Control system and control method

Abstract

To obtain good control characteristics with respect to a control object with strong nonlinear characteristics.SOLUTION: An industrial PC1 generates time series data on a control amount and an operation amount, which correspond to an ideal control response, transmits the data on the control amount, and transmits a parameter value of approximate expression of the operation amount. A PID controller 2 includes: a receiving section 30 that receives the transmitted control amount as a reference set value, and receives a parameter value of approximate expression as a parameter value of approximate expression of a feedforward control operation amount; a feedback calculation section 25 that uses the reference set value and a measured value of the control amount as input, and calculates a first operation amount by performing PID calculation; a feedforward addition section 26 that calculates the feedforward control operation amount on the basis of the received parameter value and calculates a second operation amount by adding the feedforward control operation amount to the first operation amount; and an operation amount output section 28 that outputs the second operation amount to a control object.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a control system and a control method that uses both feedback control and feedforward control. [Background technology]

[0002] Regarding PID control, a technique for automatically adjusting PID parameters to maintain optimal control performance when a set value SP is changed has been disclosed (see Patent Document 1). This PID parameter adjustment technique is applicable to a temperature regulator, which is a PID controller for controlling temperature. In addition, this is a method for searching for PID parameters so as to follow a target trajectory of a controlled variable PV, and theoretically, this method assumes a controlled object with linear characteristics.

[0003] A linear characteristic is a characteristic in which the relationship between the theoretical manipulated variable MV and the output action to the actual controlled object is linear when the output value of the theoretical manipulated variable MV is 0% to 100% on the horizontal axis of a graph and the output action to the actual controlled object is 0% to 100% on the vertical axis as shown in Fig. 21. However, for example, a slightly nonlinear characteristic (weakly nonlinear characteristic) as shown in Fig. 22 can be applied to the technology disclosed in Patent Document 1 as an allowable range for PID control.

[0004] The method disclosed in Patent Document 1 cannot maintain good PID control performance for a control target with strongly nonlinear characteristics in which the relationship between theory and reality is as shown in Fig. 23. Such strongly nonlinear characteristics appear in temperature control systems that use special electric heaters, or flow control systems or pressure control systems that control fluids with valves.

[0005] 24 to 26 show the results of simulations when the operating amount MV (heater output) is 0% and the controlled amount PV (temperature) is heated to different target temperatures (set values ​​SP) by PID control from a state where the operating amount MV (heater output) is 0% and the controlled amount PV (temperature) is stabilized at 50°C. In these simulations, when heating from 50°C to 150°C as shown in Fig. 24, the PID parameters are adjusted so that the controlled amount PV follows the target temperature.

[0006] Here, when the temperature is raised from 50°C to 250°C as shown in Fig. 25, if the PID parameters are the same as in Fig. 24, the controlled variable PV will fluctuate up and down. Similarly, when the temperature is raised from 50°C to 350°C as shown in Fig. 26, if the PID parameters are the same as in Fig. 24, the controlled variable PV will fluctuate even more up and down. The reason that the controlled variable PV fluctuates up and down is that, as shown in Fig. 27, the theoretical and actual slopes of the manipulated variable MV for maintaining each target temperature in Figs. 24 to 26 (approximately 70% in Fig. 24, approximately 80% in Fig. 25, and approximately 90% in Fig. 26) are different, and the greater the slope, the more likely it is that the controlled variable PV will fluctuate up and down.

[0007] As described above, it is difficult to obtain good control characteristics with PID control, for example, for a control target with strongly nonlinear characteristics. On the other hand, in order to maintain stable and safe control operation, the PID control loop is executed with a PID controller (such as a temperature controller) dedicated to PID calculation, which is also a standard instrumentation concept in industry, especially within manufacturing equipment. In other words, the limitations of PID control must be overcome while maintaining the reasons why PID controllers should be used, and improvements are required. [Prior art documents] [Patent documents]

[0008] [Patent Document 1] Patent No. 4223894 Summary of the Invention [Problem to be solved by the invention]

[0009] The present invention has been made to solve the above-mentioned problems, and has an object to provide a control system and a control method that can obtain good control characteristics for a controlled object having strongly nonlinear characteristics. [Means for solving the problem]

[0010] The control system of the present invention is composed of a host device and a PID controller, the host device includes an ideal response generating unit configured to generate time series data of a controlled variable and time series data of a manipulated variable corresponding to an ideal control response, a memory unit configured to store the time series data of the controlled variable and the time series data of the manipulated variable, a functional equation approximation replacement unit configured to approximate the time series data of the manipulated variable stored in the memory unit by a function whose second-order derivative is continuous, and a transmission unit configured to sequentially extract data of the controlled variable for each control period from the time series data stored in the memory unit and transmit the data to the PID controller at a specified timing, and to transmit parameter values ​​of the approximation equation obtained by the functional equation approximation replacement unit to the PID controller. the control amount output unit configured to output the second operation amount calculated by the feedforward control adder to a control target object, ....

[0011] In one configuration example of the control system of the present invention, the PID controller further includes a limit processing unit configured to output a third manipulated variable obtained by limiting the second manipulated variable calculated by the feedforward addition unit to a value within a range between a manipulated variable upper limit value and a manipulated variable lower limit value, and the transmission unit transmits, at the specified timing, a parameter value of the manipulated variable upper limit value and a parameter value of the manipulated variable lower limit value, which are calculated based on a parameter value transmitted by the transmission unit itself and assume an error range of an approximation value of the manipulated variable for each control cycle, together with the data of the controlled variable and the parameter value of the approximation formula, to the PID controller. the receiving unit receives the parameter value of the manipulated variable upper limit value and the parameter value of the manipulated variable lower limit value transmitted from the host device as new values ​​to be used in the limit processing unit, the limit processing unit calculates the manipulated variable upper limit value based on the feedforward control manipulated variable and the parameter value of the manipulated variable upper limit value and calculates the manipulated variable lower limit value based on the feedforward control manipulated variable and the parameter value of the manipulated variable lower limit value, and the manipulated variable output unit outputs the third manipulated variable to a control object instead of outputting the second manipulated variable to the control object.

[0012] Moreover, in one configuration example of the control system of the present invention, the parameter value of the operating volume upper limit value is an upward side margin value, and the parameter value of the operating volume lower limit value is a downward side margin value, and the limit processing unit sets a value obtained by adding the upward side margin value to the feedforward control operating volume as the operating volume upper limit value, and sets a value obtained by subtracting the downward side margin value from the feedforward control operating volume as the operating volume lower limit value. In addition, in one configuration example of the control system of the present invention, the PID controller further includes an operation amount correction amount output unit configured to transmit time series data of the first operation amount to an outside. In addition, in one configuration example of the control system of the present invention, the ideal response generating unit is characterized in that it generates time series data of controlled variables and time series data of manipulated variables corresponding to an ideal control response by utilizing a virtual controlled object model for reproducing the behavior of the controlled object on a computer.

[0013] The control method of the present invention includes a first step in which a host device generates time series data of a controlled variable and time series data of a manipulated variable corresponding to an ideal control response, a second step in which the host device stores the time series data of the controlled variable and the time series data of the manipulated variable, a third step in which the host device approximates the time series data of the manipulated variable stored in the second step by a function whose second derivative is continuous, a fourth step in which the host device sequentially extracts data of the controlled variable for each control cycle from the time series data stored in the second step at a specified timing and sequentially transmits the data to a PID controller, and transmits parameter values ​​of the approximation equation obtained in the third step to the PID controller, and a fourth step in which the PID controller references the controlled variable transmitted from the host device and sets the time series data. a fifth step of receiving a parameter value of the approximation equation transmitted from the host device as a new constant value and receiving a parameter value of the approximation equation of a feedforward control manipulated variable from the host device as a parameter value of an approximation equation of a feedforward control manipulated variable; a sixth step of the PID controller acquiring a measured value of the controlled variable; a seventh step of the PID controller performing a PID calculation using the reference set value and the measured value of the controlled variable as inputs to calculate a first manipulated variable; an eighth step of the PID controller calculating a feedforward control manipulated variable based on the parameter value received in the fifth step and adding the feedforward control manipulated variable to the first manipulated variable to calculate a second manipulated variable; and a ninth step of outputting the second manipulated variable calculated in the eighth step to a controlled object.

[0014] Moreover, one configuration example of the control method of the present invention further includes a tenth step in which the PID controller outputs a third manipulated variable obtained by limiting the second manipulated variable calculated in the eighth step to a value within a range between a manipulated variable upper limit value and a manipulated variable lower limit value, the fourth step includes a step of transmitting, at the specified timing, a parameter value of the manipulated variable upper limit value and a parameter value of the manipulated variable lower limit value, which assume an error range of an approximation value of the manipulated variable for each control cycle calculated from a parameter value transmitted by the host device, together with the data of the controlled variable and the parameter value of the approximation formula, to the PID controller, and the fifth step includes The method includes a step of receiving the parameter value of the manipulated variable upper limit value and the parameter value of the manipulated variable lower limit value transmitted from the host device as new values ​​to be used in the tenth step, the tenth step includes a step of calculating the manipulated variable upper limit value based on the feedforward control manipulated variable and the parameter value of the manipulated variable upper limit value, and calculating the manipulated variable lower limit value based on the feedforward control manipulated variable and the parameter value of the manipulated variable lower limit value, and the ninth step includes a step of outputting the third manipulated variable to a control object instead of outputting the second manipulated variable to the control object.

[0015] Moreover, in one configuration example of the control method of the present invention, the parameter value of the manipulated variable upper limit value is an upward side margin value, and the parameter value of the manipulated variable lower limit value is a downward side margin value, and the tenth step includes a step of setting a value obtained by adding the upward side margin value to the feedforward control manipulated variable as the manipulated variable upper limit value, and setting a value obtained by subtracting the downward side margin value from the feedforward control manipulated variable as the manipulated variable lower limit value. Moreover, one configuration example of the control method of the present invention is characterized in that it further includes an eleventh step in which the PID controller transmits time-series data of the first manipulated variable to an outside. Moreover, in one configuration example of the control method of the present invention, the first step is characterized by including a step of generating time series data of a controlled variable and time series data of a manipulated variable corresponding to an ideal control response by utilizing a virtual controlled object model for reproducing the behavior of the controlled object on a computer. Effect of the Invention

[0016] According to the present invention, by providing the host device with an ideal response generating unit, a storage unit, a function formula approximation replacing unit, and a transmitting unit, and providing the PID controller with a receiving unit, a controlled variable acquiring unit, a feedback calculating unit, a feedforward adding unit, and a manipulated variable output unit, it is possible to obtain good control characteristics for a controlled object with strongly nonlinear characteristics while efficiently utilizing the PID controller. Also, in the present invention, the combination of the PID controller and the host device is connected based on control theory, so that it is possible to realize instrumentation that is responsive to strongly nonlinear characteristics and easy to perform fine adjustments based on control theory. [Brief description of the drawings]

[0017] [Figure 1] FIG. 1 is a block diagram showing a configuration of a control system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a flowchart illustrating the operation of the industrial PC according to the embodiment of the present invention. [Diagram 3] FIG. 3 is a diagram showing an example of a change in the feedforward amount according to the embodiment of the present invention. [Figure 4] FIG. 4 is a flowchart illustrating the operation of the PID controller according to the embodiment of the present invention. [Diagram 5] FIG. 5 is a diagram showing changes in the controlled variable and the manipulated variable that correspond to an ideal control response. [Figure 6] FIG. 6 is a diagram showing changes in the controlled variable and the manipulated variable that correspond to an ideal control response. [Figure 7] FIG. 7 is a diagram showing changes in the controlled variable and the manipulated variable that correspond to an ideal control response. [Figure 8]FIG. 8 is a diagram showing the result of executing only feedforward control on a control target with a strong nonlinear characteristic. [Figure 9] FIG. 9 is a diagram showing the result of executing only feedforward control on a control target with a strong nonlinear characteristic. [Figure 10] FIG. 10 is a diagram showing the result of executing only feedforward control on a control target with a strong nonlinear characteristic. [Figure 11] FIG. 11 is a diagram showing a manipulated variable that is an approximation of a manipulated variable that corresponds to an ideal control response. [Figure 12] FIG. 12 is a diagram showing a simulation result of the control according to the embodiment of the present invention. [Figure 13] FIG. 13 is a diagram showing a comparison result between the feedforward control operation amount in FIG. 12 and the operation amount actually output from the operation amount output section. [Figure 14] FIG. 14 is a diagram showing another simulation result of the control according to the embodiment of the present invention. [Figure 15] FIG. 15 is a diagram showing a comparison result between the feedforward control operation amount in FIG. 14 and the operation amount actually output from the operation amount output section. [Figure 16] FIG. 16 is a diagram showing a change in the difference between the feedforward control operation amount in FIG. 15 and the operation amount actually output from the operation amount output section. [Figure 17] FIG. 17 is a diagram showing another simulation result of the control according to the embodiment of the present invention. [Figure 18] FIG. 18 is a diagram showing a comparison result between the feedforward control operation amount in FIG. 17 and the operation amount actually output from the operation amount output section. [Figure 19] FIG. 19 is a diagram showing a change in the difference between the feedforward control operation amount in FIG. 18 and the operation amount actually output from the operation amount output section. [Figure 20] FIG. 20 is a block diagram showing an example of the configuration of a computer that realizes a control system according to an embodiment of the present invention. [Figure 21]FIG. 21 is a diagram for explaining a control target of linear characteristics. [Figure 22] FIG. 22 is a diagram for explaining a control target having weakly nonlinear characteristics. [Diagram 23] FIG. 23 is a diagram for explaining a control target having a strongly nonlinear characteristic. [Figure 24] FIG. 24 is a diagram showing a simulation result of PID control for a control target having a strongly nonlinear characteristic. [Diagram 25] FIG. 25 is a diagram showing a simulation result of PID control for a control target having a strongly nonlinear characteristic. [Figure 26] FIG. 26 is a diagram showing a simulation result of PID control for a control target having a strongly nonlinear characteristic. [Figure 27] FIG. 27 is a diagram for explaining the reason why the controlled variable fluctuates up and down in PID control for a controlled object with nonlinear characteristics. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0018] [Principle 1] It is possible to obtain changes in the controlled variable PV and the manipulated variable MV that are close to the ideal control response by using a simulation that uses a controlled object model (a virtual controlled object that reproduces the behavior of the controlled object on a computer based on mathematical formulas such as differential equations) that may include strongly nonlinear characteristics, or by using a control trial that uses an actual controlled object.

[0019] Therefore, if the time series data of the controlled variable PV obtained by simulation or control trial is used as the reference set value SP, and the time series data of the manipulated variable MV is used as the manipulated variable MV_f for feedforward control, it is in principle possible to realize feedback control (PID control) that follows the reference set value SP even for a controlled object with strongly nonlinear characteristics.

[0020] Incidentally, the execution of simulations using the control target model and the storage of numerous time-series data sets assuming various conditions should be performed by an industrial personal computer (IPC) or other device at a higher level than a PID controller (a local controller with limited calculation functions for the purpose of continued stability) such as a temperature regulator, making it necessary to distribute the placement of each function block.

[0021] Here, when obtaining time series data of the controlled variable PV and time series data of the manipulated variable MV close to an ideal control response by a simulation or the like, PID control is not necessarily used, so for example, a simple combination of step inputs of the manipulated variable MV may be used. In that case, the combination with PID control, which is a control theory method, may be incompatible, and the PID control for compensating for the excess or deficiency of the feedforward control may cause unnecessary fluctuations in the manipulated variable MV. The inventor then came to the conclusion that a configuration in which the feedforward control waveform (a function formula with a continuous second-order differential) that is compatible with PID control even if it does not match the time series data of the manipulated variable MV close to an ideal control response is suitable is suitable. Based on this configuration, the combination of a PID controller (such as a temperature controller) and an industrial PC is connected based on control theory, so that the instrumentation can be improved to one that is easy to fine-tune based on control theory while dealing with strongly nonlinear characteristics.

[0022] [Principle 2] The feedforward control operation volume MV_f is approximately replaced with a feedforward control waveform (a transfer function whose second-order derivative is continuous) that is compatible with PID control, so by combining it with PID control and visualizing and quantifying the feedback control operation volume MV_b (the difference between the control volume MV and the operation volume MV_f) which corresponds to the amount by which the PID control corrects the operation volume MV_f, an index for fine adjustment can be obtained. The relationship between the index and fine adjustment know-how can be expected to be obtained empirically through repeated simulations and actual control.

[0023] [Example] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. This embodiment corresponds to the principle of the invention, but will be described as a configuration in which, in addition to the basic configuration, a function that does not impede stable continuity and is rather preferable is added.

[0024] 1 is a block diagram showing the configuration of a control system according to this embodiment. The control system is composed of an industrial PC 1 (host device) and a PID controller 2. The industrial PC 1 includes an ideal response generating unit 10 that generates time series data of a controlled variable PV and time series data of a manipulated variable MV corresponding to an ideal control response, a controlled variable change storage unit 11 that stores the time series data of the controlled variable PV, a manipulated variable change storage unit 12 that stores the time series data of the manipulated variable MV, a function equation approximation substitution unit 13 that approximates the time series data of the manipulated variable by a function whose second-order derivative is continuous, a controlled variable output unit 14 that, at a specified timing, sequentially extracts data of the controlled variable PV for each control period from the time series data stored in the storage unit 11 and sequentially transmits the data to the PID controller 2, and a function equation approximation substitution unit 15 that, at a specified timing, approximates the time series data of the controlled variable PV by a function whose second-order derivative is continuous. the control variable function output unit 15 that transmits to the PID controller 2 the parameter values ​​of the approximation equation obtained by the parameter value output unit 13; a control variable upper limit value output unit 16 that transmits to the PID controller 2 a parameter value for prescribing a control variable upper limit value OH_x assuming an error range of the approximation value of the control variable MV for each control cycle calculated from the parameter values ​​of the approximation equation at a specified timing; and a control variable lower limit value output unit 17 that transmits to the PID controller 2 a parameter value for prescribing a control variable lower limit value OL_x assuming an error range of the approximation value of the control variable MV for each control cycle calculated from the parameter values ​​of the approximation equation at a specified timing.

[0025] The control amount change memory unit 11 and the operation amount change memory unit 12 constitute a memory unit 18, and the control amount output unit 14, the operation amount function output unit 15, the operation amount upper limit value output unit 16, and the operation amount lower limit value output unit 17 constitute a transmission unit 19.

[0026] The PID controller 2 includes a set value input unit 20 that receives the controlled variable PV transmitted from the industrial PC 1 as a new value of the reference set value SP_r, a manipulated variable function input unit 21 that receives the parameter value of the approximation equation transmitted from the industrial PC 1 as the parameter value of the approximation equation of the feedforward control controlled variable MV_f, a manipulated variable upper limit value input unit 22 that receives the parameter value of the controlled variable upper limit value OH_x transmitted from the industrial PC 1, a manipulated variable lower limit value input unit 23 that receives the parameter value of the controlled variable lower limit value OL_x transmitted from the industrial PC 1, a controlled variable acquisition unit 24 that acquires the measured value of the controlled variable PV, and performs PID calculations using the reference set value SP_r and the measured value of the controlled variable PV as inputs to obtain a feedback control controlled variable MV_b (first controlled variable). the control system includes a feedback calculation unit 25 that calculates a feedforward control operation amount MV_f based on the parameter values ​​of the received approximation equation and adds the feedforward control operation amount MV_f to the feedback control operation amount MV_b to calculate a operation amount MV_x' (second operation amount), a limit processing unit 27 that outputs a operation amount MV (third operation amount) obtained by limiting the operation amount MV_x' calculated by the feedforward addition unit 26 to a value within the range between an operation amount upper limit value OH_x and an operation amount lower limit value OL_x, an operation amount output unit 28 that outputs the operation amount MV obtained by the limit processing unit 27 to the controlled object, and an operation amount correction amount output unit 29 that transmits data of the feedback control operation amount MV_b.

[0027] The set value input section 20 , the manipulated variable function input section 21 , the manipulated variable upper limit value input section 22 , and the manipulated variable lower limit value input section 23 constitute a receiving section 30 . The transmitter 19 and the receiver 30 may transmit and receive data via wired communication or wireless communication. The present invention is not limited to a specific communication standard, and any appropriate communication standard may be appropriately selected to realize communication between the industrial PC 1 and the PID controller 2.

[0028] Fig. 2 is a flow chart for explaining the operation of the industrial PC 1. The ideal response generating unit 10 of the industrial PC 1 generates data on the time change of the controlled variable PV corresponding to the ideal control response and data on the time change of the manipulated variable MV output to the controlled object at the time of this control response (Fig. 2, step S100). The ideal response generating unit 10 may obtain the change of the controlled variable PV and the change of the manipulated variable MV close to the ideal control response by searching for an optimal solution in a simulation using a controlled object model that may include a strongly nonlinear characteristic, or by issuing an automatic trial command for control using an actual controlled object. In the present invention, the method of generating data by the ideal response generating unit 10 is not particularly limited.

[0029] The ideal response generator 10 generates time series data of the controlled variable PV and time series data of the manipulated variable MV for each preset control condition. The control condition usually refers to the condition of changing the set value SP (the set value SP before the change and the set value SP after the change) assumed in the temperature rise control using, for example, the PID controller 2 (temperature regulator).

[0030] The generated time series data of the controlled variable PV and the time series data of the manipulated variable MV each have time information (time stamp) added, with the start time of the control action being time 0. The time interval of the generated time series data is preferably the same as the control period of the PID controller 2, but may be a time interval shorter than the control period.

[0031] The controlled variable change storage unit 11 stores a set of time-series data of the controlled variable PV generated for each control condition by the ideal response generating unit 10 (step S101 in FIG. 2). An ID corresponding to the control condition is added to the data set generated for each control condition by the ideal response generating unit 10. The controlled variable change storage unit 11 stores this ID together with the data set.

[0032] Meanwhile, the manipulated variable change storage unit 12 stores a set of time-series data of the manipulated variable MV generated for each control condition by the ideal response generator 10 (step S102 in FIG. 2). As described above, an ID corresponding to the control condition is added to the data set generated for each control condition by the ideal response generator 10. The manipulated variable change storage unit 12 stores this ID together with the data set.

[0033] The ideal response generator 10 must end data generation when a specified end time has elapsed from the point in time when the controlled variable PV stabilizes after the set value SP is changed. The reason for this is that if data generation continues, the storage capacity of the controlled variable change storage unit 11 and the manipulated variable change storage unit 12 will become enormous.

[0034] Next, the function formula approximation replacement unit 13 approximates the time series data set of the manipulated variable MV stored in the manipulated variable change storage unit 12 by a function whose second-order differential is continuous (FIG. 2, step S103). As the approximation formula, formulas (1) to (3) disclosed in JP 2021-124864 A are preferable. MV_X1 =[Kx1 / {(1+ATfs)(1+(2.0-A)Tfs)}]FF_X (1) MV_X2 =[Kx2s / {(1+ATfs)(1+(2.0-A)Tfs)}]FF_X (2) MV_f = MV_X1 + MV_X2 (3)

[0035] In the transfer function expressions (1) and (2), MV_X1 and MV_X2 are the feedforward amounts, Tf is a parameter (time constant) that specifies the time it takes for the feedforward amounts MV_X1 and MV_X2 to gradually converge, and A is a coefficient (A is a real number greater than 0) that adjusts the balance of the time constant Tf. The recommended value for coefficient A is 1.0. FF_X is a trigger variable that becomes 0 (insignificant value) before the manipulated variable MV to be approximated rises, and becomes 1 (significant value) when the manipulated variable MV to be approximated rises.

[0036] Kx1 is a parameter that defines the feedforward amount MV_X1 for a step-like change in the manipulated variable MV to be approximated. According to equation (1), the feedforward amount MV_X1 gradually converges from zero to the value of the parameter Kx1. Kx2 is a parameter that defines the feedforward amount MV_X2 for an impulse-like change in the manipulated variable MV to be approximated. According to equation (2), the feedforward amount MV_X2 gradually converges to zero after its total amount (the integrated value for each control cycle) approaches the value of the parameter Kx2. MV_f in equation (3) is an approximation value of the manipulated variable MV. On the PID controller 2 side described later, MV_f is called the feedforward control manipulated variable.

[0037] An example of the changes in the feedforward amounts MV_X1 and MV_X2 is shown in Fig. 3. In the approximation results shown in Fig. 3, the parameter Kx1 was 20.0, the parameter Kx2 was 2000.0, and the time constant Tf was 15.0 seconds. The functional equation approximation substitution unit 13 performs the above-mentioned approximation for each data set of the manipulated variable MV generated for each control condition.

[0038] Next, at a specified timing (YES in step S104 in FIG. 2), the controlled variable output unit 14 selects a specified data set from the time series data sets of the controlled variable PV stored in the controlled variable change storage unit 11. The controlled variable output unit 14 sequentially extracts data of the controlled variable PV for each control cycle of the PID controller 2 from the selected data set and sequentially transmits the data to the PID controller 2. At this time, the controlled variable output unit 14 transmits the data of the controlled variable PV for each control cycle so that the time interval indicated by the time stamp value of the data sequentially transmitted by the controlled variable output unit 14 matches the control cycle of the PID controller 2 (step S105 in FIG. 2).

[0039] At a specified timing, the manipulated variable function output unit 15 selects an approximation equation determined for a specified data set of the manipulated variable MV from among the approximation equations determined by the function equation approximation replacement unit 13. The manipulated variable function output unit 15 transmits the parameter values ​​of the selected approximation equation to the PID controller 2 (Step S106 in FIG. 2).

[0040] The parameter values ​​to be transmitted include Tf, Kx1, Kx2, and A, as well as the time Tx from the start of the control operation until the trigger variable FF_X changes from 0 to 1. However, if the coefficient A is registered in advance in the PID controller 2 as a fixed value, the coefficient A does not need to be transmitted. Also, if the time Tx is a fixed value, that is, the time at which the data of the manipulated variable MV rises is always the same, and the time Tx is registered in advance in the PID controller 2 as a fixed value, the time Tx does not need to be transmitted.

[0041] At a specified timing, the manipulated variable upper limit output unit 16 transmits to the PID controller 2 a parameter value for prescribing the manipulated variable upper limit value OH_x assuming an error range of the approximation value of the manipulated variable MV for each control period calculated from the parameter value transmitted by the manipulated variable function output unit 15 (step S107 in FIG. 2). At this time, the manipulated variable upper limit output unit 16 transmits to the PID controller 2 a parameter value for prescribing the manipulated variable upper limit value OH_x for each control period so that the time indicated by the time stamp value (time stamp value of the data of the manipulated variable MV to be approximated) added to the parameter value transmitted by itself is the same as the time indicated by the time stamp value of the data of the controlled variable PV transmitted by the controlled variable output unit 14. As a result, the interval between the times indicated by the time stamp values ​​of the parameters transmitted sequentially by the manipulated variable upper limit output unit 16 matches the control period of the PID controller 2. In the simplest processing, an upward margin ΔOHx centered on the approximation value of the manipulated variable MV for each control period may be used as a parameter for prescribing the manipulated variable upper limit value OH_x.

[0042] At a specified timing, the manipulated variable lower limit output unit 17 transmits to the PID controller 2 a parameter value for prescribing the manipulated variable lower limit value OL_x assuming an error range of the approximation value of the manipulated variable MV for each control cycle calculated from the parameter value transmitted by the manipulated variable function output unit 15 (step S108 in FIG. 2). At this time, the manipulated variable lower limit output unit 17 transmits to the PID controller 2 a parameter value for prescribing the manipulated variable lower limit value OL_x for each control cycle so that the time indicated by the time stamp value (time stamp value of the data of the manipulated variable MV to be approximated) added to the parameter value transmitted by itself is the same as the time indicated by the time stamp value of the data of the controlled variable PV transmitted by the controlled variable output unit 14. As a result, the interval between the times indicated by the time stamp values ​​of the parameters transmitted sequentially by the manipulated variable lower limit output unit 17 matches the control cycle of the PID controller 2. In the simplest processing, a downward margin ΔOLx centered on the approximation value of the manipulated variable MV for each control cycle may be used as a parameter for prescribing the manipulated variable lower limit value OL_x.

[0043] It is not necessary to set the upward margin ΔOHx and the downward margin ΔOLx to fixed values, and as described below, the upward margin ΔOHx and the downward margin ΔOLx may each be changed according to the elapsed time from the time when the set value SP was changed.

[0044] The controlled variable output unit 14 repeatedly executes the process of step S105 until the specified data set stored in the controlled variable change storage unit 11 is completely transmitted (YES in step S109 in FIG. 2). The controlled variable upper limit value output unit 16 and the controlled variable lower limit value output unit 17 repeatedly execute the processes of steps S107 and S108. The controlled variable upper limit value output unit 16 and the controlled variable lower limit value output unit 17 similarly end their processes when the controlled variable output unit 14 ends its process (i.e., when the end of the data set of the controlled variable MV to be approximated is reached). In the example of FIG. 2, it is described that the parameter values ​​of the approximation formula are also repeatedly transmitted, but the parameter values ​​of the approximation formula only need to be transmitted once.

[0045] It is desirable for the controlled variable PV, the parameter value of the manipulated variable upper limit value OH_x, and the parameter value of the manipulated variable lower limit value OL_x, which require data synchronization, i.e., the same time stamp value, to arrive at the PID controller 2 at the same time, but a time lag in arrival is acceptable. If this time lag is a small amount of time relative to the control period (e.g., 1 second) of the PID controller 2, there is no practical problem. This completes the operation on the industrial PC 1 side, and the industrial PC 1 waits until the next specified timing.

[0046] Here, the above-mentioned prescribed timing and prescribed data set will be explained. For example, when an operator of the industrial PC 1 manually changes the set value SP of the PID controller 2, the timing when the operator instructs to change the set value SP becomes the prescribed timing, and the data set (control conditions) instructed by the operator becomes the prescribed data set.

[0047] Furthermore, for example, when temperature control of a heating furnace or the like is automatically performed according to predetermined schedule information, the timing of changing the set value SP determined by the schedule information becomes the specified timing, and the data set (control conditions) determined by the schedule information becomes the specified data set.

[0048] Fig. 4 is a flowchart explaining the operation of the PID controller 2. The set value input unit 20 of the PID controller 2 receives the controlled variable PV transmitted from the industrial PC 1 as a new value of the reference set value SP_r (step S200 in Fig. 4). The simplest processing is to receive data of one controlled variable PV for each control cycle of the PID controller 2.

[0049] The manipulated variable function input unit 21 receives the parameter values ​​of the approximation equation transmitted from the industrial PC 1 as the parameter values ​​of the approximation equation of the feedforward control manipulated variable MV_f (step S201 in FIG. 4).

[0050] The operation volume upper limit value input unit 22 receives the parameter value of the operation volume upper limit value OH_x transmitted from the industrial PC 1 as a new value to be used in the limit processing unit 27 (step S202 in FIG. 4). The operation volume lower limit value input unit 23 receives the parameter value of the operation volume lower limit value OL_x transmitted from the industrial PC 1 as a new value to be used in the limit processing unit 27 (step S203 in FIG. 4).

[0051] The controlled variable acquisition unit 24 acquires a measured value of the controlled variable PV (Step S204 in FIG. 4). In the case of temperature control using the PID controller 2 (temperature regulator), the value of the controlled variable PV is acquired from a temperature sensor.

[0052] Next, the feedback calculation unit 25 receives the reference set value SP_r received by the set value input unit 20 and the measured value of the controlled variable PV acquired by the controlled variable acquisition unit 24 as inputs, and performs PID calculation to calculate a feedback control manipulated variable MV_b so that the measured value of the controlled variable PV coincides with the reference set value SP_r. Specifically, when performing a speed-type PID calculation such as the transfer function formula shown in equation (4), the feedback calculation unit 25 calculates a manipulated variable change width ΔMV_b (step S205 in FIG. 4). ΔMV_b=Kp{ΔEr+(1 / Ti)Er+TdΔ 2 Er} ···(4)

[0053] In formula (4), Er is the control deviation, which is the difference SP_r-PV between the reference set value SP_r and the measured value of the controlled variable PV. ΔEr is the first-order difference of the control deviation Er (the amount of change in the deviation Er per one control cycle), Δ 2 Er is the second difference of the control deviation Er (the amount of change in the deviation Er per control cycle), Kp is the proportional gain of the PID parameters, Ti is the integral time of the PID parameters, and Td is the differential time of the PID parameters. Note that the proportional gain Kp has a relationship with the proportional band Pb of Kp=100 / Pb.

[0054] Then, the feedback calculation unit 25 adds the control input MV_x calculated by the feedforward addition unit 26 one control cycle ago (the value of MV_x' one control cycle ago, described later) and the control input change range ΔMV_b to obtain the feedback control control input MV_b (step S206 in FIG. 4), as shown in equation (5) (FIG. 4). MV_b = MV_x + ΔMV_b (5)

[0055] In addition, the feedback calculation unit 25 may be provided with a general additional function such as anti-reset windup processing (processing for preventing unnecessary accumulation of integral operations).

[0056] The feedforward adder 26 calculates the feedforward control manipulated variable MV_f using equations (1) to (3) based on the parameter values ​​received by the manipulated variable function input unit 21, and adds the feedforward control manipulated variable MV_f to the feedback control manipulated variable MV_b to calculate the manipulated variable MV_x' (step S207 in FIG. 4). The time used in calculating the feedforward control manipulated variable MV_f is the elapsed time (a time that is an integer multiple of the control period) from the point at which reception of the control variable PV, the parameter value of the manipulated variable upper limit value OH_x, and the parameter value of the manipulated variable lower limit value OL_x began (the point at which the control action began).

[0057] The parameter values ​​received by the manipulated variable function input unit 21 include Tf, Kx1, Kx2, A, and Tx. The time Tx indicates the time from the start of reception (the start of the control action) until the trigger variable FF_X changes from 0 to 1. Therefore, the feedforward adder 26 changes the trigger variable FF_X from 0 to 1 when the elapsed time from the start of reception (the start of the control action) reaches Tx.

[0058] As described above, when the coefficient A is registered in advance in the PID controller 2 as a fixed value, the feedforward addition unit 26 may use the registered value of the coefficient A. Similarly, when the time Tx is registered in advance in the PID controller 2 as a fixed value, the feedforward addition unit 26 may use the registered value of the time Tx.

[0059] When the feedback calculation unit 25 performs a speed-type PID calculation, the feedforward adder 26 calculates the difference between the feedforward control operation amount MV_f of the current control cycle calculated by the feedforward adder 26 and the feedforward control operation amount MV_f of the previous control cycle as a change width ΔMV_f. Then, the feedforward adder 26 adds the change width ΔMV_f to the feedback control operation amount MV_b as shown in equation (6) to calculate a new value of the operation amount MV_x'. MV_x' = MV_b + ΔMV_f (6)

[0060] The limit processing unit 27 calculates the operation volume upper limit value OH_x for the current control cycle as shown in equation (7) based on the feedforward control operation volume MV_f for the current control cycle calculated by the feedforward addition unit 26 and the parameter value of the operation volume upper limit value OH_x received by the operation volume upper limit value input unit 22 (step S208 in FIG. 4). OH_x = MV_f + ΔOHx (7)

[0061] In this embodiment, since the upward margin ΔOHx is used as the parameter value of the manipulated variable upper limit value OH_x, the value obtained by adding the upward margin ΔOHx to the feedforward control manipulated variable MV_f is set to the manipulated variable upper limit value OH_x. In addition, the limit processing unit 27 calculates the operation volume lower limit value OL_x for the current control cycle as shown in equation (8) based on the feedforward control operation volume MV_f for the current control cycle calculated by the feedforward addition unit 26 and the parameter value of the operation volume lower limit value OL_x received by the operation volume lower limit value input unit 23 (step S209 in FIG. 4). OL_x = MV_f - ΔOLx (8)

[0062] In this embodiment, the downward margin ΔOLx is used as the parameter value of the manipulated variable lower limit value OL_x, so the value obtained by subtracting the downward margin ΔOLx from the feedforward control manipulated variable MV_f is set to the manipulated variable lower limit value OL_x.

[0063] The limit processing unit 27 outputs an operation amount MV obtained by limiting the operation amount MV_x' calculated by the feed-forward addition unit 26 to a value that is equal to or greater than the lower limit value OL_x of the operation amount and equal to or less than the upper limit value OH_x of the operation amount in the current control cycle (step S210 in FIG. 4). That is, when the operation amount MV_x' is smaller than the lower limit value OL_x of the operation amount (MV_x' < OL_x), the limit processing unit 27 sets the operation amount MV = OL_x, and when the operation amount MV_x' is larger than the upper limit value OH_x of the operation amount (MV_x' > OH_x), the operation amount MV = OH_x, and when the operation amount MV_x' is equal to or greater than the lower limit value OL_x of the operation amount and equal to or less than the upper limit value OH_x of the operation amount (OL_x ≤ MV_x' ≤ OH_x), the limit processing is performed such that the operation amount MV = MV_x'.

[0064] Normally, limit processing of the standard upper limit value of 100% and the lower limit value of 0% of the operation amount of the thermostat is further executed. That is, when the operation amount MV is smaller than the lower limit value of 0% of the operation amount, the limit processing unit 27 sets the operation amount MV to 0%, and when the operation amount MV is larger than the upper limit value of 100% of the operation amount, the operation amount MV is set to 100%.

[0065] The operation amount output unit 28 outputs the operation amount MV that has been subjected to limit processing by the limit processing unit 27 to the control target (step S211 in FIG. 4). The output destination of the operation amount MV is an operation unit (not shown) such as a heater or a valve. In the case of a heater, the actual output destination of the operation amount MV is a power regulator (not shown) that supplies power to the heater.

[0066] The operation amount correction amount output unit 29 transmits the feedback control operation amount MV_b (the difference between the operation amount MV as the control result and the feed-forward control operation amount MV_f) to the outside (step S212 in FIG. 4). As the output destination of the feedback control operation amount MV_b, for example, there is an industrial PC1. As a result, time-series data of the feedback control operation amount MV_b is stored in the industrial PC1, and this time-series data can be displayed.

[0067] The PID controller 2 executes the processes of steps S200 to S212 for each control cycle until the control is ended, for example, by a command from an operator (YES in step S213 in FIG. 4).

[0068] However, the set value input unit 20, the manipulated variable upper limit input unit 22, and the manipulated variable lower limit input unit 23 stop updating the reference set value SP_r and the parameter values ​​of the manipulated variable upper limit value OH_x and the manipulated variable lower limit value OL_x (step S215 in FIG. 4) when a certain duration has elapsed since the measured value of the controlled variable PV stabilized (YES in step S214 in FIG. 4). Also, the feedforward adder 26 stops updating the feedforward control manipulated variable MV_f (step S215).

[0069] As a result, the reference set value SP_r, the feedforward control manipulated variable MV_f, the manipulated variable upper limit value OH_x, and the manipulated variable lower limit value OL_x are each fixed to the value of one control cycle before. The above durations must be set so that updates of the reference set value SP_r, the feedforward control manipulated variable MV_f, the manipulated variable upper limit value OH_x, and the manipulated variable lower limit value OL_x stop before data transmission from the industrial PC 1 ends.

[0070] Thereafter, the processes of steps S204 to S212 are executed every control cycle until the next specified timing occurs and the processes of steps S200 to S203 are resumed.

[0071] In this embodiment, the feedback control operation amount MV_b is transmitted to the outside each time it is output from the feedback calculation unit 25. However, the time series data of the feedback control operation amount MV_b stored in the operation amount correction amount output unit 29 may be transmitted all at once after the updating of the reference set value SP_r, the feedforward control operation amount MV_f, the operation amount upper limit value OH_x, and the operation amount lower limit value OL_x has stopped, or after a series of control operations has been completed.

[0072] Next, the effect of this embodiment will be described with reference to an example (simulation) of application to a controlled object with strongly nonlinear characteristics shown in Fig. 23. Here, the ideal response generating unit 10 generates time series data of the controlled variable PV and time series data of the manipulated variable MV that correspond to an ideal control response by a simulation using a controlled object model.

[0073] If the nonlinear characteristic of FIG. 23 is modeled, the manipulated variable MV in the settled state after the temperature rise can be obtained from the model for the temperature rise control shown in FIG. 24 to FIG. 26, so simple data such as those shown in FIG. 5 to FIG. 7 can be generated. FIG. 5 shows the change in the controlled variable PV (temperature) and the change in the manipulated variable MV corresponding to the ideal control response when the temperature is raised from 50°C to 150°C as shown in FIG. 24. FIG. 6 shows the change in the controlled variable PV and the change in the manipulated variable MV corresponding to the ideal control response when the temperature is raised from 50°C to 250°C as shown in FIG. 25. FIG. 7 shows the change in the controlled variable PV and the change in the manipulated variable MV corresponding to the ideal control response when the temperature is raised from 50°C to 350°C as shown in FIG. 26.

[0074] The controlled variable change storage unit 11 stores a set of time series data of the controlled variable PV generated for each control condition by the ideal response generation unit 10. The manipulated variable change storage unit 12 stores a set of time series data of the manipulated variable MV generated for each control condition by the ideal response generation unit 10. An ID corresponding to the control condition is added to the data set generated for each control condition by the ideal response generation unit 10. In the example of Figs. 5 to 7, different IDs are assigned to the data set when the temperature is increased from 50°C to 150°C, the data set when the temperature is increased from 50°C to 250°C, and the data set when the temperature is increased from 50°C to 350°C. 5 to 7, the change in the set value SP is also shown for convenience, but it is not necessary to store the set value SP.

[0075] Here, we will explain practical problems when the changes in the manipulated variable MV shown in Figures 5 to 7 are performed only by feedforward control, that is, when not combined with the feedback control of the PID controller 2. The strongly nonlinear characteristics of the controlled object are generally characteristics that appear when several types of complex characteristics overlap, and do not involve high-precision reproducibility. Therefore, Figures 8 to 10 show the results of performing only feedforward control with a 3% error between the model and the actual object.

[0076] Fig. 8 shows the results of only executing feedforward control when the temperature is raised from 50°C to 150°C. Fig. 9 shows the results of only executing feedforward control when the temperature is raised from 50°C to 250°C. Fig. 10 shows the results of only executing feedforward control when the temperature is raised from 50°C to 350°C. When only feedforward control is executed, an error occurs in the manipulated variable MV in the settled state after the temperature is raised, and it can be seen that an offset remains in the set value SP and the controlled variable PV, as shown in Figs. 8 to 10.

[0077] Next, a case where this embodiment is applied will be described. An important feature of this embodiment is that a data set of an ideal control response is stored in the industrial PC 1, and data of the controlled variable PV is transmitted from the upper side as data of the reference set value SP_r of the PID controller 2. Another important feature is that, as shown in Fig. 3, the change in the manipulated variable MV corresponding to the ideal control response is approximated by a function whose second-order derivative is continuous, and the parameter value of the approximation formula is transmitted from the upper side as the parameter value of the feedforward control manipulated variable MV_f.

[0078] In the following, a case where the temperature is increased from 50°C to 250°C is shown as a representative application example. The manipulated variable MV equivalent to the ideal control response when the temperature is increased from 50°C to 250°C shown in Fig. 6 is approximated by equations (1) to (3) to show the manipulated variable MV_f in Fig. 11. The approximated MV_f is a waveform that is continuous even at second-order differentials and above. This approximation process is obtained by automatically searching for the values ​​of the parameters Tf, Kx1, Kx2, and Tx in the industrial PC 1 so that the error between the manipulated variable MV equivalent to the ideal control response and the manipulated variable MV_f is minimized (coefficient A is a fixed value).

[0079] In the example of FIG. 11, the manipulated variable MV corresponding to the ideal control response maintains a value of 90% for 50 seconds, and then maintains a constant value of 82%. As a result of the automatic search, the time constant Tf is 70 seconds, the parameter Kx1 is 82, the parameter Kx2 is 2400, and the time Tx is 100 seconds. As mentioned above, the coefficient A is 1.0. However, the parameter values ​​may be obtained by repeating a simulation including human operation. By performing the approximation processing with a high load on the industrial PC 1, the PID controller 2 can continue PID control in parallel with the approximation processing.

[0080] Fig. 12 shows a simulation result of the control according to this embodiment based on the approximation result of Fig. 11. Fig. 13 shows a comparison result between the feedforward control manipulated variable MV_f in Fig. 12 and the manipulated variable MV actually output from the manipulated variable output unit 28. The difference between the feedforward control manipulated variable MV_f and the manipulated variable MV corresponds to the feedback control manipulated variable MV_b by PID control. Since the feedforward control manipulated variable MV_f containing an error when approximating the time series data of the manipulated variable MV corresponding to an ideal control response is given, the response of Fig. 11 is not completely reproduced, but it can be seen that a change in the manipulated variable MV that is continuous like a control theory-based change can be obtained.

[0081] Regarding feedback control, as shown in Figs. 24 to 26, unnecessary fluctuations in the manipulated variable MV occur depending on the target temperature, so it is preferable to regulate it using the manipulated variable upper limit value OH_x and the manipulated variable lower limit value OL_x.

[0082] Fig. 14 is a diagram showing the results of application under the same conditions as in Fig. 12 when a change occurs that shortens the process time constant of the controlled object by about 30%. Fig. 15 shows the results of comparison between the feedforward control manipulated variable MV_f in Fig. 14 and the manipulated variable MV actually output from the manipulated variable output unit 28. Fig. 16 shows the change in the difference between the feedforward control manipulated variable MV_f in Fig. 15 and the manipulated variable MV actually output from the manipulated variable output unit 28. It becomes possible to consider that the increase in the difference between the feedforward control manipulated variable MV_f and the manipulated variable MV to the positive side in the latter half of the transient state is a characteristic of the shortening of the process time constant.

[0083] Fig. 17 is a diagram showing the results of application under the same conditions as in Fig. 12 when a change occurs that lengthens the process dead time of the controlled object by about 40%. Fig. 18 shows the results of comparison between the feedforward control manipulated variable MV_f in Fig. 17 and the manipulated variable MV actually output from the manipulated variable output unit 28. Fig. 19 shows the change in the difference between the feedforward control manipulated variable MV_f in Fig. 18 and the manipulated variable MV actually output from the manipulated variable output unit 28. It becomes possible to consider that the increase in the difference between the feedforward control manipulated variable MV_f and the manipulated variable MV to the negative side in the first half of the transient state is a characteristic of the extension of the process dead time.

[0084] In the present invention, the limit processing unit 27 is not an essential component. When the limit processing unit 27 is not provided, the operation amount output unit 28 outputs the operation amount MV_x' calculated by the feedforward addition unit 26 to the control target. When the limit processing unit 27 is not provided, it is not necessary to transmit the parameter value of the operation amount upper limit value OH_x and the parameter value of the operation amount lower limit value OL_x from the industrial PC 1.

[0085] The industrial PC 1 and the PID controller 2 described in this embodiment can each be realized by a computer equipped with a CPU (Central Processing Unit), a storage device, and an interface, and a program that controls these hardware resources. An example of the configuration of this computer is shown in FIG.

[0086] The computer includes a CPU 200, a storage device 201, and an interface device (I / F) 202. In the case of the industrial PC 1, the I / F 202 is connected to hardware of a communication circuit for communication with the PID controller 2, etc. In the case of the PID controller 2, the I / F 202 is connected to a sensor that measures the controlled variable PV, hardware of a communication circuit for communication with the industrial PC 1, a power regulator, etc. In such a computer, a program for realizing the control method of the present invention is stored in the storage device 201. The CPU 200 of each of the industrial PC 1 and the PID controller 2 executes the processing described in this embodiment according to the program stored in the storage device 201. [Industrial Applicability]

[0087] The present invention can be applied to a control system. [Explanation of symbols]

[0088] 1...industrial PC, 2...PID controller, 10...ideal response generation unit, 11...controlled variable change memory unit, 12...operated variable change memory unit, 13...function formula approximation replacement unit, 14...controlled variable output unit, 15...operated variable function output unit, 16...operated variable upper limit value output unit, 17...operated variable lower limit value output unit, 18...memory unit, 19...transmitting unit, 20...set value input unit, 21...operated variable function input unit, 22...operated variable upper limit value input unit, 23...operated variable lower limit value input unit, 24...controlled variable acquisition unit, 25...feedback calculation unit, 26...feedforward addition unit, 27...limit processing unit, 28...operated variable output unit, 29...operated variable correction variable output unit, 30...receiving unit.

Claims

1. It is composed of a host device and a PID controller, The host device is an ideal response generating unit configured to generate time series data of a controlled variable and time series data of a manipulated variable corresponding to an ideal control response; a storage unit configured to store time series data of the controlled variable and time series data of the manipulated variable; a functional expression approximation substitution unit configured to approximate the time series data of the manipulated variable stored in the storage unit by a function whose second-order derivative is continuous; a transmission unit configured to sequentially retrieve control amount data for each control period from the time-series data stored in the storage unit and sequentially transmit the data to the PID controller at a specified timing, and to transmit parameter values ​​of the approximation equation determined by the function equation approximation replacement unit to the PID controller, The PID controller is a receiving unit configured to receive the control amount transmitted from the host device as a new value of a reference set value, and to receive a parameter value of an approximation equation transmitted from the host device as a parameter value of an approximation equation of a feedforward control manipulated variable; A control variable acquisition unit configured to acquire a measurement value of a control variable; a feedback calculation unit configured to calculate a first manipulated variable by performing a PID calculation using the reference set value and the measured value of the controlled variable as input; a feedforward adder configured to calculate a feedforward control operation amount based on the parameter value received by the receiver and to add the feedforward control operation amount to the first operation amount to calculate a second operation amount; a manipulated variable output unit configured to output the second manipulated variable calculated by the feedforward adder to a controlled object.

2. 2. The control system of claim 1, the PID controller further includes a limit processing unit configured to output a third manipulated variable obtained by limiting the second manipulated variable calculated by the feedforward addition unit to a value within a range between an manipulated variable upper limit value and an manipulated variable lower limit value, the transmission unit transmits, at the specified timing, a parameter value for the manipulated variable upper limit value and a parameter value for the manipulated variable lower limit value, which are calculated based on the parameter value transmitted by the transmission unit itself and assume an error range of an approximation value of the manipulated variable for each control period, together with the data of the controlled variable and the parameter value of the approximation formula, to the PID controller; the receiving unit receives the parameter value of the operation volume upper limit value and the parameter value of the operation volume lower limit value transmitted from the host device as new values ​​to be used in the limit processing unit; the limit processing unit calculates the operation volume upper limit value based on the feedforward control operation volume and a parameter value of the operation volume upper limit value, and calculates the operation volume lower limit value based on the feedforward control operation volume and the parameter value of the operation volume lower limit value; The control system according to claim 1, wherein the manipulated variable output unit outputs the third manipulated variable to a control target, instead of outputting the second manipulated variable to the control target.

3. 3. The control system of claim 2, the parameter value of the operation volume upper limit value is an upward margin value, the parameter value of the manipulated variable lower limit is a downward margin value, the limit processing unit sets a value obtained by adding the upward side margin value to the feedforward control operation amount as the operation amount upper limit value, and sets a value obtained by subtracting the downward side margin value from the feedforward control operation amount as the operation amount lower limit value.

4. 2. The control system of claim 1, The control system according to claim 1, further comprising a manipulated variable correction output unit configured to transmit time series data of the first manipulated variable to an outside.

5. A control system according to any one of claims 1 to 4, The ideal response generating unit generates time series data of a controlled variable and time series data of a manipulated variable corresponding to an ideal control response by utilizing a virtual controlled object model for reproducing the behavior of the controlled object on a computer.

6. A first step in which a host device generates time series data of a controlled variable and time series data of a manipulated variable corresponding to an ideal control response; a second step in which the host device stores time series data of the controlled variable and time series data of the manipulated variable; a third step in which the host device approximates the time series data of the manipulated variable stored in the second step by a function whose second derivative is continuous; a fourth step in which the host device sequentially extracts control amount data for each control period from the time series data stored in the second step and sequentially transmits the control amount data to the PID controller at a specified timing, and also transmits the parameter values ​​of the approximation equation obtained in the third step to the PID controller; a fifth step in which the PID controller receives the control amount transmitted from the host device as a new value of a reference set value and receives a parameter value of an approximation equation transmitted from the host device as a parameter value of an approximation equation of a feedforward control manipulated variable; a sixth step of the PID controller acquiring a measured value of a controlled variable; a seventh step in which the PID controller performs a PID calculation using the reference set value and the measured value of the controlled variable as inputs to calculate a first manipulated variable; an eighth step of the PID controller calculating a feedforward control manipulated variable based on the parameter value received in the fifth step, and adding the feedforward control manipulated variable to the first manipulated variable to calculate a second manipulated variable; and a ninth step of outputting the second manipulated variable calculated in the eighth step to a controlled object.

7. 7. The control method according to claim 6, The method further includes a tenth step of outputting a third manipulated variable obtained by limiting the second manipulated variable calculated in the eighth step to a value within a range between an upper manipulated variable limit value and a lower manipulated variable limit value, the fourth step includes a step of transmitting, at the specified timing, a parameter value for the manipulated variable upper limit value and a parameter value for the manipulated variable lower limit value, which are calculated based on a parameter value transmitted by the host device and assume an error range of an approximation value of the manipulated variable for each control cycle, together with data on the controlled variable and a parameter value of the approximation formula, to the PID controller; the fifth step includes a step of receiving the parameter value of the manipulated variable upper limit value and the parameter value of the manipulated variable lower limit value transmitted from the host device as new values ​​to be used in the tenth step; the tenth step includes a step of calculating the operation volume upper limit value based on the feedforward control operation volume and a parameter value of the operation volume upper limit value, and calculating the operation volume lower limit value based on the feedforward control operation volume and a parameter value of the operation volume lower limit value, The control method according to claim 9, further comprising the step of outputting the third manipulated variable to a control target, instead of outputting the second manipulated variable to the control target.

8. 8. The control method according to claim 7, the parameter value of the operation volume upper limit value is an upward margin value, the parameter value of the manipulated variable lower limit is a downward margin value, the tenth step including a step of setting a value obtained by adding the upward side margin value to the feedforward control operation amount as the operation amount upper limit value, and setting a value obtained by subtracting the downward side margin value from the feedforward control operation amount as the operation amount lower limit value.

9. 7. The control method according to claim 6, The control method further comprises an eleventh step of the PID controller transmitting time series data of the first manipulated variable to an outside.

10. 10. The control method according to claim 6, a control method characterized in that the first step includes a step of generating time series data of a controlled variable and time series data of a manipulated variable corresponding to an ideal control response by utilizing a virtual controlled object model for reproducing the behavior of the controlled object on a computer.

Images