weights for all parameters are set equally. On the other hand, when prioritizing operating conditions or prioritizing desired performance for each operating condition, the evaluation value may be calculated by adjusting the weights. Further, the evaluation value may be a value obtained by converting the weighted output result with an evaluation value function. The evaluation value function may be, for example, simply the sum of the weighted output results, or the sum of the values converted to the degree (ratio) of reaching the output result with respect to the target performance. At this time, depending on the setting of the evaluation function, the search algorithm may be set to search for control parameters that minimize or maximize the evaluation value.

[0048] Next, with reference to FIG. 6, the operation of the parameter automatic adjustment system 100 according to an embodiment of the present disclosure will be described. FIG. 6 shows an example of an operation sequence of the parameter automatic adjustment system 100 according to an embodiment of the present disclosure.

[0049] As shown in FIG. 6, in step S401, the UI unit 101 transmits the adjustment items set by the user to the parallel search unit 201 and the actual machine parameter search unit 202.

[0050] In step S402, the parallel search unit 201 selects a plurality of candidate parameters A for the equipment model 204 from the search space set based on the adjustment items, and transmits the selected plurality of candidate parameters A to the control parameter setting unit 203. For example, as the candidate parameter A, a combination of different candidate parameters may be given simultaneously (in parallel) for each of the plurality of equipment models 204.

[0051] In step S403, the actual machine parameter search unit 202 selects a plurality of candidate parameters B for the facility 103 from the search space set based on the adjustment items, and transmits the selected plurality of candidate parameters B to the control parameter setting unit 203. For example, as the candidate parameter B, combinations of different candidate parameters for one facility 103 may be sequentially (in series) given.

[0052] In step S404, the control parameter setting unit 203 selects trial parameters to be set for each facility model 204 from the candidate parameters A and B, and transmits the selected trial parameters to each facility model 204. For example, as the trial parameters, combinations of different trial parameters for each of the plurality of facility models 204 may be given simultaneously (in parallel).

[0053] In step S405, the control parameter setting unit 203 selects trial parameters to be set for the facility 103 from the candidate parameters A and B, and transmits the selected trial parameters to the facility 103. For example, as the trial parameters, combinations of different trial parameters for one facility 103 may be sequentially (in series) given.

[0054] In step S406, the sensor 104 acquires the actual machine operation result of the facility 103 that has operated according to the set trial parameters. The actual machine operation result indicates the operation of the facility 103 (for example, the movement of the arm, etc.), and may indicate, for example, the physical quantity of the facility 103 detected and / or measured by the sensor 104.

[0055] In step S407, each facility model 204 executes a simulation according to the set trial parameters, and transmits each model operation result to the parallel search unit 201 and the comparison unit 205.

[0056] In step S408, the sensor 104 transmits the acquired actual machine operation result to the actual machine parameter search unit 202 and the comparison unit 205.

[0057] In step S409, the comparison unit 205 compares the model operation result with the actual machine operation result, and based on the comparison result, transmits parameter switching determination information to the control parameter setting unit 203. For example, when the model evaluation value and the actual machine evaluation value significantly deviate, the parameter switching determination information may instruct the control parameter setting unit to select a control parameter so that the deviation between the model evaluation value and the actual machine evaluation value becomes smaller.

[0058] In step S410, the comparison unit 205 compares the model operation result with the actual machine operation result, and based on the comparison result, transmits model update determination information to the model update unit 206. For example, when the model evaluation value and the actual machine evaluation value significantly deviate, the model update determination information may instruct the model update unit 206 to update the internal parameters of the equipment model 204 so that the deviation between the model evaluation value and the actual machine evaluation value becomes smaller.

[0059] In step S411, the model update unit 206 transmits model update information to the equipment model 204 based on the model update determination information.

[0060] In step S412, the control parameter setting unit 203 transmits control parameter information to the UI unit 101 based on the candidate parameters A, B and the parameter switching determination information. For example, the control parameter information may indicate the current adjustment progress.

[0061] In step S413, the comparison unit 205 transmits comparison information to the UI unit 101 based on the comparison between the model operation result and the actual machine operation result. For example, the comparison information may indicate the current adjustment progress.

[0062] Steps S402 to S413 described above are repeated until a control parameter that satisfies the target performance set by the user is obtained.

[0063] When a control parameter that satisfies the target performance is acquired, in step S414, the control parameter setting unit 203 transmits the adjustment result to the UI unit 101 and ends the parameter automatic adjustment process.

[0064] In addition, when the simulation by the equipment model 204 can be executed sufficiently faster than the actual operation, parallel searches (S402, S403, S404, S407) by the equipment model 204 may be executed multiple times during the actual operation (S406 to S408). Also, multiple trial parameters may be input to the equipment 103 in step S405, and the equipment 103 may sequentially execute them to output multiple actual operation results.

[0065] Next, with reference to FIG. 7, the operation of the parameter automatic adjustment device 102 according to an embodiment of the present disclosure will be described. FIG. 7 is a flowchart showing the operation of the parameter automatic adjustment device 102 according to an embodiment of the present disclosure.

[0066] As shown in FIG. 7, in step S501, the parameter automatic adjustment device 102 receives adjustment items such as operation conditions, target performance, control parameter range, and performance evaluation weights from the UI unit 101.

[0067] In step S502, the parameter automatic adjustment device 102 selects candidate parameters from the parameter search space according to the set adjustment items in the parallel search unit 201 and the actual machine parameter search unit 202 respectively.

[0068] In step S503, the parameter automatic adjustment device 102 selects a trial parameter from the plurality of candidate parameters.

[0069] In step S504, the parameter automatic adjustment device 102 sets the selected trial parameter to the equipment model 204 and the equipment 103. A simulation of a predetermined operation and an actual operation are executed according to the set trial parameter.

[0070] In step S505, the parameter automatic adjustment device 102 obtains the evaluation values of the operation result by the simulation of the equipment model 204 and the actual operation result by the equipment 103.

[0071] In step S506, the parameter automatic adjustment device 102 compares the model evaluation value by the equipment model 204 with the actual machine evaluation value by the equipment 103. As shown in FIG. 8, when a plurality of model evaluation values are higher than the actual machine evaluation value by a predetermined difference or more (S506: Y), it proceeds to S509; otherwise (S506: N), it proceeds to S507.

[0072] In step S507, the parameter automatic adjustment device 102 compares the model evaluation value by the equipment model 204 with the actual machine evaluation value by the equipment 103. As shown in FIG. 9, when a plurality of model evaluation values are lower than the actual machine evaluation value by a predetermined difference or more (S507: Y), it proceeds to S510; otherwise (S507: N), it proceeds to S508.

[0073] In step S508, when the model evaluation value by the equipment model 204 and the actual machine evaluation value by the equipment 103 are in a state of being substantially the same as shown in FIG. 10, the parameter automatic adjustment device 102 selects the next trial parameter based on the control parameter that obtained the best value among the model evaluation value of the equipment model 204 and the actual machine evaluation value of the equipment 103, and proceeds to S511.

[0074] In step S509, the parameter automatic adjustment device 102 updates the internal parameters of the equipment model 204 so as to lower the evaluation value of the equipment model 204 so that the model evaluation value of the equipment model 204 approaches the actual machine evaluation value of the equipment 103. Also, the parameter automatic adjustment device 102 selects the next trial parameter based on the control parameter that obtained the result closest to the actual machine evaluation value of the equipment 103 among the model evaluation values, and proceeds to S511.

[0075] In step S510, the parameter automatic adjustment device 102 updates the internal parameters of the equipment model 204 so as to increase the evaluation value of the equipment model 204 such that the model evaluation value of the equipment model 204 approaches the actual machine evaluation value of the equipment 103. Further, the parameter automatic adjustment device 102 selects the next trial parameter based on the control parameter for which the actual machine evaluation value of the equipment 103 is obtained, and proceeds to S511.

[0076] In step S511, the parameter automatic adjustment device 102 determines whether the actual machine evaluation value of the equipment 103 has reached the target performance. If it has reached (S511: Y), it proceeds to S512; if it has not reached (S511: N), it proceeds to S502. Note that in FIG. 7, the process from S502 to S511 is a trial.

[0077] In step S512, the parameter automatic adjustment device 102 outputs and displays the adjusted final result, and ends the adjustment operation.

[0078] Next, with reference to FIGS. 8 to 10, a user interface (UI) display according to an embodiment of the present disclosure will be described. As described above, the UI unit 101 may include a display device capable of displaying the adjustment process of the parameter adjustment process in the parameter automatic adjustment system 10 to the user.

[0079] FIG. 8 shows an example of the parameter adjustment result display according to an embodiment of the present disclosure. As shown in FIG. 8, the UI unit 101 includes an adjustment progress graph 601, an operating condition parameter setting area 602, a control condition parameter setting area 603, an evaluation progress setting area 604, and a pointer 605 such as a cursor and a touch interface.

[0080] The adjustment progress graph 601 illustrates the progress of the evaluation values during parameter adjustment. The adjustment progress graph 601 includes an indicator 6011 indicating the high and low directions of performance, a selected vertical axis label 6012 (e.g., an evaluation value by an evaluation function, a specific performance value, etc.), a selected horizontal axis label 6013 (e.g., evaluation elapsed time t, number of trials, etc.), model evaluation values 6014 for a selected plurality of trial parameters, actual machine evaluation values 6015 for a selected trial parameter, and a model update direction 6016.

[0081] In the operating condition parameter setting area 602, when clicked or tapped by the user, the display and / or editing of the operating condition parameters 301 can be performed. As a graphical user interface (GUI), table editing, value selection using a slider, etc. can be used.

[0082] In the control condition parameter setting area 603, when clicked or tapped by the user, the display and / or editing of the control condition parameters 302 can be performed. As a GUI, table editing, value selection using a drop-down menu, a slider, etc. can be used. Also, by expressing the performance weight parameters with a heat map or the like, the visibility for the user can be enhanced.

[0083] In the evaluation progress setting area 604, when clicked or tapped by the user, commands such as start, interruption, or / and end of automatic adjustment, selection of the content to be displayed in the adjustment progress graph 601, etc. can be performed. As a GUI, value selection using a drop-down menu, radio buttons, check boxes, etc. can be used.

[0084] As shown, when the model evaluation value 6014 is higher than the actual machine evaluation value 6015 by a predetermined difference or more, it is possible that: 1. The disturbance component of the equipment 103 is not appropriately reflected in the equipment model 204, and in the simulation, the model evaluation value 6014 tends to show higher performance than the actual machine evaluation value 6015; 2. The trial parameters that may show higher performance than the trial parameters set for the equipment 103 are set in the equipment model 204. Therefore, by adjusting the disturbance component of the equipment model 204, it can be indicated to update the equipment model 103 in the direction (6016) where the output of the equipment model 204 approaches the output of the equipment 103. Also, for the equipment 103, the trial parameters that may show higher performance can be selected from the trial parameters of the equipment model 204 and used for the search of the next trial parameters.

[0085] Note that the indicator 6011 indicates which direction has higher performance according to the selected vertical axis label 6012. For example, when the position error is selected on the vertical axis, since it can be interpreted that the smaller the position error value, the higher the performance, the indicator 6011 is a downward arrow, and the lower label is "High performance". Alternatively, in the case of the evaluation value obtained by weighting a plurality of performance values and applying them to the evaluation function, for the evaluation function that returns a larger evaluation value as the performance is higher, the indicator 6011 is an upward arrow, and the upper label is "High performance". Thus, the user can easily recognize the quality of the performance without misunderstanding the meaning of the graph. Furthermore, by clicking on the indicator 6011, the up and down can be swapped, and accordingly, the graph can also be swapped up and down for display. Thus, the evaluation value and the performance value can be displayed according to the user's preference.

[0086] Also, when the pointer 605 is aligned with, clicked, or tapped on the line segment of the model evaluation value 6014, the actual machine evaluation value 6015, and / or the model update direction 6016, the related control parameter values, etc. may be displayed by a pop-up or the like.

[0087] FIG. 9 shows an example of parameter adjustment result display according to an embodiment of the present disclosure. In the example shown in FIG. 9, an example of a state where the model evaluation value 6014 is lower than the actual machine evaluation value 6015 is shown.

[0088] When the model evaluation value 6014 is lower than the actual machine evaluation value 6015 by a predetermined difference or more, 1. the sensitivity of the equipment 103 etc. is not reflected in the equipment model 204, and in the simulation, the model evaluation value 6014 tends to show lower performance than the actual machine evaluation value 6015, 2. it is considered possible that the trial parameters set for the equipment 103 are showing higher performance than the trial parameters of the equipment model 204. Therefore, by performing sensitivity adjustment etc. of the equipment model 204, it is possible to display that the equipment model 204 is updated in the direction (6016) where the output of the equipment model 204 approaches the output of the equipment 103. Also, since high-performance trial parameters are set for the equipment 103, these can be continuously used for the search for the next trial parameters.

[0089] FIG. 10 shows an example of parameter adjustment result display according to an embodiment of the present disclosure. In the example shown in FIG. 10, an example of a state where the model evaluation value 6014 and the actual machine evaluation value 6015 are substantially the same is shown.

[0090] In this case, 1. the operation results of the equipment model 204 and the equipment 103 are substantially the same for the same control parameters, 2. it is considered that among the plurality of trial parameters set for the equipment model 204, there are parameters that may show higher performance than the parameters set for the equipment 103. Therefore, based on the control parameters that obtained the best value among the model evaluation value 6014 and the actual machine evaluation value 6015, the search for the next trial parameters can be performed. Also, for the trial parameters for which a model evaluation value 6014 lower than the actual machine evaluation value 6015 is obtained, the efficiency of parallel search by the equipment model 204 may be increased by pruning or setting different search spaces.

[0091] According to the above-described embodiments of the present disclosure, when a plurality of evaluation values of the equipment model 204 of the parameter automatic adjustment system 100 are higher than those of the actual machine, the equipment model 204 is updated in a direction in which the output of the equipment model 204 approaches the actual machine output by adjusting disturbance components and the like of the equipment model 204. Also, trial parameters that may achieve high performance for the equipment 103 can be selected from the trial parameters of the equipment model 204 and used for the search for the next trial parameters. On the other hand, when a plurality of evaluation values of the equipment model 204 are lower than those of the actual machine, the equipment model 204 is updated in a direction in which the output of the equipment model 204 approaches the actual machine output by adjusting the sensitivity and the like of the equipment model 204. Also, the trial parameters set for the equipment 103 can be continuously used for the search for the next trial parameters. When the model evaluation value and the actual machine evaluation value are substantially the same, the search for the next trial parameters can be performed based on the control parameters that obtained the best value among the model evaluation value and the actual machine evaluation value. Also, for the trial parameters for which a model evaluation value lower than the actual machine evaluation value is obtained, the efficiency of parallel search by the equipment model 204 can be improved by pruning or setting different search spaces.

[0092] In this way, the search for a plurality of operating conditions can be efficiently executed by parallel search using a plurality of equipment models 204. Correction of the modeling error can be performed while continuing the parameter search that involves operating the time-consuming actual machine. If the modeling error is reduced, the adjustment time can be reduced by narrowing down the search range based on the parameter search results obtained by the actual machine, and the adjustment process can be presented to the user.

[0093] In the above-described embodiments, the notation “... section” used for each component may be replaced with other notations such as “... circuitry”, “... assembly”, “... device”, “... unit”, or “... module”.

[0094] The embodiments have been described above with reference to the drawings, but the present disclosure is not limited to such examples. It is obvious that those skilled in the art can conceive of various modification examples or correction examples within the scope described in the claims. Such modification examples or correction examples are also understood to belong to the technical scope of the present disclosure. Also, within the scope not departing from the gist of the present disclosure, the components in the embodiments may be arbitrarily combined.

[0095] The present disclosure can be realized by software, hardware, or software in cooperation with hardware. Each functional block used in the description of the above embodiments may be realized partially or entirely as an LSI which is an integrated circuit, and each process described in the above embodiments may be controlled partially or entirely by one LSI or a combination of LSIs. The LSI may be composed of individual chips, or may be composed of one chip so as to include part or all of the functional blocks. The LSI may have data input and output. Depending on the degree of integration, the LSI may also be referred to as an IC, a system LSI, a super LSI, or an ultra LSI.

[0096] The method of integrating into an integrated circuit is not limited to LSI, and may be realized as an application specific circuit, a general-purpose processor, or a dedicated processor. Also, after manufacturing the LSI, an FPGA (Field Programmable Gate Array) that can be programmed, or a reconfigurable processor that can reconfigure the connection and / or setting of circuit cells inside the LSI may be used. The present disclosure may be realized as digital processing or analog processing.

[0097] Furthermore, when an integrated circuit technology replacing the LSI appears due to the progress of semiconductor technology or another derived technology, of course, the technology may be used to integrate the functional blocks. The application of biotechnology or the like is possible as an example.

[0098] In addition, the following supplementary notes are disclosed regarding the above description. (Supplementary Note 1) A plurality of equipment models that model equipment, a control parameter setting unit that sets a plurality of first control parameters to be used in a first trial for the plurality of equipment models and sets a second control parameter to be used in the first trial for the equipment, a comparison unit that compares the model operation results in the first trial of the plurality of equipment models with the first control parameters and the actual machine operation results in the first trial of the equipment with the second control parameter, and having, The control parameter setting unit selects a control parameter to be used in a second trial based on a first comparison result between the model operation result in the first trial and the actual machine operation result in the first trial, a parameter automatic adjustment device. (Appendix 2) The parameter automatic adjustment device according to Appendix 1, further including a model update unit that updates the plurality of equipment models based on the first comparison result. (Appendix 3) The comparison unit compares a plurality of model evaluation values indicating the model operation results in the first trial with an actual machine evaluation value indicating the actual machine operation results in the first trial, when the plurality of model evaluation values are higher than the actual machine evaluation value by a predetermined first difference or more, the model update unit updates the plurality of equipment models so that the plurality of model evaluation values approach the actual machine evaluation value, The control parameter setting unit selects a control parameter to be used in the second trial based on the first control parameter corresponding to the model evaluation value closest to the actual machine evaluation value, the parameter automatic adjustment device according to Appendix 2. (Appendix 4) when the plurality of model evaluation values are lower than the actual machine evaluation value by a predetermined second difference or more, the model update unit updates the plurality of equipment models so that the plurality of model evaluation values approach the actual machine evaluation value, The control parameter setting unit selects a control parameter to be used in the second trial based on the second control parameter, the parameter automatic adjustment device according to Appendix 3. (Appendix 5) When the plurality of model evaluation values are not higher than the actual machine evaluation value by a predetermined first difference and are not lower than the actual machine evaluation value by a predetermined second difference, the control parameter setting unit selects a control parameter to be used in the second trial based on the best value between the plurality of model evaluation values and the actual machine evaluation value. The parameter automatic adjustment device according to Appendix 4. (Appendix 6) The parameter automatic adjustment device according to any one of Appendices 1 to 5, A display device that displays the model operation result in the first trial and the actual machine operation result in the first trial, A parameter automatic adjustment system having the above. (Appendix 7) Setting a plurality of first control parameters to be used in the first trial for a plurality of equipment models that model the equipment, and setting a second control parameter to be used in the first trial for the equipment, Comparing the model operation result in the first trial of the plurality of equipment models with the plurality of first control parameters and the actual machine operation result in the first trial of the equipment with the second control parameter, Selecting a control parameter to be used in the second trial based on the first comparison result between the model operation result in the first trial and the actual machine operation result in the first trial, A parameter automatic adjustment method executed by a computer having the above.

[0099] The disclosure contents of the specification, drawings, and abstract included in the Japanese application of Japanese Patent Application No. 2021-184816 filed on November 12, 2021 are all incorporated herein by reference.

Industrial Applicability

[0100] One aspect of the present disclosure is useful for a parameter automatic adjustment system.

Explanation of Signs

[0101] 100 Parameter automatic adjustment system 101 User Interface (UI) Unit 102 Parameter Automatic Adjustment Unit 103 Equipment 104 Sensor 201 Parallel Search Unit 202 Actual Machine Parameter Search Unit 203 Control Parameter Setting Unit 204 Equipment Model 205 Comparison Unit 206 Model Update Unit

Claims

1. A plurality of equipment models that model the operation of the entire equipment, a control parameter setting unit that sets a plurality of first control parameters to be used in a first trial for the plurality of equipment models and sets a second control parameter to be used in the first trial for the equipment, a comparison unit that compares the model operation results of the plurality of equipment models in the first trial with the first control parameters and the actual machine operation results of the equipment in the first trial with the second control parameter, and having, the control parameter setting unit selects control parameters to be used in a second trial based on a first comparison result between the model operation result in the first trial and the actual machine operation result in the first trial, a parameter automatic adjustment device.

2. The parameter automatic adjustment device according to claim 1, further including a model update unit that updates the plurality of equipment models based on the first comparison result.

3. The comparison unit compares a plurality of model evaluation values indicating the model operation results in the first trial with an actual machine evaluation value indicating the actual machine operation results in the first trial, when the plurality of model evaluation values are higher than the actual machine evaluation value by a predetermined first difference or more, the model update unit updates the plurality of equipment models so that the plurality of model evaluation values approach the actual machine evaluation value, the control parameter setting unit selects control parameters to be used in the second trial based on the first control parameter corresponding to the model evaluation value closest to the actual machine evaluation value, the parameter automatic adjustment device according to claim 2.

4. when the plurality of model evaluation values are lower than the actual machine evaluation value by a predetermined second difference or more, the model update unit updates the plurality of equipment models so that the plurality of model evaluation values approach the actual machine evaluation value, the control parameter setting unit selects control parameters to be used in the second trial based on the second control parameter, the parameter automatic adjustment device according to claim 3.

5. when the plurality of model evaluation values are not higher than the actual machine evaluation value by a predetermined first difference or more and the plurality of model evaluation values are not lower than the actual machine evaluation value by a predetermined second difference or more, the control parameter setting unit selects control parameters to be used in the second trial based on the best value between the plurality of model evaluation values and the actual machine evaluation value, the parameter automatic adjustment device according to claim 4.

6. The parameter automatic adjustment device according to claim 1, a display device that displays the model operation result in the first trial and the actual machine operation result in the first trial; A parameter automatic adjustment system comprising:

7. setting a plurality of first control parameters to be used in a first trial for a plurality of equipment models that model the operation of the entire equipment, and setting a second control parameter to be used in the first trial for the equipment; comparing the model operation result in the first trial of the plurality of equipment models with the plurality of first control parameters and the actual machine operation result in the first trial of the equipment with the second control parameter; selecting a control parameter to be used in a second trial based on a first comparison result between the model operation result in the first trial and the actual machine operation result in the first trial; A parameter automatic adjustment method executed by a computer, comprising:

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