JP6988950B2 - Simulation methods, simulation programs and simulators - Google Patents

Description

The present disclosure relates to simulation methods, simulation programs and simulators that support the adjustment of target values used to control objects.

As one of the controllers that adjusts the control amount so that the observed value from the controlled object matches the target value, there is a temperature controller attached to the heating system.

As a technique for processing a target temperature for temperature control, for example, Patent Document 1 (Japanese Unexamined Patent Publication No. 2005-276169) describes a controller that executes a control process based on a target value and an observed amount from a controlled object. Disclosed is a device provided in the preceding stage for processing a target value for a regulator.
In Patent Document 2 (Japanese Unexamined Patent Publication No. 2007-11982), adjustment information for adjusting the target temperature is calculated by a personal computer as an adjusting device, and is given from the personal computer to the temperature controller by communication. The temperature controller discloses a configuration for adjusting the target temperature based on this adjustment information.

Japanese Unexamined Patent Publication No. 2005-276169 Japanese Unexamined Patent Publication No. 2007-11982

Regarding temperature control, modeling using simulation technology and characteristic evaluation of the modeled device have been put into practical use. By simulating using such a model, it is possible to study the optimum target value without an actual machine, so that it is possible to realize cost reduction and shortening of the design period.

In this regard, the user has a need to make manual adjustments when designing the target value. Patent Document 2 is designed by automatically calculating the adjustment information of the target value even if there is no temperature controller which is an actual machine, but it enables the user to manually adjust the adjustment information of the target value. Does not provide an environment.

The present disclosure has been made in view of such a background, and an object thereof is to provide an environment in which a user can manually adjust a target value used for controlling an object.

An example of the present disclosure is a method in which a computer simulates the temporal characteristics of an object heated by a heating element that changes the calorific value according to the manipulated variable, and the manipulated variable is input and the observed object is output. The first temporal characteristic is calculated as the input of the target model using the step of constructing the target model indicating A step to calculate as the time characteristic of 2, a step to change the target value column based on the followability of the second time characteristic to the target value sequence, and a step to calculate using the changed target value sequence. An object for visualizing the step of re-implementing, the target value sequence before the change, and the second temporal characteristic calculated in the step of re-execution on a common time axis, and the target value column after the change. Includes a step to output a GUI containing an adjustment object that accepts user operations for adjustment.

According to this disclosure, since the target value sequence and the calculated second temporal characteristic are visualized and presented on a common time axis, the target value sequence of the second temporal characteristic is presented to the user. It is possible to visually give the followability to. Furthermore, the user can estimate the adjustment amount for the changed target value sequence by referring to the visually obtained followability, and input the adjustment amount to the simulation via the adjustment object. can. Thereby, according to the present disclosure, it is possible to provide an environment in which the user can manually adjust the target value used for controlling the target.

In the above disclosure, the object for visualization visualizes the target value sequence before the change, the second temporal characteristic calculated in the step of re-execution, and the target value sequence after the change on a common time axis. Contains objects to do.

According to this disclosure, as the temporal characteristics of the target simulation for the user, the target value sequence before the change, the second temporal characteristic calculated in the step of re-execution, and the target value after the change are disclosed. Columns can be visualized and presented as a list on a common time axis.

In the above disclosure, the object for visualization is the graph of the target value column at the coordinates where the elapsed time is assigned to the common time axis and the target value, the manipulated variable and the observed amount are assigned to the axis orthogonal to the time axis. , A graph showing a first temporal characteristic and a graph showing a second temporal characteristic are included.

According to this disclosure, as an aspect of presenting the temporal characteristics of the target simulation, the elapsed time is assigned to a common time axis, and the target value, the manipulated variable, and the observed amount are assigned to the axis orthogonal to the time axis. It can be presented as a graph of a target value sequence, a graph showing a first temporal characteristic, and a graph showing a second temporal characteristic at the specified coordinates.

In the above disclosure, the simulation method further comprises a step of evaluating the followability using a predetermined evaluation function, and the GUI further provides a visualization of the evaluation value calculated by the evaluation function. Contains objects.

According to this disclosure, the followability described above can be provided to the user as visual information of the evaluation value quantitatively expressed.

In the above disclosure, the GUI further includes an object that accepts a user operation to specify a period for evaluating followability in the simulation at the elapsed time indicated by the time axis.

According to this disclosure, the user can specify the period for evaluating the followability in the simulation in the elapsed time indicated by the time axis.

In the above disclosure, the simulation method further calculates the step using the adjusted target value sequence when a user operation for adjusting the changed target value sequence is received via the adjustment object. Prepare for the step of re-implementing.

According to this disclosure, when the user manipulates the adjustment object to adjust the modified target value sequence, the computer uses the adjusted target value sequence as the input of the target model as the first temporal characteristic. Is calculated, and the output of the target model for the input of the first temporal characteristic is calculated as the second temporal characteristic.

In the above disclosure, the adjustment object includes a first object that accepts a user operation for increasing or decreasing the changed target value sequence, or a second object that accepts a user operation for inputting a numerical value.

According to this disclosure, as an adjustment object, it is possible to provide a user with an object that accepts an operation of increasing / decreasing a value or an object that accepts an operation of directly inputting a numerical value.

In the above disclosure, the first object includes a plurality of buttons arranged in parallel with the direction in which the time axis extends in association with a common time axis, and each button has the nearest scale of the button on the time axis. Accepts user operations that increase or decrease the target value in the target value column corresponding to the indicated time.

According to this disclosure, it is possible to provide an environment that enables the user to adjust the target value corresponding to the scale of the time axis.

In the above disclosure, each button accepts a user operation to increase or decrease the target value within the range from the upper limit value to the lower limit value of the target value.

According to this disclosure, when the user operates a button to increase or decrease the target value, even if the increased / decreased value exceeds the upper limit or the lower limit, the target value after the increase / decrease operation is kept in the range of the upper limit value to the lower limit value. be able to.

In the above disclosure, each button accepts a user operation to increase or decrease the target value by a predetermined amount.

According to this disclosure, when the user operates a button to increase or decrease the target value, the value can be increased or decreased by a predetermined amount for each operation.

In the above disclosure, the GUI further includes an object that, when each button is operated, draws a target value corresponding to the time indicated by the nearest scale of the button.

According to this disclosure, it is possible to present the target value to the user corresponding to the nearest scale on the time axis of the button to be operated.

Other examples of the present disclosure provide a simulation program for realizing the simulation method described above when executed by a computer.

Other examples of the present disclosure provide simulators for performing the simulation methods described above.

According to the present invention, it is possible to provide an environment in which a user can manually adjust a target value for controlling an object.

It is a figure which shows the main module composition of the simulator 500 which concerns on embodiment. It is a figure which shows typically an example of the structure of the heating system which concerns on this embodiment. It is a schematic diagram which shows the structure of the temperature controller 7 of FIG. It is a schematic diagram which shows the structure of the control system 1 which concerns on this embodiment. It is a schematic diagram which shows the hardware composition of the processing unit 10 of PLC100 of FIG. It is a schematic diagram which shows an example of the hardware composition of the support apparatus 200 which concerns on embodiment of this invention. (A) and (B) are graphs showing an example of target value shaping by the simulator 500 according to the present embodiment. It is a flowchart which shows the outline of the process which concerns on this embodiment. It is a block diagram which shows the structure of FIG. 2 in a simplified manner while associating with a data flow. It is a figure explaining the process of the work model identification part 31 of the step S12 of FIG. It is a figure explaining the process of the target value optimization part 32 of step S23 of FIG. It is a figure explaining the kind of composition of the heating system to which the target value shaping can be applied in a table format. It is a graph which shows an example of the data of the operation amount MV, the control amount PV1 and "work SV (original)" acquired by the simulator 500 in step S11 of FIG. It is a graph which shows an example of the data acquired in the work model identification of step S12 of FIG. It is a figure which shows an example of the GUI for adjusting the target value which concerns on this embodiment. It is a figure which shows an example of the display of the evaluation value 291 output by the evaluation function which concerns on this embodiment. It is a figure which shows the other example of the GUI for the target value adjustment which concerns on this embodiment. It is a figure which shows the other example of the GUI for the target value adjustment which concerns on this embodiment. It is a figure which shows the other example of the GUI for the target value adjustment which concerns on this embodiment. It is a figure which shows the other example of the GUI for the target value adjustment which concerns on this embodiment.

Embodiments of the present invention will be described in detail with reference to the drawings. The same or corresponding parts in the drawings are designated by the same reference numerals and the description thereof will not be repeated.

<A. Application example>

First, an example of a situation in which the present invention is applied will be described. The simulator 500 according to this embodiment is typically mounted on a general-purpose computer such as a personal computer.

FIG. 1 is a diagram showing a main module configuration of the simulator 500 according to the embodiment. In the present disclosure, the simulator exemplifies a time simulation of an object whose state changes dynamically, that is, the state changes with the passage of time in FA (Factory Automation) provided in a work production line. Here, the target of the simulation is an example of a work that is heated and the temperature changes as a state, but the target is not limited to this.

With reference to FIG. 1, the simulator 500 includes a data acquisition unit 30 for acquiring data for simulation, a work model identification unit 31 for constructing a model representing an object, and a target value for calculating an optimum target value. It includes an optimization unit 32, a drawing data generation unit 33 that generates data for drawing a GUI (Graphical User Interface), and a display driver 34 that draws (displays) the GUI by driving the display 207 based on the drawing data. The display driver 34 is not dedicated to the simulator 500, but may be provided in a computer for general purposes and the driver may be used.

The simulator 500 calculates (simulates) the temporal characteristics of an object (work 60 described later) heated by a heating element (heater 3 described later) that changes the calorific value according to the operation amount MV.

More specifically, the work model identification unit 31 inputs a time-series operation amount (actual MV) that changes with the passage of time collected from the actual machine that heats the work 60, and observes the work amount (work temperature). ) Is output, and a work model showing the work is constructed. The output of the work model represents a time-series observable (model PV1) that changes over time. The work model is represented using a heat transfer function that represents the heat transfer characteristics of the work 60 due to heating. The work model identification unit 31 performs a process of determining the parameters used for the heat transfer function using a time-series observation amount (actual MV1) that changes with the passage of time collected from the actual machine that heats the work 60. The heat transfer function is constructed by determining the parameters.

The target value optimization unit 32 calculates the optimum target value using the configured work model. More specifically, the target value optimization unit 32 uses the time-series target value sequence (work SV (original)) indicating a temporal change from the data acquisition unit 30 to input the work model in the first time. The target characteristic (time-series manipulated variable MV) is calculated, and the output of the work model for the input of the first temporal characteristic is calculated as the second temporal characteristic (time-series model temperature (model PV1)) ( This is called the calculation step). The first temporal characteristic (operation amount MV) is calculated by PID control (Proportional-Integral) that models the control of the temperature controller, which is represented by the function identified by the parameter from the data acquisition unit 30. -Differential Controller) Calculation using the model is applied. By calculation using the PID control model, the manipulated variable MV for changing the output from the work model (model PV described later) according to the target value is derived.

The target value optimization unit 32 changes the target value based on the followability of the second temporal characteristic (model PV1) to the target value sequence (work SV (original)). More specifically, in the target value optimization unit 32, the value of the second temporal characteristic (model PV) follows the change of the target value sequence (work SV (original)) with the passage of time without delay. The changing followability is evaluated using a predetermined evaluation function. The target value optimization unit 32 changes the target value sequence based on the evaluation value of the followability, and re-executes the above calculation step using the changed target value sequence. For example, the target value optimization unit 32 calculates a changed target value sequence (RS work SV) so that the model PV1 follows the work SV (original) based on the evaluation value of the followability, and the changed target. The above calculation step is repeated using the value sequence.

The simulator 500 further provides the user with a GUI as an environment in which the changed target value sequence (RS work SV) can be manually adjusted. Specifically, the drawing data generation unit 33 uses the target value sequence before the change (work SV (original)) and the second temporal characteristic (RS work SV of the target value sequence) calculated by the above re-execution. Includes an object for visualizing the model PV1), which is a time-series value calculated using the data, on a common time axis, and an adjustment object that accepts user operations for adjusting the changed target value sequence. Generate drawing data for GUI. The display driver 34 drives the display 207 based on the drawing data to display the GUI on the display 207.

The user can use the object visualized on the display 207 as a target value sequence (work SV (original)) displayed on a common time axis and a second temporal characteristic (model PV1 calculated using the RS work SV). ) Deviation, that is, followability can be visually recognized. Further, the user can obtain a guideline for the adjustment amount from the deviation so as to reduce the deviation.

When the user operates the adjustment object to adjust the changed target value sequence, the target value optimization unit 32 accepts the adjusted target value sequence and uses the received adjusted target value sequence. And repeat the calculation steps described above. A GUI showing the result of the re-execution is displayed on the display 207. In the GUI showing the result of the re-execution, the user can see that the deviation between the target value sequence (work SV (original)) and the second temporal characteristic (model PV1 calculated using RS work SV) becomes small, for example. In other words, when the user visually recognizes that the followability is improved, the user uses the work 60 in the adjusted target value sequence rather than the adjusted target value sequence (that is, the changed target value sequence). It can be judged that it is suitable as a target value for heating control.

According to the configuration of FIG. 1, a target for the temperature controller 7 to control the heater 3 so as to change the temperature of the work 60 at the time of heating according to the original target value sequence (work SV (original)). It is possible to provide an environment in which the value sequence (RS work SV) can be manually adjusted by the user via the GUI. Hereinafter, a more specific application example of this embodiment will be described.

<B. Simulation model configuration>

FIG. 2 is a diagram schematically showing an example of the configuration of the heating system according to the present embodiment. The heating system of FIG. 2 employs an FB (feedback) control system. The heating system shown in FIG. 2 includes a PID control system. In the present specification, the "PID control system" is a proportional element that performs a proportional operation (Proportional Operation: P operation), an integral element that performs an integral operation (Integral Operation: I operation), and a differential operation (Derivative Operation: D operation). It is a general term for a control system including at least one element among the differential elements that perform the above. That is, in the present specification, the PID control system includes not only a control system including any proportional element, an integral element, and a differential element, but also a part of the control elements, for example, a proportional element and an integral element (PI). It is a concept that also includes control systems).

As an example, FIG. 2 shows that the temperature controller 7 is a semiconductor wafer being subjected to CVD processing in, for example, a CVD device that creates various functional films on a work 60 corresponding to a semiconductor wafer by a CVD (Chemical Vapor Deposition) method. As an example, a temperature controller used for temperature control of the heater 3 for heating the temperature of the heater 3 to the target temperature can be mentioned.

With reference to FIG. 2, the heating system from the power source 5 via the temperature controller 7, the SSR (Solid State Relay) 4, and the SSR 4 to heat the work 60 in the heating furnace 2. It includes a heater 3 to which electric power is supplied and a temperature sensor 62. The heater 3 is typically a resistor that converts the supplied power into heat energy. The temperature sensor 62 measures the temperature due to the heat generated by the heater 3. Further, in FIG. 2, as input data for simulation, a temperature sensor 61 attached to the back surface of the work 60 is provided in order to acquire the temperature of the work 60. The temperature sensor 61 is not provided in the environment of the actual machine. The temperature sensors 61 and 62 are composed of a thermocouple or a resistance thermometer (platinum resistance thermometer).

In the FB control system of FIG. 2, in the temperature controller 7, the temperature of heat generated by the heater 3 being energized is measured by the temperature sensor 62, and the measured temperature (observed amount: Process Value; hereinafter also referred to as “PV2”). The operation amount (Manipulated Value; hereinafter also referred to as “MV”) is output so that the target value (setting value: Setting Value; hereinafter also referred to as “SV”) acquired by the simulation matches. That is, in the actual machine, the temperature controller 7 determines the manipulated variable MV so that the controlled variable PV2 of the heater 3 matches the target value.

In the field of control engineering, "observable amount" is defined as a value containing some error in "control amount", but if this error is ignored, "observable amount" can be regarded as "control amount" of the controlled object. can. Therefore, in the following description, "controlled quantity" may be read as "observed quantity".

The temperature controller 7 outputs the manipulated variable MV calculated by executing the process related to the PID control system to the SSR 4. In the feedback control system, the operation amount takes a value in the range of 0 to 100 [%], and the SSR 4 controls the circuit from the power supply 5 to the heater 3 on / off at a duty ratio according to the operation amount MV. do. For example, if the operation amount is 50 [%], the period of 50 [%] of the predetermined control cycle is turned on (energized state), and the remaining 50 [%] period is turned off (non-energized state). Be made.

In this way, the temperature controller 7 adjusts the operation amount MV, so that the calorific value of the heater 3 depends on the duty ratio, and in principle, the calorific value is only in the range of 0 to 100 [%]. Cannot be adjusted. Therefore, when the operation amount MV calculated in the PID control system exceeds 100% or is less than 0%, the SSR 4 and the heater 3 cannot operate according to the operation amount MV. In the present specification, such a state (MV ≧ 100 [%] and / or MV ≦ 0 [%]) is expressed as “saturated” in the manipulated variable, and in the PID control of the temperature controller 7, the PID control is performed. By performing the process of avoiding the saturation, the situation where the operation amount MV is saturated is avoided.

In the present embodiment, the temperature controller 7 is provided in the production line of the work 60 and communicates with a PLC (Programmable Logic Controller) 100 that controls each device provided in the production line. When the production line is in operation, the temperature controller 7 receives a command indicating the target value SV from the PLC 100, calculates the operation amount MV according to the received command, and outputs the calculated operation amount MV to the SSR 4. As a result, the heater 3 generates heat, and the work 60 placed on the heater 3 is heat-treated by heat transfer from the heater 3. The temperature controller 7 transmits the controlled variable PV2 and the manipulated variable MV, which are the measured temperatures of the heater 3, to the PLC 100 during operation. As a result, the PLC 100 can collect the controlled variable PV2 and the manipulated variable MV according to the target value SV.

In the present embodiment, in the configuration of FIG. 2, in order to acquire data for simulation, a temperature sensor 61 is attached to the work 60, and a controlled amount which is the measured temperature of the work 60 measured by the temperature sensor 61. PV1 is also acquired. As a result, the simulator 500 can derive the target value SV by using the control amount PV1 that more accurately reflects the temperature of the work 60 than the control amount PV2. Therefore, the target value SV is derived by using the control amount PV2 of the heater 3. It is possible to derive a more suitable target temperature for the CVD process of the work 60 as compared with the case of deriving.

<C. Configuration of temperature controller>

FIG. 3 is a schematic diagram showing the configuration of the temperature controller 7 of FIG. With reference to FIG. 3, the temperature controller 7 includes an input circuit 109, an analog-to-digital conversion unit 112 (hereinafter, also referred to as “A / D conversion unit 112”), a display unit 121, and an operation unit 122. , A communication interface 124, a processing unit 101, a digital-to-analog conversion unit 114 (hereinafter, also referred to as “D / A conversion unit 114”), and an output circuit 116.

The input circuit 109 receives the controlled variable PV2 which is the measured temperature from the temperature sensor 62, and outputs a voltage / current signal in a predetermined range. The A / D conversion unit 112 converts the analog signal from the input circuit 109 into a digital signal and outputs it to the processing unit 101.

The operation unit 122 includes buttons, switches, and the like provided on the front surface of the housing of the temperature controller 7 of FIG. 2, receives user operations, and outputs information indicating the accepted user operations to the processing unit 101. The display unit 121 includes a display, an indicator, and the like provided on the front surface of the housing of the temperature controller 7, and notifies the user of information indicating the processing status in the processing unit 101. In another aspect, the operation unit 122 and the display unit 121 may be provided as a touch panel capable of presenting a GUI.

The communication interface 124 exchanges various information with an external device (typically, PLC100). The communication interface 124 outputs information from the PLC 100 (for example, a target value SV) to the processing unit 101.

The processing unit 101 includes a processor 102, a memory 104, and a program module 105. The program module 105 is stored in a non-volatile storage medium such as a flash memory. The processor 102 calculates an operation amount MV that causes the control amount PV2 to follow the target value SV by executing the program of the program module 105.

The D / A conversion unit 114 converts a digital signal indicating an operation amount calculated by the processing unit 101 into an analog signal, and outputs the digital signal to the output circuit 116. The output circuit 116 forms an analog signal from the D / A conversion unit 114 into a signal corresponding to the control target (SSR4 in the example shown in FIG. 2) and outputs the signal. For example, when 0 to 100 [%] of the manipulated variable corresponds to a voltage signal of 0 to 10 [V], the output circuit 116 adjusts so that a signal in this voltage range is output. Alternatively, the output circuit 116 generates a PWM (Pulse Width Modulation) signal having a duty ratio according to the value of the manipulated variable. A portion (SSR4 in the example shown in FIG. 1) that performs an operation according to the operation amount MV is also referred to as an actuator.

The program module 105 includes a PID control module 166 and a target value filter 167. The target value filter 167 determines the target value characteristic in the feedback control system, and the PID control module 166 determines the feedback characteristic which is a characteristic of the feedback control system. The target value filter 167 is intended to improve the response characteristics to a change in the target value. In the temperature controller 7, when the target value SV is changed, the target value filter 167 gradually changes the target value from the current value to the changed value at a rate of change that matches the response characteristics of the entire system including the controlled object. Change. As a result, the target value filter 167 acts to prevent saturation of the manipulated variable MV of the control unit 160.

<D. Control system configuration>

The configuration of the control system 1 including the PLC 100 to which the temperature controller 7 is connected will be described. FIG. 4 is a schematic diagram showing the configuration of the control system 1 according to the present embodiment. With reference to FIG. 4, the control system 1 includes one or more PLCs 100 connected to the network NW. The PLC 100 can exchange data with each other via the network NW.

The PLC 100 includes a processing unit 10 that is a main body that executes a program, a power supply unit 12 that supplies electric power to the processing unit 10 and the like, and an IO (Input / Output) unit 14 that exchanges signals from field devices. The field device includes, for example, an actuator of the detection sensor 6 and the temperature controller 7, but the type of the field device is not limited thereto.

A support device 200 is detachably connected to the PLC 100. The support device 200 has a function of generating a program (including parameters) executed by the PLC 100, a function of monitoring the operating state of the connected PLC 100, the value of various data, and the like. Further, the support device 200 may have an editor function, a compile function, a debug function, a simulation function, and the like in order to assist the user in generating a program.

(D1: PLC hardware configuration)

FIG. 5 is a schematic diagram showing a hardware configuration of the processing unit 10 of the PLC 100 of FIG. With reference to FIG. 5, the processing unit 10 includes a processor 100, a chipset 103, a main memory 104, a non-volatile memory 106, a touch panel 108 capable of providing a GUI, and a USB (Universal Serial Bus) connector 110. , A system bus controller 120, a system bus connector 130, a network controller 140, a communication connector 150, a field network controller 151, and a field communication connector 152. The chipset 103 and other components are connected to each other via various buses.

The processor 100 and chipset 103 are typically configured according to a general purpose computer architecture. The main memory 104 is a volatile storage area and stores various programs to be executed by the processor 100 after the power is turned on to the processing unit 10. The main memory 104 is also used as a working memory when the processor 100 executes various programs. As such a main memory 104, a device such as a DRAM (Dynamic Random Access Memory) or a SRAM (Static Random Access Memory) is used.

The non-volatile memory 106 non-volatilely stores a real-time OS (Operating System), a system program, various application programs (modules), and various parameters. The non-volatile memory 106 includes, for example, an HDD (Hard disk Drive), an SSD (Solid State Drive), and the like.

The processing unit 10 has a system bus controller 120, a network controller 140, and a field network controller 151 as communication interfaces. These communication interfaces send output data and receive input data. The system bus controller 120 communicates with the IO unit 14 via the system bus connector 130, the network controller 140 communicates with other PLCs via the communication connector 150, and the field network controller 151 communicates with the temperature via the communication connector 152. Communicates with field equipment such as controller 7. The USB connector 110 is a communication interface for connecting the support device 200 and the processing unit 10. Typically, the support device 200 transfers a parameter including a program or target value SV that can be executed by the processor 100 to the PLC 100 via the USB connector 110. Further, the PLC 100 can transfer the operation amount MV and the control amounts PV1 and PV2 received from the temperature controller 7 to the support device 200 via the USB connector 110.

In another aspect, the support device 200 can also receive the operation amount MV, the control amount PV1, PV2 and the like from the temperature controller 7 without going through the PLC 100.

(D2: Hardware configuration of support device)

FIG. 6 is a schematic diagram showing an example of the hardware configuration of the support device 200 according to the embodiment of the present invention. With reference to FIG. 6, the support device 200 typically comprises a general purpose computer. From the viewpoint of maintainability, a notebook-type personal computer having excellent portability may be used.

With reference to FIG. 6, the support device 200 includes a CPU (Central Processing Unit) 201 that executes various programs including an OS (Operating System), a ROM (Read Only Memory) 202 that stores BIOS and various data, and a CPU 201. It includes a memory RAM 203 that provides a work area for storing data necessary for executing a program in the CPU 201, and a hard disk (HDD) 204 that non-volatilely stores a program or the like executed by the CPU 201.

The support device 200 further includes a keyboard 205 and a mouse 206 corresponding to an operation receiving unit that receives an operation from the user, and a display 207 for displaying information to the user. The support device 200 includes a communication interface (IF) 209 for communicating with the PLC 100 (processing unit 10) and the like. The support device 200 may be provided as a touch panel 217 in which the display 207 is integrally configured with an operation unit that receives user operations.

Various programs executed by the support device 200 are stored in the CD-ROM 300 and distributed. The program stored in the CD-ROM 300 is read by the CD-ROM (Compact Disk-Read Only Memory) drive device 208 and stored in the hard disk (HDD) 204 or the like. Alternatively, the program may be configured to be downloaded from a higher-level host computer or the like via the network. The HDD 204 stores the simulation program 218 and the data group 219 used in the simulation. The data group 219 includes an operation amount MV, a control amount PV1, PV2, a target value SV, and the like, and these data are shown as time-series data that changes with the passage of time.

<E. Target value shaping>

The simulator 500 shapes the target value SV for temperature control of the heater 3 for optimization so as to accurately follow the control amount PV1 of the work 60 to the target value sequence “work SV (original)”. By implementing (reference shaping: also called RS), the target value of shaping "RS work SV" is derived.

7 (A) and 7 (B) are graphs showing an example of target value shaping by the simulator 500 according to the present embodiment. These graphs are obtained experimentally, with time (seconds) on the horizontal axis and temperature (° C.) on the vertical axis to represent changes in temperature over time. The graph of FIG. 7A shows the “work SV (original)” as a target value sequence showing the change over time that the temperature of the work 60 should take in the process of CVD processing in the production line, and the target value shaping by the simulator 500. The "RS work SV" that has been done is shown. In FIG. 7B, when the heater 3 is driven according to the operation amount MV based on the “work SV (source)” in the environment of FIG. 2, the control amount PV1 indicated by the “work PV (source)” is acquired. On the other hand, when the heater 3 is driven according to the operation amount MV based on the "RS work SV", the control amount PV1 indicated by the "work PV (RS)" is acquired.

According to FIG. 7B, the “work PV (RS)” has a higher followability to the “work SV (original)” than the “work PV (original)”, that is, the “work SV (original)”. The deviation from and is quickly reduced. Further, the control amount PV1 of the work 60 is used instead of the control amount PV2 of the heater 3 for shaping the target value sequence. Therefore, according to the target value shaping of the simulator 500, the temperature change of the work 60 with time is optimized (shaped) so as to be able to accurately follow the change of the “work SV (original)” in the process of the CVD process. You can also get "RS Work SV".

<F. Flowchart>

FIG. 8 is a flowchart showing an outline of the process according to the present embodiment. With reference to FIG. 8, the simulator 500 performs modeling (step S1), which is a process of forming a model indicating a simulation target, and an adjustment process (step S2) for a target value, and the target acquired by the adjustment process. The value sequence (ie, "RS work SV") is transferred to the PLC100. After that, control by the actual machine (step S3) is carried out. In step S3, when the actual machine is in operation, the temperature controller 7 generates an operation amount MV according to a command signal based on the target value sequence “RS work SV” transmitted from the PLC 100, outputs the operation amount MV to the SSR 4, and outputs the heater 3. Control the calorific value.

More specifically, in modeling (step S1), the simulator 500 acquires the operation amount MV and the control amounts PV1 and PV2 of the actual machine via the PLC100 by the data acquisition unit 30 by communicating with the PLC100. , Acquire the data of "work SV (original)" indicating the original target value column (step S11). As for the acquired operation amount MV and control amount PV1 and PV2 data, the PLC100 outputs the time-series "work SV (original)" data to the temperature controller 7 in synchronization with the control cycle, and the temperature controller. 7 is the time-series data of the operation amount MV generated according to the time-series target value sequence "work SV (original)", and the time-series control amount PV1 acquired when the heater 3 is controlled according to the operation amount MV. Contains PV2.

FIG. 13 is a graph showing an example of data of the operation amount MV, the control amount PV1 and the “work SV (original)” acquired by the simulator 500 in step S11 of FIG. In FIG. 13, the vertical axis represents the unit (%) of the time-series manipulated variable MV, the controlled variable PV1 and the unit (° C.) of the “work SV (original)”, and the horizontal axis represents the time (seconds). There is. The simulator 500 may display the graph of FIG. 13 on the display 207.

Further, in modeling (step S1), the simulator 500 identifies the parameters of the controlled target model using the work model identification unit 31 (step S12). The identification procedure will be described later.

Next, in the adjustment process (step S2), the simulator 500 is an optimized "RS work SV" that accurately follows the "work SV (original)" of the original target value sequence by the target value optimization unit 32. To get. Specifically, the target value optimization unit 32 sets the "work SV (original)" acquired in step S1 as a parameter of the adjustment process (step S22), and the simulation target model identified in step S12. And "RS work SV" is acquired by using "work SV (original)" (step S23). The procedure for designing the target value in step S23 will be described later.

(F1. Data acquisition)

The data acquired by the simulator 500 in step S1 of FIG. 8 will be described with reference to FIG. FIG. 9 is a block diagram showing the configuration of FIG. 2 in a simplified manner while associating it with the data flow.

With reference to FIG. 9, during operation, the PLC 100 outputs a command according to the original target value sequence “work SV (original)” to the temperature controller 7 in synchronization with the control cycle. The temperature controller 7 uses the "work SV (original)" command and the control quantities PV1 and PV2 from the temperature sensors 61 and 62 to perform a PID control calculation to prevent saturation, thereby performing an operation amount MV. Is calculated. The SSR 4 outputs electric power corresponding to the duty ratio of the operation amount MV to the heater 3, and the heater 3 generates heat by energization. The work 60 placed on the heater 3 is heated by the heat generated by the heater 3. The temperature sensors 61 and 62 measure the temperatures of the work 60 and the heater 3, respectively, and output control quantities PV1 and PV2 indicating the measured temperatures.

The PLC 100 collects and collects the "work SV (original)" of the target value sequence which is the time series data, the manipulated variable MV and the controlled variables PV1 and PV2 of the time series data synchronized with the control cycle from the temperature controller 7. The time-series data is transmitted to the support device 200. The simulator 500 of the support device 200 stores these time-series data 221 acquired from the PLC 100 in the HDD 204, for example, as a data group 219.

(F2. Parameter identification of simulation target model)

FIG. 10 is a diagram illustrating the processing of the work model identification unit 31 in step S12 of FIG. With reference to FIG. 10, the simulator 500 uses the operation amount MV (hereinafter, also referred to as the actual MV) acquired from the actual machine in step S11 and the transfer function parameter, for example, the function f (s) of the following equation 1. ) Is performed according to the work transfer function 220, and the controlled variable PV1 is output as the calculated value (step S121).

f (s) = K1 / ((T1 · s + 1) (T2 · s + 1) (T3 · s + 1)) ... (Equation 1). The input of (Equation 1) is a real MV, T1, T2 and T3 are time constants and positive real numbers, K1 is a gain (gain) and shows a positive real number constant, and s is a Laplace operator. Is shown.

The work transfer function 220 may be a controlled target model corresponding to the heating element of the work 60 including the SSR 4 and the heater 3, and may be a function that acts to change the controlled variable PV1 according to the size of the actual MV. , The above is not limited to (Equation 1). Hereinafter, the controlled variable PV1 calculated by the work transfer function 220 representing the controlled object model is also referred to as “model PV1”.

The simulator 500 evaluates the model PV1 which is a time-series value using a predetermined function using the actual PV1 and outputs the evaluation value (step S122). The evaluation value is, for example, a value representing the followability of the model PV1 to the actual PV1.

The simulator 500 determines the optimum values of the parameters of the work transfer function 220 (transfer function parameters K1, T1, T2, T3) by, for example, a method according to a mountain climbing method (step S123). More specifically, the simulator 500 compares the evaluation value in step S122 with the threshold value, and if the comparison result determines that the convergence condition is satisfied, the simulator 500 determines the value of the parameter possessed by the work transfer function 220 as the optimum value. On the other hand, if it is determined that the comparison result does not satisfy the convergence condition, the process returns to the process using the work transfer function 220 (step S121), and the model PV1 is calculated again. When the simulator 500 re-executes the calculation using the work transfer function 220 (Equation 1), the simulator 500 changes at least one value of the parameters K1, T1, T2, and T3 of (Equation 1), and changes the parameters. The model PV1 is calculated by the work transfer function 220 having a value (steps S122 and S123).

As described above, the simulator 500 repeats the processing of steps S121 to S123 for the real MV which is the time series data every time ti (i = 1, 2, 3 ... n) using the real PV1 of the time ti. The process of calculating the parameters of the work transfer function 220 is repeated. The simulator 500 is optimized so that when the convergence condition is satisfied in the iterative process, for example, the work transfer function 220 having the parameters acquired at time tun can be derived from the model PV1 having excellent followability to the actual PV1. Identify as a work model.

FIG. 14 is a graph showing an example of data acquired in the work model identification in step S12 of FIG. In FIG. 14, the vertical axis represents the unit (%) of the actual MV, the model PV1 and the unit (° C.) of the actual PV1, and the horizontal axis represents the time (seconds). In FIG. 14, the graph of the actual PV1, the graph of the model PV1 acquired in the process of the optimum parameter search by the hill climbing method described above, and the graph of the actual MV are shown on a common time axis. According to the graph of FIG. 14, since the model PV1 accurately follows the actual PV1, it is shown that the work model having the optimum parameters could be identified in step S12. The simulator 500 can display the graph of FIG. 14 on the display 207 via the drawing data generation unit 33 and the display driver 34.

The simulator 500 stores the work transfer function 220 identified in step S123 in a storage unit such as HDD 204.

(F3. Design of target value)

FIG. 11 is a diagram illustrating the processing of the target value optimization unit 32 in step S23 of FIG. With reference to FIG. 11, in step S23, the simulator 500 performs target value shaping using the work transfer function 220 after identification. More specifically, the simulator 500 inputs the original target value sequence (that is, "work SV (original)") set in step S22. The simulator 500 repeatedly executes the process of step S23 for each time ti using the work SV (original) (ti) while changing the time ti to t1, t2, t3 .... By such repeated execution, the simulator 500 calculates the optimum RS work SV that reduces the difference between the work SV (original) and the model PV1.

In the time ti (i = 1, 2, 3, ... n), the simulator 500 converts the "work SV (original)" data in the time ti from step S22 into the "RS work SV" in the target value shaping process (step S231). Is output to the PID control process (step S232). The simulator 500 calculates the manipulated variable MV by performing the PID process for avoiding saturation by using the “RS work SV” and the model PV1 from step S233 described later (step S232). The manipulated variable MV calculated in this way is also referred to as a model MV.

The simulator 500 calculates the model PV1 by using the calculated model MV as an input and performing an operation according to the work transfer function 220 after identification (step S233). The simulator 500 evaluates the calculated model PV1 using a predetermined evaluation function, and outputs an evaluation value (step S234). The predetermined evaluation function is a function for evaluating the followability of the model PV1 to the "work SV (original)". The simulator 500 determines the optimum RS work SV (step S235). More specifically, the simulator 500 is a time-series model PV1 calculated at a time when the evaluation value output from step S234 satisfies a predetermined convergence condition, for example, when the convergence condition is satisfied at time tn, time t1. The time-series model PV1 calculated by ~ tun is determined to be the optimized RS work SV.

When the simulator 500 can determine (search) the optimized RS work SV, it outputs the RS work SV, but when it cannot determine, the model PV1 from step S233 is subjected to the target shaping process (step S231). Then, it is output to the PID control process (S232) as an RS work SV. The simulator 500 repeats the subsequent processes of steps S223 to S235 until the optimized RS work SV is determined.

The simulator 500 performs the processing of steps S231 to S235 for the time ti data in the "work SV (original)" of the target value sequence input from step S22 until the convergence condition is satisfied, in the time t1, t2, t3 ... Repeat for the data. As a result, the simulator 500 can acquire the time-series optimized RS work SV corresponding to the time-series data of the "work SV (original)". The simulator 500 stores the optimized "RS work SV" in a storage unit such as HDD 204 as a data group 291.

In the process of FIG. 11, the control amount PV2 (hereinafter, also referred to as model PV2) may be calculated from the model MV output from the PID control process (step S232) in synchronization with the calculation of the model PV1. More specifically, the simulator 500 is a model showing the temperature of the heater 3 in synchronization with the calculation of the model PV1 by an arithmetic process (step S236) using a heater transfer function that models the heat transfer characteristics of the heater 3. PV2 may be calculated. In the present embodiment, the simulator 500 may display the time-series model PV2 corresponding to the “work SV (original)” of the target value sequence on the display 207, for example.

<G. Configuration of heating system to which Simulator 500 can be applied>

FIG. 12 is a diagram illustrating in a table format the types of configurations of a heating system to which target value shaping can be applied. With reference to FIG. 12, as the type 111 of the configuration of the heating system, for example, a cascade control 211, a work temperature FB (feedback) control 212, a work temperature FF (feed forward) control 213, and a heater temperature FB (feedback) control 214 are provided. include. In association with each type 111, the presence / absence of the temperature sensor 61 of the work 60 and the temperature sensor 62 of the heater 3 in the actual machine adopting the configuration of the heating system of the type, and the conditions of the simulator 500 for the heating system are shown. The conditions of the simulator 500 include the necessity of modeling 1141 of the work transfer function and modeling 1151 of the heater transfer function, RS target 1161, and optimization target 1171. The RS target 1161 indicates a target temperature SV to be shaped in the simulator 500. More specifically, the target temperature SV indicates the target temperature of the heater 3 (indicated as the heater SV in FIG. 12) or the target temperature of the work 60 (indicated as the work SV in FIG. 12). The optimization target 1171 is a control amount to be evaluated in the target value evaluation (step S234), and more specifically, as a difference between the target temperature SV and the calculated control amount PV, the model PV1 (FIG. 12 shows the work temperature error) or model PV2 (shown as the heater temperature error in FIG. 12).

The simulator 500 according to the present embodiment utilizes a heater transfer function or a work transfer function 220 to provide a portion (work or work) of a heating system that does not have a temperature sensor during operation for all types of system configurations shown in FIG. It is possible to design a target value that optimizes the temperature of the heater).

<H. Manual adjustment of target value>

FIG. 15 is a diagram showing an example of a GUI for adjusting a target value according to the present embodiment. With reference to FIG. 15, the drawing data generation unit 33 generates drawing data for drawing the GUI of FIG. 15, the display driver 34 drives the display 207 based on the drawing data, and the display 207 is shown in FIG. Display the GUI.

The GUI of FIG. 15 has a common target value sequence before change (“work SV (original)”) indicating a temporal change and a second temporal characteristic (“model PV1”) calculated by the simulator 500. An adjustment object (spin) that accepts user operations for adjusting an object for visualization on the time axis (graph 280) and a modified target value sequence (“RS work SV”) derived by the target value optimization unit 32. Includes button 270 or slide bar 271).

With reference to FIG. 15, in graph 280, time (seconds) is taken on the horizontal axis, and temperature (unit: ° C.) and manipulated variable (unit:%) are taken on the vertical axis orthogonal to the horizontal axis. The graph shows, for example, "model MV", "work SV (original)", "model PV1", "RS work SV", and, as temporal characteristics acquired with respect to the controlled variable PV1 of the work 60 to be simulated. For each of the "model PV2", for example, a line graph showing changes in values (temperature, manipulated variable) corresponding to the passage of time is included, which are shown on a common time axis.

In the graph 280, which is the object for visualization, at least the target value sequence (“work SV (original)”), the second temporal characteristic (“model PV1”), and the changed target value (“model PV1”). By visualizing the RS work SV ") on a common time axis, the user can visually grasp the magnitude of the deviation of the" model PV1 "with respect to the" work SV (original) ", that is, the followability. Can provide information for. In addition, by visually presenting the change in the value of the "RS work SV" with the passage of time, the value of the "RS work SV" corresponding to the time zone in which the followability is reduced to the user. Information can be presented to identify.

The spin button 270 corresponds to a first object that accepts a user operation to increase or decrease the changed target value sequence (“RS work SV”). The spin button 270 includes a plurality of buttons arranged in parallel with the direction in which the time axis extends in relation to the time axis. Each button accepts a user operation to increase or decrease the target value (value in the target value sequence "RS work SV") corresponding to the time indicated by the nearest scale of the button on the time axis. The GUI may further include an object that, when each button is operated, draws a target value corresponding to the time indicated by the nearest scale of the button.

Further, the adjustment object may include a second object such as a numerical input dialog for accepting a user operation for inputting a numerical value in place of the spin button 270 or together with the spin button 270.

Further, each button of the spin button 270 can accept a user operation for increasing / decreasing the target value within a range from a predetermined upper limit value to a lower limit value of the value of the target value sequence (“RS work SV”). , The GUI may include an object in a dialog box that displays the upper and lower bounds and draws the current value in relation to the button. This makes it possible to visually present to the user a range in which the target value can be adjusted.

Further, each button of the spin button 270 may be configured to accept a user operation for increasing or decreasing the value of the target value sequence (“RS work SV”) by a predetermined amount.

In another aspect, the user may operate the slider 273 of the slide bar 271 for numerical adjustment of the target value sequence (“RS work SV”) in the graph 280. The slide bar 271 includes a slider 273 and a slider bar 272 in which the slider 273 is a slide movable area. When the user specifies a numerical value corresponding to a certain time in the target value column (“RS work SV”) of the graph 280 and moves the slider 273 on the slider bar 272, the numerical value is adjusted according to the movement amount. Can be (changed). The GUI may include a dialog box object that draws the current value of the target value sequence (“RS Work SV”), or the adjusted value, in connection with the slider 273. The user can also adjust the value of the graph by combining the operation of the spin button 270 and the operation of the slider 273.

When the simulator 500 receives a user operation for adjusting the value of the changed target value sequence (“RS work SV”) via the adjustment object (spin button 270 or slider 273), the adjusted target is the target. The process is re-executed by the target value optimization unit 32 using the value sequence.

More specifically, the simulator 500 detects that the acceptance of the user operation of the spin button 270 for numerical adjustment of the graph is completed (for example, the enter key is operated) by the GUI based on the output of the adjustment object. Then, the simulation is executed again. In the re-execution of the simulation, the simulator 500 accepts the user operation for the spin button 270 (or the slider 273), and the target value optimization unit 32 receives the "RS work SV" corresponding to the time based on the accepted operation content. The value in is adjusted, and the time-series target value sequence SV of the adjusted "RS work SV" is output to the data acquisition unit 30.

The data acquisition unit 30 receives the time-series target value sequence SV which is the value of the adjusted “RS work SV” via the GUI. The target value optimization unit 32 executes processing using the adjusted time-series target value sequence SV according to the processing procedure described in FIG. 11, and the drawing data generation unit 33 outputs the result of the re-executed simulation. The drawing data to be drawn is generated, and the display driver 34 drives the display 207 based on the drawing data. The display 207 displays a GUI (FIG. 15) including a graph 280 of the simulation execution result using the adjusted column SV.

As a result, the simulator 500 provides the user with a graph 280 including the "RS work SV" of the target value sequence acquired by the simulation (target value optimization unit 32) using the target value sequence SV adjusted by the user. It is possible to present the GUI that it has. When the user adjusts the "RS work SV" again so that the model PV1 accurately follows the "work SV (original)", the simulator 500 simulates using the target value sequence SV adjusted by the user. (Target value optimization unit 32) is executed. By repeating such a simulation, the calculated target value sequence "RS work SV" can be further optimized by the adjustment of the user.

(H1. Presentation of evaluation value)

In the embodiment, the followability of the model PV1 to the "work SV (original)" is evaluated in step S234 (FIG. 11) using a predetermined evaluation function, and the GUI is calculated by the evaluation function. It may be configured to include an object for visualizing the evaluation value.

FIG. 16 is a diagram showing an example of display of the evaluation value 291 output by the evaluation function according to the present embodiment. The simulator 500 can present the evaluation value 291 as information for assisting the user in adjusting the target value sequence “RS work SV”. More specifically, the simulator 500 stores the evaluation value 291 of the evaluation function in the HDD 204. When the graph 280 of the simulation result is displayed, the simulator 500 displays an object representing the evaluation value 291 via the drawing data generation unit 33. In FIG. 16, by visualizing and presenting the evaluation value 291 of the evaluation function, how much the model PV1 shown in the graph 280 follows the target value sequence “work SV (original)” to the user. It is possible to quantitatively provide the followability showing the above. From the evaluation value 291 the user can obtain a standard for determining whether or not to adjust the "RS work SV".

(H2. Adjustment of simulation time)

In another aspect, the simulation is started at predetermined intervals, and the user can adjust the target value sequence “RS work SV” given to the simulator 500 at intervals.

17, FIG. 18, FIG. 19 and FIG. 20 are diagrams showing other examples of the GUI for adjusting the target value according to the present embodiment. With reference to FIG. 17, a GUI having an object for displaying a graph 280 showing a simulation result, a period 292, and adjustment data 290 on a display 207 based on the drawing data generated by the drawing data generation unit 33. Is displayed. The period 292 is a value that can be set by a user operation, and indicates the time of the start and end (for example, 0 seconds for the start and 5400 seconds for the end) of the period for which the target value adjustment is to be performed. The adjustment data 290 is data that can be set by a user operation. Specifically, the adjustment data 290 corresponds to each of the start time 293 of a plurality of simulations according to a predetermined interval (for example, 600 seconds) in the period 292 and each start time 293, and "RS work SV". Includes the target value of 294.

The simulator 500 outputs the adjustment data 290 based on the user operation content received via the GUI of FIG. 17 to the target value optimization unit 32. The target value optimization unit 32 measures the adjusted "RS work SV" 294 corresponding to each start time tj indicated by the adjustment data 290, and the actual MV and the actual PV1 corresponding to the time tj stored in the HDD 204. Output to the acquisition unit 30. The simulator 500 re-executes the simulation by the target value optimization unit 32 using the data acquired by the data acquisition unit 30.

More specifically, the target value optimization unit 32 uses the adjusted “RS Work SV” 294, the actual MV, and the actual PV1 corresponding to the time tj for each time tj, and after the adjustment for each time tj. Calculate "RS work SV". The drawing data generation unit 33 generates drawing data based on the simulation result for each interval, and the display 207 displays a GUI based on the drawing data. In the displayed GUI, the simulation result is displayed as a line graph in which the values for each time tj corresponding to the interval are connected by a straight line.

The adjustment data 290 of FIG. 17 shows 600 seconds as an interval (start time 293 is 0 seconds, 600 seconds, 1200 seconds ... 5400 seconds), but the interval is not limited to 600 seconds.

In FIG. 18, the period 292 indicates 0 to 9600 seconds, and the interval indicated by the start time 293 is 600 seconds (start time 293 is 0 seconds, 600 seconds, 1200 seconds ..., 9600 seconds), and the start time is 293. For example, "RS Work SV" 294 corresponding to 4200 seconds has been adjusted (changed) from 166.0 to 22.1.

In this case, the simulation using the adjusted "RS work SV" 294 is executed at the interval indicated by the start time 293, and the execution result is displayed by the graph 280 of FIG. It is shown that the graph 280 of FIG. 19 has improved followability to the “work SV (original)” of the model PV1 as compared with the case of the graph 280 of FIG. From the graph 280 of FIG. 19, the user can determine the adjusted "RS work SV" 294 of FIG. 19 as a candidate of a target value for controlling the heating system of the actual machine.

In FIGS. 18 and 19, the user adjusted the "RS Work SV" 294 corresponding to one start time 293 (eg 4200 seconds), but as shown in FIG. 20, a plurality of start times 293 (eg 7800). It is also possible to adjust the "RS Work SV" 294 corresponding to each of seconds, 8400 seconds, 9000 seconds and 9600 seconds). By adjustment, the values of "RS Work SV" 294 corresponding to 7800 seconds, 8400 seconds, 9000 seconds and 9600 seconds are all changed to 300.0.

In the simulation using the target value shown in the adjusted "RS work SV" 294 shown in FIGS. 17 to 20, the simulator 500 performs the process of FIG. 11 every time tj specified by the interval. Therefore, the user can adjust (change) the time for performing the simulation by the length of the interval set via the adjustment data 290. Therefore, in the adjustment data 290, the elapsed time indicated by the time axis of the graph 280 is the period during which the target value optimization unit 32 evaluates the followability of the model PV1 to the “work SV (source)” in step S234 (FIG. 11). It also functions as an object that accepts user operations for designation at (ie, start time 293).

<I. Realization example of simulator 500>

The simulation program 218 that realizes the simulator 500 is stored in the HDD 204 that stores the program non-volatilely, and the CPU 201 realizes the simulator 500 by executing the simulation program 218 stored in the HDD 204. The simulation program 218 is not limited to the HDD 204, and may be stored in various other recording media such as the RAM 203 or the CD-ROM 300. These storage media store the information of the program, etc. by electrical, magnetic, optical, mechanical, or chemical action so that the information of the program, etc. recorded by the computer or other device, machine, etc. can be read. It is a medium to do. When the simulation program 218 is executed, the CPU 201 expands the target program stored in these recording media into the RAM 203. Then, the CPU 201 interprets and executes the program expanded in the RAM 203 to control each component.

In embodiments, the simulator 500 exemplifies the configurations provided by the execution of the simulation program 218, but some or all of these provided configurations may be part of a dedicated hardware circuit (eg, an ASIC). It may be implemented using Application Specific Integrated Circuit) or FPGA (Field-Programmable Gate Array). Alternatively, the main part of the support device 200 may be realized by using hardware that follows a general-purpose architecture. In this case, virtualization technology may be used to execute a plurality of OSs having different uses in parallel, and to execute necessary applications on each OS.

In this embodiment, the support device 200 is a simulator 500 that is the main body that carries out the simulation, but the main body that carries out the simulation is not limited to the support device 200. For example, the simulator 500 may be mounted on the PLC 100 or the temperature controller 7, or may be mounted on yet another entity, for example, a cloud server on a network, and the GUI is a support device 200 that communicates with the cloud server. It may be provided to the user via a browser implemented in.

<J. Addendum>

The present embodiment as described above includes the following technical ideas.

[Structure 1]

A method in which a computer (20) simulates the temporal characteristics of an object (60) heated by a heating element (3) that changes the calorific value according to an operation amount (MV).

A step of constructing a target model (220) indicating the target with the operation amount (MV) as an input and the observation amount (PV1) of the target as an output.

The first temporal characteristic is calculated as an input (MV) of the target model using a time-series target value sequence (work RS (source)), and the target model is input with respect to the input of the first temporal characteristic. The step (S232, S233) of calculating the output (PV1) as the second temporal characteristic,

The step (S231, S235) of changing the target value sequence based on the followability of the second temporal characteristic to the target value sequence, and

Using the changed target value sequence, the step of re-implementing the above-mentioned calculation step and the step of re-implementing the above calculation step,

Adjust the object (280) for visualizing the target value sequence before the change and the second temporal characteristic calculated in the step to be re-executed on a common time axis, and the target value sequence after the change. A simulation method comprising outputting a GUI including an adjustment object (270, 271) that accepts user operations for.
[Structure 2]

The object for visualization visualizes the target value sequence before the change, the second temporal characteristic calculated in the step to be re-executed, and the target value sequence after the change on the common time axis. The simulation method according to configuration 1, comprising an object for.
[Structure 3]

The object for visualization is a graph of the target value column at coordinates in which the elapsed time is assigned to the common time axis and the target value, the manipulated variable, and the observed amount are assigned to the axis orthogonal to the time axis. The simulation method according to configuration 1 or 2, comprising the graph showing the first temporal characteristic and the graph showing the second temporal characteristic.
[Structure 4]

A step (S234) for evaluating the followability using a predetermined evaluation function is further provided.

The simulation method according to any one of configurations 1 to 3, wherein the GUI further includes an object for visualizing an evaluation value (291) calculated by the evaluation function.
[Structure 5]

The simulation method according to configuration 4, wherein the GUI further includes an object (292) for accepting a user operation for designating a period for evaluating the followability in an elapsed time indicated by the time axis.
[Structure 6]

When a user operation for adjusting the changed target value sequence is accepted via the adjustment object, the step of re-implementing the calculation step using the adjusted target value sequence is further provided. The simulation method according to any one of configurations 1 to 5.
[Structure 7]

The adjustment object is

Either configuration 1 to 6, including a first object (270, 271) that accepts a user operation for increasing or decreasing the changed target value, or a second object that accepts a user operation for inputting a numerical value. The simulation method according to 1.
[Structure 8]

The first object includes a plurality of buttons arranged in parallel with the direction in which the time axis extends in association with the common time axis.

The simulation method according to configuration 7, wherein each button accepts a user operation for increasing or decreasing a target value in the target value sequence corresponding to a time indicated by the nearest scale of the button on the time axis.
[Structure 9]

The simulation method according to configuration 8, wherein each button accepts a user operation for increasing or decreasing the target value within a range from the upper limit value to the lower limit value of the target value.
[Structure 10]

The simulation method according to configuration 8 or 9, wherein each button accepts a user operation for increasing or decreasing the target value by a predetermined amount.
[Structure 11]

The simulation according to any one of configurations 8 to 10, further comprising an object that draws the target value corresponding to the time indicated by the nearest scale of the button when each button is operated. Method.
[Structure 12]

A simulation program (218) for realizing the simulation method according to any one of configurations 1 to 11 when executed by a computer (200).
[Structure 13]

A simulator (500) for executing the simulation method according to any one of configurations 1 to 11.

It should be considered that the embodiments disclosed this time are exemplary in all respects and not restrictive. The scope of the present invention is shown by the scope of claims rather than the description of the embodiments described above, and is intended to include all modifications within the meaning and scope equivalent to the scope of claims.

1 Control system, 3 Heater, 5 Power supply, 7 Temperature controller, 30 Data acquisition unit, 31 Work model identification unit, 32 Target value optimization unit, 33 Drawing data generation unit, 34 Display driver, 61, 62 Temperature sensor, 200 Support device, 207 display, 218 simulation program, 219 data group, 220 work transfer function, 221 time series data, 270 spin buttons, 271 slide bar, 272 slider bar, 273 slider, 280 graph, 290 adjustment data, 291 evaluation value. , 292 period, 500 simulator, MV operation amount, PV1, PV2 control amount, SV target temperature.

Claims (12)

A method in which a computer simulates the temporal characteristics of an object heated by a heating element that changes the amount of heat generated according to the amount of operation.
A step of constructing an object model indicating the object, which uses the manipulated variable as an input and the observed amount of the object as an output.
The first temporal characteristic is calculated as the input of the target model using the target value sequence of the time series, and the output of the target model with respect to the input of the first temporal characteristic is calculated as the second temporal characteristic. Steps to do and
A step of changing the target value sequence based on the followability of the second temporal characteristic to the target value sequence, and
Using the changed target value sequence, the step of re-implementing the above-mentioned calculation step and the step of re-implementing the above calculation step,
An object for visualizing the target value sequence before the change and the second temporal characteristic calculated in the step to be re-executed on a common time axis, and a user for adjusting the target value sequence after the change. Steps to output a GUI, including adjustment objects that accept operations, and
Including a step of evaluating the followability using a predetermined evaluation function, and the like.
The GUI further accepts an object for visualizing the evaluation value calculated by the evaluation function and a user operation for designating a period for evaluating the followability in the simulation in the elapsed time indicated by the time axis. Simulation method, including with objects. The object for visualization visualizes the target value sequence before the change, the second temporal characteristic calculated in the step to be re-executed, and the target value sequence after the change on the common time axis. The simulation method according to claim 1, comprising an object for the purpose. The object for visualization is a graph of the target value column at coordinates in which the elapsed time is assigned to the common time axis and the target value, the manipulated variable, and the observed amount are assigned to the axis orthogonal to the time axis. The simulation method according to claim 1 or 2, further comprising a graph showing the first temporal characteristic and a graph showing the second temporal characteristic. When a user operation for adjusting the changed target value sequence is accepted via the adjustment object, the step of re-implementing the calculation step using the adjusted target value sequence is further provided. The simulation method according to any one of claims 1 to 3. The adjustment object is
Any of claims 1 to 4 , including a first object that accepts a user operation for increasing or decreasing a target value in the changed target value column, or a second object that accepts a user operation for inputting a numerical value. The simulation method according to item 1. The first object includes a plurality of buttons arranged in parallel with the direction in which the time axis extends in association with the common time axis.
The simulation method according to claim 5 , wherein each button accepts a user operation for increasing or decreasing the target value corresponding to the time indicated by the nearest scale of the button on the time axis. The simulation method according to claim 6 , wherein each button accepts a user operation for increasing or decreasing the target value within a range from the upper limit value to the lower limit value of the target value. The simulation method according to claim 6 or 7 , wherein each button accepts a user operation for increasing or decreasing the target value by a predetermined amount. The GUI further according to any one of claims 6 to 8 , further comprising an object that draws the target value corresponding to the time indicated by the nearest scale of the button when each button is operated. Simulation method. A method in which a computer simulates the temporal characteristics of an object heated by a heating element that changes the amount of heat generated according to the amount of operation.
A step of constructing an object model indicating the object, which uses the manipulated variable as an input and the observed amount of the object as an output.
The first temporal characteristic is calculated as the input of the target model using the target value sequence of the time series, and the output of the target model with respect to the input of the first temporal characteristic is calculated as the second temporal characteristic. Steps to do and
A step of changing the target value sequence based on the followability of the second temporal characteristic to the target value sequence, and
Using the changed target value sequence, the step of re-implementing the above-mentioned calculation step and the step of re-implementing the above calculation step,
An object for visualizing the target value sequence before the change and the second temporal characteristic calculated in the step to be re-executed on a common time axis, and a user for adjusting the target value sequence after the change. Includes a step to output a GUI, including an adjustment object that accepts operations, and
The adjustment object is
A first object that accepts a user operation for increasing or decreasing the target value in the changed target value column, or a second object that accepts a user operation for inputting a numerical value is included.
The first object includes a plurality of buttons arranged in parallel with the direction in which the time axis extends in association with the common time axis.
A simulation method in which each button receives a user operation for increasing or decreasing the target value corresponding to the time indicated by the nearest scale of the button on the time axis. A simulation program for realizing the simulation method according to any one of claims 1 to 10 , when executed by a computer. A simulator for executing the simulation method according to any one of claims 1 to 10.

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