Parameter determination device, parameter determination method, and parameter determination system

Abstract

To easily determine a control parameter suitable for actually measured data.SOLUTION: The parameter determination device 20 includes the acquisition unit 221 that acquires the input data u to the control target P and the output data y output by the control target P, the estimator that estimates the first signal including the disturbance acting on the control target P, and the reference model of the control target P. The control system includes a feedforward controller that outputs a second signal based on a target value of output data y, a feedback controller 13 that outputs a third signal based on a difference between the output data y and the target value, and a determination unit 222 that determines a control parameter of the feedback controller 13 by determining a minimum value of a cost function by inputting the input data u and the output data y acquired by an acquisition unit 221 to the cost function indicating a difference between the input data u and the virtual input.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present invention relates to a parameter determination device, a parameter determination method, and a parameter determination system. [Background technology]

[0002] The gain adjustment device of Patent Document 1 adjusts control parameters used in a two-degree-of-freedom control system based on actual measurement data acquired from a plant and target values, and adjusts the gain of the two-degree-of-freedom control system. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-46121 Summary of the Invention [Problem to be solved by the invention]

[0004] When adjusting the control parameters used in a model-reference two-degree-of-freedom control system based on actual measurement data obtained from the controlled object (plant), the gain of the feedback controller included in the two-degree-of-freedom control system can become extremely large, resulting in the problem of making it difficult to adjust the control parameters. This is due to the reference model for disturbance suppression performance, one of the reference models for the target response and one for disturbance suppression performance set by the designer of the two-degree-of-freedom control system. Furthermore, since two-degree-of-freedom control systems require adjustment of more parameters than fixed PID (Proportional Integral Differential) controllers, the parameters must be adjusted repeatedly.

[0005] The present invention has been made in view of these points, and has as its object to easily determine control parameters suitable for actual measurement data. [Means for solving the problem]

[0006] a feedforward controller that includes a reference model of the controlled object and outputs a second signal for calculating a virtual input corresponding to a target value of the output data; a feedback controller that outputs a third signal for calculating the virtual input based on a difference between the output data acquired by the acquisition unit and the target value; and a calculator that calculates, as the virtual input, a sum obtained by multiplying a subtraction value obtained by subtracting the first signal from the second signal by a predetermined coefficient and adding the third signal to the multiplied value; and a determiner that determines a control parameter of the feedback controller by inputting the input data and the output data acquired by the acquisition unit into a cost function indicating a difference between the input data and the virtual input acquired by the acquisition unit and finding a minimum value of the cost function.

[0007] The determination unit may determine, as the control parameters, a proportional gain, an integral gain, and a differential gain of a proportional unit, an integrator, and a differentiator, respectively, included in the feedback controller.

[0008] The determination unit may determine the control parameter of the feedback controller that outputs, as the third signal, a subtraction result obtained by subtracting a second calculated value of a second term including the proportional gain and a third calculated value of a third term including the differential gain from a first calculated value of a first term including the integral gain.

[0009] The feedback controller may include a first feedback controller that outputs a fourth signal for calculating the third signal based on the target value, and a second feedback controller that outputs the third signal based on the output data acquired by the acquisition unit and the fourth signal, and the determination unit may determine a first control parameter of the first feedback controller and a second control parameter of the second feedback controller.

[0010] A parameter determination method according to a second aspect of the present invention includes: an acquisition step executed by a computer to acquire, over a predetermined period, a plurality of pieces of input data for a controlled object and a plurality of pieces of output data output by the controlled object; an estimator that estimates and outputs a first signal including a disturbance acting on the controlled object based on the input data and the output data; a feedforward controller that includes a reference model of the controlled object and outputs a second signal for calculating a virtual input corresponding to the input data based on a target value of the output data; a feedback controller that outputs a third signal for calculating the virtual input based on a difference between the output data acquired in the acquisition step and the target value; and a calculator that calculates, as the virtual input, an added value obtained by multiplying a subtraction value obtained by subtracting the first signal from the second signal by a predetermined coefficient and then adding the third signal to the multiplied value; the input data and the output data acquired in the acquisition step to determine a minimum value of the cost function indicating a difference between the input data and the virtual input acquired in the acquisition step, thereby determining a control parameter of the feedback controller.

[0011] A parameter determination system according to a third aspect of the present invention is a parameter determination system comprising: a control system that calculates a virtual input corresponding to input data to a controlled object; and a parameter determination device that determines control parameters of the control system, wherein the control system comprises an estimator that estimates and outputs a first signal including a disturbance acting on the controlled object based on the input data to the controlled object and output data output by the controlled object; a feedforward controller that includes a reference model of the controlled object and outputs a second signal for calculating a virtual input corresponding to the input data based on a target value of the output data; and a parameter determination device that determines a control parameter of the control system based on a difference between the output data output by the controlled object and the target value. the parameter determination device has a feedback controller that outputs a third signal for calculating a force, and a calculator that calculates, as the virtual input, an added value obtained by multiplying a subtraction value obtained by subtracting the first signal from the second signal by a predetermined coefficient and then adding the third signal to the resulting multiplication value; and the parameter determination device has an acquisition unit that acquires, over a predetermined period of time, a plurality of pieces of input data to the controlled object and a plurality of pieces of output data output by the controlled object, and a determination unit that determines the control parameters of the feedback controller by inputting the input data and the output data acquired by the acquisition unit into a cost function of the control system that indicates the difference between the input data acquired by the acquisition unit and the virtual input, and finding the minimum value of the cost function. [Effects of the Invention]

[0012] The present invention has the effect of easily determining control parameters suitable for actual measurement data. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a diagram showing an overview of a parameter determination system 1 according to the present embodiment. [Figure 2] FIG. 1 is a diagram illustrating the configuration of an MFC system Z. [Figure 3] FIG. 2 is a diagram for explaining a reference model Md. [Figure 4] FIG. 1 is a diagram showing the configuration of a control system 10. [Figure 5] 5 shows an equivalent circuit of the control system 10 shown in FIG. [Figure 6] FIG. 2 is a diagram showing the configuration of a parameter determination device 20. [Figure 7] An example of a processing sequence in the parameter determination device 20 is shown. [Figure 8] FIG. 10 is a diagram showing a simulation result of vehicle yaw rate control. DETAILED DESCRIPTION OF THE INVENTION

[0014] <Overview of Parameter Determination System 1> FIG. 1 is a diagram showing an overview of a parameter determination system 1 according to this embodiment. The parameter determination system 1 shown in FIG. 1 includes a control system 10 and a parameter determination device 20. The parameter determination system 1 is a system for determining control parameters used when calculating an input signal u for controlling a control object P. The control object P is, for example, a vehicle, and the control parameters are the gains of a proportional unit, an integrator, and a differentiator included in the control system 10. As an example, the parameter determination system 1 determines a proportional gain K of a proportional unit used when calculating, as the input signal u, a steering angle for controlling the yaw rate (output signal y) of the vehicle. p , the integral gain of the integrator K i and the differential gain K of the differentiator d Determine.

[0015] The control system 10 is a system that calculates an input signal u based on an output signal y output by a controlled object P and a target value r of the output signal y. The control system 10 calculates a proportional gain K p , integral gain K i , differential gain K d are applied to the proportional controller, integrator, and differentiator, respectively, and model-free control (MFC) is performed to calculate the input signal u.

[0016] The parameter determination device 20 determines a control parameter based on an input signal u (hereinafter referred to as "input data u") input to the control object P and an output signal y (hereinafter referred to as "output data y") output by the control object P during a predetermined period. The predetermined period is, for example, 100 seconds. The parameter determination device 20 determines a proportional gain K that minimizes the output of a cost function indicating the difference between the input signal u (hereinafter referred to as "virtual input") calculated by the control system 10 and the input data u actually input to the control object P. p , integral gain K i , differential gain K d is determined as the control parameter.

[0017] The model-free control performed by the control system 10 is performed so as to reduce the difference between the output signal y and the target value r, and the minimization of the cost function performed by the parameter determination device 20 is performed so as to reduce the difference between the output of the reference model and the output signal y. The reference model is, for example, a model including the control object P and a controller for the control object P, and details will be described later. As described above, the target to be approximated to the output signal y differs between the data-driven control using the cost function and the model-free control, and therefore, even if the control parameters determined by the parameter determination device 20 are applied to the control system 10, the control object P may not be controlled appropriately.

[0018] Therefore, in the parameter determination system 1, a control system 10 including a reference model executes MFC, and a parameter determination device 20 determines control parameters that minimize the cost function of the control system 10. By configuring the parameter determination system 1 in this way, it is possible to determine control parameters using the cost function of a controller including a reference model used in data-driven control, making it easier to appropriately control the control target P.

[0019] Furthermore, in a model-reference two-degree-of-freedom control system, the gain of the PID controller can become extremely large when data-driven control is applied. In a model-reference two-degree-of-freedom control system, the feedforward controller is generally given a reference model of a complementary sensitivity function to design the target response, and the feedback controller is generally given a reference model of a sensitivity function to design the response to disturbances. When designing a model-reference two-degree-of-freedom control system within the framework of data-driven tuning, the target sensitivity function must be set so that the error is zero. For this reason, when data-driven tuning is performed using the target sensitivity function as described above, the gain becomes extremely large.

[0020] In contrast to this, the parameter determination system 1 having the above configuration can approximate a part of the PID controller to the reference model, thereby preventing the gain of the PID controller (i.e., the control parameter) from becoming extremely large. That is, in the parameter determination system 1, in designing a model reference type two-degree-of-freedom control system, it becomes possible to use only the reference model of the target complementary sensitivity function without using the reference model of the target sensitivity function. The configurations and operations of the control system 10 and the parameter determination device 20 will be described in detail below.

[0021] <Configuration of control system 10> The control system 10 is a system in which a reference model is applied to an MFC system. FIG. 2 shows the configuration of the MFC system Z, and FIG. 3 shows the reference model M d FIG. First, the MFC system Z will be explained.

[0022] As shown in Fig. 2, the MFC system Z includes an estimator 11, a feedforward controller 12, a feedback controller 13, and a calculator 14. The estimator 11 estimates and outputs a first signal F(^)^ including a disturbance acting on a control target P based on input data u and output data y. The first signal F^ may include unmodeled dynamics. The feedforward controller 12 generates a second signal p(^)^ for calculating a virtual input corresponding to the input data u based on a target value r of the output data y. v Outputs r.

[0023] The feedback controller 13 is a PID controller, and generates a third signal u for calculating a virtual input based on the difference e between the output data y and the target value r. fb The calculator 14 outputs the second signal p v The subtraction value obtained by subtracting the first signal F^ from r is multiplied by a predetermined coefficient α -1 The product of multiplication and the third signal u fb The sum of these is calculated as a virtual input. The mathematical model of MFC System Z is explained below.

[0024] A single-input, single-output nonlinear discrete system can be given as equation (1).

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[0025] Then, the microlocal model can be given as equations (2) and (3).

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[0026] Based on the above microlocal model, the MFC system Z shown in FIG. 2 can be derived and expressed as equations (4) and (5).

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[0027] In the estimator 11, the equation (5) is algebraically identified and expressed as the equations (6) to (9).

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[0028] Furthermore, the third signal u output by the feedback controller 13 fb is the proportional gain K p , integral gain K i and differential gain K d Using the above, it is expressed as in equations (10) to (12).

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[0029] Next, the reference model M d Explain. Reference model M d is a model corresponding to the system M including the MFC system Z and the controlled object P shown in FIG. 3. d is the signal y corresponding to the output signal y when the target value r of the output signal y is input. d The reference model M d can be given as equation (13).

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[0030] 4 is a diagram showing the configuration of the control system 10. The control system 10 shown in FIG. 4 uses the reference model M shown in FIG. d is applied to the feedforward controller 12 and the feedback controller 13 is an I-PD (Integral-Proportional Differential) controller, but is the same in other respects. A mathematical model of the control system 10 will now be described.

[0031] The mathematical model of the control system 10 can be given as in equations (14) and (15).

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[0032] The estimator 11 can be given as in equation (16).

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[0033] By using equations (14) to (16), the control system 10 can be expressed as in equation (17).

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[0034] The feedback controller 13 can be given as in equation (18).

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[0035] Therefore, when m=1, equation (18) can be expressed as the I-PD controller shown in equation (19).

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[0036] Since the I-PD controller has two degrees of freedom, in the feedback controller 13, equation (18) can be replaced by equations (20) to (22).

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[0037] FIG. 5 shows an equivalent circuit of the control system 10 shown in FIG. 4. The control system 10 shown in FIG. 5 differs from the control system 10 shown in FIG. 4 in that the feedback controller 13 includes a controller C1 and a controller C2, but is otherwise the same. The controller C1 is C1 shown in equations (20) and (23), and the controller C2 is C2 shown in equations (20) and (24). As shown in FIG. 5, the feedback controller 13 generates a third signal u based on the target value r. fb a controller C2 that outputs a fourth signal b for calculating the third signal u based on the output data y and the fourth signal b; fb and a controller C1 that outputs:

[0038] As shown in equation (22), the controller C2 functions as a reference model filter. d That is, the control system 10 functions as a model matching type controller. Therefore, in a state where the estimator 11 estimates the desired estimated quantity (first signal F^), the feedforward controller 12 alone can approximate y=M d When r is realized and an estimation error occurs in the estimator 11, the feedback controller 13 calculates y=M d By operating the control system 10 in this manner, the control system 10 can prevent the control parameters from becoming extremely large even when data-driven control is applied. The mathematical model of the control system 10 has been described above.

[0039] <Configuration of parameter determination device 20> 6 is a diagram showing the configuration of the parameter determining device 20. The parameter determining device 20 shown in FIG. 6 includes a storage unit 21 and a control unit 22. The control unit 22 includes an acquisition unit 221 and a determination unit 222.

[0040] The storage unit 21 has a storage medium such as a read-only memory (ROM), a random access memory (RAM), a hard disk drive (HDD), or a solid state drive (SSD), etc. The storage unit 21 stores programs executed by the control unit 22 and various information for determining control parameters of the control system 10.

[0041] The control unit 22 is a processor such as a CPU (Central Processing Unit) or an ECU (Electronic Control Unit). The control unit 22 functions as an acquisition unit 221 and a determination unit 222 by executing a program stored in the storage unit 21. The control unit 22 may be configured with one processor, multiple processors, or a combination of one or more processors and an electronic circuit.

[0042] The acquisition unit 221 acquires a plurality of pieces of input data u to the control object P and a plurality of pieces of output data y output by the control object P during a predetermined period. The predetermined period is, for example, 100 seconds. The acquisition unit 221 may acquire the plurality of pieces of input data u and the plurality of pieces of output data y during the predetermined period from the control system 10. The acquisition unit 221 acquires a plurality of pieces of input data u and a ... set by the user of the parameter determination system 1 by operating an operation unit (not shown) of the parameter determination system 1. d , the design parameter α and the pre-filter L p Obtain the prefilter L p More on this later.

[0043] The determination unit 222 determines the proportional gain K p , integral gain K i and differential gain K das the control parameters. The determination unit 222 determines the control parameters of the feedback controller 13 shown in, for example, equation (19). That is, the determination unit 222 determines the first control parameter of the controller C2 and the second control parameter of the controller C1 shown in equations (20), (23), and (24). Since the first control parameter and the second control parameter are the same control parameter, the determination unit 222 determines one control parameter.

[0044] The determination unit 222 has a cost function indicating the difference between the input data u of the control system 10 acquired by the acquisition unit 221 and a virtual input (i.e., input signal u) calculated by the control system 10. The determination unit 222 has the cost function by, for example, referring to the storage unit 21. The determination unit 222 then inputs the input data u and output data y acquired by the acquisition unit 221 into the cost function and determines the minimum value of the cost function, thereby determining the control parameters of the feedback controller 13. Below, the cost function will be explained using VRFT (Virtual Reference Feedback Tuning), which is one of the data-driven controls.

[0045] When the time series data D obtained when an open / closed experiment including a control target P is conducted at a predetermined time is given as in equation (25), the virtual value of the target value r is expressed as in equation (26), where N is the data length and t is the discrete time.

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[0046] In VRFT, processing is performed based on the difference between the input data u actually input to the control target P and the virtual input. Therefore, if a feedback controller C using an adjustable parameter ρ is given as in equation (27), the cost function J VR (ρ) can be given by equation (28).

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[0047] Reference model M d In the control system 10 including the above, the cost function corresponding to the equation (28) is given as the equation (31), so that the pre-filter L p By applying the pre-filter L, equation (28) is replaced by equation (32), which is an approximation of equation (31). p For example, |L p |=|M d | / φ uu It is expressed as φ uu is, for example, 1.

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[0048] Furthermore, the virtual input calculated by the control system 10 is given by equation (35).

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[0049] If a design parameter α adjusted by the user is given in equation (35), equation (32) can be expressed as equation (39).

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[0050] In the case of a PID controller (that is, when the order m is 2), the equation (40) is expressed as the equation (43).

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[0051] The determination unit 222 determines the reference model M d and pre-filter L pand inputs the input data and output data acquired by the acquisition unit 221. Then, the determination unit 222 can determine the control parameters shown in equation (43) by minimizing the cost function (i.e., identifying w corresponding to the minimum value of J(w)). By operating in this manner, the determination unit 222 can determine the control parameters in model-free control, which is performed so as to reduce the difference between the output signal y and the target value r, by data-driven control, which is performed so as to reduce the difference between the output of the reference model and the output signal y. The cost function has been described above.

[0052] <Processing Sequence in Parameter Determination Device 20> 7 shows an example of a processing sequence in the parameter determining device 20. The processing sequence shown in FIG.

[0053] The acquisition unit 221 acquires a plurality of pieces of input data u and a plurality of pieces of output data y from the control object P at a predetermined time (step S11). The determination unit 222 determines the reference model M d , prefilter L p and the design parameter α are set in the control system 10 shown in equation (17) and the cost function shown in equation (46) (step S12). p is the reference model M d is the same as

[0054] The determination unit 222 substitutes the input data u and output data y acquired by the acquisition unit 221 into the cost function (step S13), and determines control parameters that minimize the cost function (step S14). The determination unit 222 outputs the determined control parameters to the feedback controller 13 (step S15), thereby applying the control parameters to the control system 10. That is, the determination unit 222 applies the determined control parameters to equation (17).

[0055] <Effect verification through simulation> The inventors have confirmed the effects of the parameter determination system 1 according to this embodiment through simulations. The simulations carried out by the inventors are simulations relating to yaw rate control in the case where the control object P is a vehicle.

[0056] In the simulation, the sampling period T s = 0.01 seconds, and white noise was added to the output signal y (yaw rate). The input data u and output data y acquired by the acquisition unit 221 were acquired by a closed-loop test, and a first-order low-pass filter was used as the filtering method for the estimator 11. The reference model M d is given as in equation (44), α=0.0, proportional gain K p =0.10, integral gain K i =1.0 was set as the initial value.

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[0057] And white noise power = 1.0 x 10 ―9 , the time constant of the low-pass filter of the estimator 11 is set to 0.1 s, and the control parameters are optimized by the method proposed in this embodiment. p =0.833, integral gain K i = 2.08. Furthermore, the white noise power was 1.0 × 10 -7 , the time constant of the low-pass filter of the estimator is set to 0.5 s, and the control parameters are optimized by the method proposed in this embodiment. p =3.75, integral gain K i =9.37.

[0058] FIG. 8 is a diagram showing the results of a simulation of vehicle yaw rate control. The horizontal axis of FIG. 8 represents time, and the vertical axis of FIG. 8 represents yaw rate, the difference between the yaw rate and the target value, and vehicle speed. The yaw rates shown in FIG. 8 represent the yaw rate of a system to which the parameter determination system 1 is not applied (hereinafter referred to as the "system before application"), the yaw rate of a system to which the parameter determination system 1 is applied (hereinafter referred to as the "system after application"), and the target value of the yaw rate. The difference from the target value shown in FIG. 8 represents the difference between the yaw rate of the system before application and the target value, and the difference between the yaw rate of the system after application and the target value. In the simulation, the yaw rate was switched between 0 and yaw rate R (0.5 rad / s) at regular intervals. Furthermore, the vehicle speed was changed from 10 km / h to 100 km / s during period P5 (40 to 50 seconds after the start of the simulation).

[0059] As shown in Fig. 8, in the system before application, a difference from the target value is likely to occur in periods P1 to P4 when the yaw rate switches. On the other hand, in the system after application, the difference from the target value is smaller than in the system before application in periods P1 to P4. Furthermore, in the system after application, even when the vehicle speed increases in period P5, making it easier for a difference between the yaw rate and the target value to occur, the difference between the yaw rate and the target value is small. From the above results, it was confirmed that the parameter determination system 1 according to this embodiment can obtain a desired response.

[0060] <Effects of the parameter determination device 20> As described above, the parameter determination device 20 includes an acquisition unit 221 that acquires a plurality of pieces of input data u to the control object P and a plurality of pieces of output data y output by the control object P over a predetermined period of time, and a determination unit 222 that determines the control parameters of the feedback controller 13 by inputting the input data u and output data y acquired by the acquisition unit 221 into a cost function indicating the difference between the input data u acquired by the acquisition unit 221 and a virtual input of the control system 10 and finding the minimum value of the cost function.

[0061] By configuring the parameter determination device 20 in this way, the reference model M d Since it is possible to determine the control parameters that minimize the cost function of the control system 10 including the reference model M, it becomes easier to appropriately control the control target P. Furthermore, when the controller C2 included in the feedback controller 13 d By having the determination unit 222 determine the control parameters in a configuration that approximates the above, it is possible to prevent the control parameters (gain) of the feedback controller 13 from becoming extremely large.

[0062] The present invention has been described above using embodiments, but the technical scope of the present invention is not limited to the scope described in the above embodiments, and various modifications and changes are possible within the scope of the gist of the present invention. For example, all or part of the device can be configured by functionally or physically distributing or integrating any unit. Furthermore, new embodiments resulting from any combination of multiple embodiments are also included in the embodiments of the present invention. The effects of the new embodiments resulting from the combination also have the effects of the original embodiments. [Explanation of symbols]

[0063] 1. Parameter determination system 10. Control System 11 Estimator 12 Feedforward Controller 13 Feedback Controller 14 Calculator 20 Parameter determination device 21 Memory section 22 Control Unit 221 Acquisition Department 222 Decision Section

Claims

1. an acquisition unit that acquires a plurality of input data to a control target and a plurality of output data output by the control target during a predetermined period; a control system including: an estimator that estimates and outputs a first signal including a disturbance acting on the controlled object based on the input data and the output data; a feedforward controller that includes a reference model of the controlled object and that outputs a second signal for calculating a virtual input corresponding to the input data based on a target value of the output data; a feedback controller that outputs a third signal for calculating the virtual input based on a difference between the output data acquired by the acquisition unit and the target value; and a calculator that calculates, as the virtual input, an added value obtained by multiplying a subtraction value obtained by subtracting the first signal from the second signal by a predetermined coefficient and then adding the multiplied value to the third signal; A parameter determination device having:

2. the determination unit determines, as the control parameters, a proportional gain, an integral gain, and a differential gain of a proportional unit, an integrator, and a differentiator, respectively, included in the feedback controller; The parameter determination device according to claim 1 .

3. the determiner determines the control parameters of the feedback controller, which outputs a subtraction result obtained by subtracting a second calculated value of a second term including the proportional gain and a third calculated value of a third term including the differential gain from a first calculated value of a first term including the integral gain as the third signal. The parameter determination device according to claim 2 .

4. the feedback controller includes a first feedback controller that outputs a fourth signal for calculating the third signal based on the target value, and a second feedback controller that outputs the third signal based on the output data acquired by the acquisition unit and the fourth signal, the determination unit determines a first control parameter of the first feedback controller and a second control parameter of the second feedback controller. The parameter determination device according to claim 1 .

5. The computer executes an acquisition step of acquiring a plurality of pieces of input data to a control target and a plurality of pieces of output data output by the control target during a predetermined period; a control system including: an estimator that estimates and outputs a first signal including a disturbance acting on the controlled object based on the input data and the output data; a feedforward controller that includes a reference model of the controlled object and outputs a second signal for calculating a virtual input corresponding to the input data based on a target value of the output data; a feedback controller that outputs a third signal for calculating the virtual input based on a difference between the output data acquired in the acquisition step and the target value; and a calculator that calculates, as the virtual input, an added value obtained by multiplying a subtraction value obtained by subtracting the first signal from the second signal by a predetermined coefficient and adding the multiplied value to the third signal; A parameter determination method having the following:

6. A parameter determination system comprising: a control system that calculates a virtual input corresponding to input data to a controlled object; and a parameter determination device that determines control parameters of the control system, The control system includes: an estimator that estimates and outputs a first signal including a disturbance acting on the control target based on the input data to the control target and output data output by the control target; a feedforward controller including a reference model of the controlled object, and outputting a second signal for calculating a virtual input corresponding to the input data based on a target value of the output data; a feedback controller that outputs a third signal for calculating the virtual input based on a difference between the output data output by the controlled object and the target value; a calculator that calculates, as the virtual input, an added value obtained by multiplying a subtraction value obtained by subtracting the first signal from the second signal by a predetermined coefficient and adding the third signal to the multiplied value; The parameter determination device an acquisition unit that acquires a plurality of pieces of input data to the control target and a plurality of pieces of output data output by the control target during a predetermined period; a determination unit that determines a control parameter of the feedback controller by inputting the input data and the output data acquired by the acquisition unit into a cost function of the control system, the cost function indicating a difference between the input data acquired by the acquisition unit and the virtual input, and finding a minimum value of the cost function; A parameter determination system having:

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