control device

Abstract

The control device includes a static compensator that calculates a static compensation input based on a static parameter, a dynamic compensator that calculates a dynamic compensation input based on a dynamic parameter, a subtracter that combines the static compensation input and the dynamic compensation input to calculate an actual input, an ideal output calculator that calculates an ideal output corresponding to the control input using an input-output model that defines an ideal input-output relationship of the control input and the control output, and a parameter adjuster that adjusts the static parameter and the dynamic parameter in such a manner that the difference between the control output and the ideal output is minimized.

Description

Technical Field

[0001] This invention relates to a control device for controlling an object. Background Technology

[0002] Control systems for construction machinery, such as hydraulic excavators, require complex controls such as automatic operation. In these systems, the control structure is hierarchical, with downstream control loops directly controlling the controlled object operating according to instructions from the upstream controller. However, when both the input / output characteristics of the controlled object and the downstream control loops change significantly, the upstream controller may fail to function properly and thus fail to control the controlled object effectively. Therefore, if the downstream control loops can maintain ideal input / output characteristics, the upstream controller can be designed based on these ideal characteristics.

[0003] Here, a technique for suppressing variations in the input-output characteristics of downstream control loops is proposed. For example, Non-Patent Document 1 discloses a control device comprising: an input-output model (Pm) representing the ideal input-output characteristics of a control input (u′) input from an upstream controller and a control output (y) output from a controlled object; a compensator (D) generating a compensation input (uc) to mitigate model errors in the ideal output (ym) of the input-output model (Pm) of the control input (u′) and the control output (y); and a subtractor calculating the actual input (u) to the controlled object by subtracting the compensation input (uc) from the control input (u′).

[0004] However, in the technology of non-patent document 1, when the input and output characteristics of the controlled object change significantly, the compensator cannot adequately compensate for the change, and the upstream controller cannot properly control the controlled object.

[0005] Existing technical documents

[0006] Non-patent literature

[0007] Non-Patent Literature 1: Umei, Okajima, Matsunaga, Asai, "Design of a Multi-Input Output System with a Model Error Suppression Compensator", Journal of the Society for System Control Information, Vol. 27 No. 2, pp. 67-72, 2014 Summary of the Invention

[0008] The present invention was made to solve the above-mentioned problems, and its purpose is to provide a control device that can properly control the controlled object using the controller designed in the present invention, even if the input and output characteristics of the controlled object change significantly.

[0009] One aspect of the present invention relates to a control device for controlling a controlled object, comprising: a controller for calculating a control input for making the deviation between a control output output from the controlled object and a target output zero; a static compensator for calculating a static compensation input for compensating for variations in the static characteristics of the controlled object based on static parameters and the control input; a dynamic compensator for calculating a dynamic compensation input for compensating for variations in the dynamic characteristics of the controlled object based on dynamic parameters and the control output; a synthesizer for synthesizing the static compensation input and the dynamic compensation input to calculate an actual input and input it to the controlled object; an ideal output calculator for calculating an ideal output corresponding to the control input using an input-output model that defines an ideal input-output relationship between the control input and the control output; and a parameter adjuster for adjusting the static parameters and the dynamic parameters respectively in a manner that minimizes the difference between the control output and the ideal output.

[0010] Based on this configuration, even if the input and output characteristics of the controlled object change significantly, the controlled object can be properly controlled using the controller designed at the time of design. Attached Figure Description

[0011] Figure 1 This is a block diagram illustrating an example of the configuration of a control device according to an embodiment of the present invention.

[0012] Figure 2 This is a flowchart illustrating an example of the processing of a control device.

[0013] Figure 3 This is a block diagram representing the feedback system that constitutes the control loop.

[0014] Figure 4 This is a hydraulic circuit diagram of a hydraulic motor control system used as the controlled object.

[0015] Figure 5 It is a graph showing the application results of the control device to the hydraulic motor control system.

[0016] Figure 6 It is a chart showing the adjustment results of static gain, proportional gain, and derivative gain.

[0017] Figure 7 It is Figure 6 A magnified view of the chart. Detailed Implementation

[0018] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. Figure 1This is a block diagram illustrating an example of the configuration of the control device 1 according to an embodiment of the present invention. The control device 1 controls the controlled object 100 by outputting a control output y(k) in response to an actual input up(k). The controlled object 100 may be, for example, construction machinery including hydraulic excavators and hydraulic cranes, or a vehicle. More specifically, the controlled object 100 may be the hydraulic system of the construction machinery or the automatic braking system of the vehicle. The k enclosed in parentheses in the reference numerals indicates a time.

[0019] The control device 1 includes a target setter 2, a subtractor 3, a controller 4, a static compensator 5, a dynamic compensator 6, a subtractor 7 (an example of a synthesizer), a parameter adjuster 9, a subtractor 8, an ideal output calculator 10, a memory 11, and a detector 12. The target setter 2, subtractor 3, controller 4, static compensator 5, dynamic compensator 6, subtractor 7, subtractor 8, parameter adjuster 9, and ideal output calculator 10 are, for example, composed of a central processing unit or an ASIC. Alternatively, the target setter 2, memory 11, and detector 12 may be omitted from the structural elements of the controlled object 100.

[0020] The target setter 2 sets the target of the control output y(k), i.e., the target output r(k). The target output r(k) adopts various values ​​depending on the controlled object 100. For example, if the controlled object 100 is construction machinery, a target speed is adopted for the motor that rotates the upper rotating body. For example, when controlling the controlled object 100 in a manner that follows a predefined target mode with control output y(k), the target output r(k) adopts time-series data of the target value constituting the target mode. For example, the target output r(k) may be a target value corresponding to the amount of operation of the lever that is input to move the working device or the upper rotating body. For example, the target output r(k) may adopt a predefined constant value.

[0021] Subtractor 3 calculates the deviation e(k) by subtracting the control output y(k) from the target output r(k).

[0022] Controller 4 calculates the control input uc(k) to make the deviation e(k) zero based on the control output y(k). Controller 4 is equivalent to the upstream controller described in the background art. Controller 4 can calculate the control input uc(k) to make the deviation e(k) zero simply by means of, for example, PID control. As an expression for PID control, for example, expression (17) described later is adopted. In addition, controller 4 can use various feedback control or feedforward control other than PID control, such as P control, PD control, and PI control, to calculate the control input uc(k).

[0023] The static compensator 5 calculates the static compensation input for compensating for variations in the static characteristics of the controlled object 100 by multiplying the static gain f0 (an example of a static parameter) by the control input uc(k). Static characteristics refer to the time-independent characteristics of the controlled object 100. For example, a static characteristic might be equivalent to the scale that the control output y(k) can achieve. The static gain f0 is the gain used to compensate for variations in this static characteristic. For example, if the dynamic compensation input calculated by the dynamic compensator 6 is too large, the actual input up(k) becomes too small, and the value of the control output y(k) is significantly smaller than expected. To avoid this situation, the static compensator 5 multiplies the static gain f0 by the control input uc(k).

[0024] The dynamic compensator 6 calculates the dynamic compensation input to compensate for variations in the dynamic characteristics of the controlled object 100 based on the dynamic gain (an example of a dynamic parameter) and the control output y(k). Dynamic characteristics refer to time-dependent characteristics such as the rise and fall characteristics of the controlled object 100. The dynamic gain is the gain used to compensate for such variations in dynamic characteristics. The dynamic gain includes, for example, a proportional gain Kp and a derivative gain KD. The dynamic compensator 6 calculates the dynamic compensation input, for example, using the expression Kp·y(k) + KD·Δy(k). Here, Δy(k) represents the derivative of y(k).

[0025] Subtractor 7 calculates the actual input up(k) by subtracting the dynamic compensation input from the static compensation input, and inputs the actual input up(k) into the controlled object 100. This adjusts the control input uc(k) to compensate for the dynamic and static characteristics of the controlled object 100. The actual input up(k) can be expressed, for example, by the following formula.

[0026] up(k)=fO·uc(k)-Kp·y(k)-KD·Δy(k)

[0027] The aforementioned static compensator 5, dynamic compensator 6, subtractor 7, and controlled object 100 constitute control loop 50. Control loop 50 is a downstream control loop that directly controls the controlled object 100. Control loop 50 responds to control input uc(k) and outputs control output y(k).

[0028] The ideal output calculator 10 utilizes the transfer function, i.e., the input-output model Gm(z), which represents the ideal input-output relationship between the control input uc(k) and the control output y(k). -1The ideal output yr(k) corresponding to the control input uc(k) is calculated. The ideal input-output relationship is equivalent to the relationship between the control input uc(k) and the control output y(k) during the design of the controller 4. Hereinafter, the relationship between the control input uc(k) and the control output y(k) will be referred to as the input-output characteristic of the control loop 50. For example, if the controller 4 is designed based on the initial input-output characteristics of the control loop 50, which includes the initial controlled object 100, the input-output model has the initial input-output characteristics of the control loop 50. Therefore, even if the input-output characteristics of the controlled object 100 change from the initial characteristics, and the input-output characteristics of the control loop 50 also change from the initial input-output characteristics, the ideal output calculator 10 can still calculate the ideal output yr(k) based on the initial input-output characteristics of the control loop 50. Input-output model Gm(z) -1 For example, it can be represented by equations (19), (20), and (21) as described later.

[0029] Subtractor 8 calculates the difference A by subtracting the ideal output yr(k) from the control output y(k), and inputs the difference A into parameter adjuster 9.

[0030] The parameter adjuster 9 adjusts the static gain f0 and the dynamic gain (Kp, KD) respectively to minimize the difference A input from the subtractor 8. The parameter adjuster 9 can calculate the static gain f0 and the dynamic gain (Kp, KD) for example by recursive least-squares. In this case, the static gain f0 and the dynamic gain (Kp, KD) are adjusted synchronously with the sampling time of the control device 1. That is, the static gain f0 and the dynamic gain (Kp, KD) can be adjusted online. As a recursive least-squares method, the evaluation function J represented by equation (9) described later can be minimized using equations (10) to (16) described later.

[0031] The memory 11 is, for example, composed of RAM or flash memory. The memory 11 stores the control output y(k) and the ideal output yr(k). In addition, the memory 11 can store the control output y(k) and the ideal output yr(k) calculated from time k up to several samples ago.

[0032] The detector 12 is, for example, a sensor that detects the control output y(k) from the controlled object 100. For example, if the controlled object 100 is an actuator, the detector 12 is a sensor that detects the state of the actuator. For example, if the controlled object 100 is an electric motor that rotates the upper rotating body, the detector 12 is a sensor that detects the rotational speed of the electric motor.

[0033] Next, the processing of control device 1 will be explained. Figure 2This is a flowchart illustrating an example of the processing of control device 1. In step S1, subtractor 3 calculates the deviation e(k) by subtracting the control output y(k) from the target output r(k).

[0034] In step S2, the controller 4 inputs the deviation e(k) and the control output y(k) into equation (17) to calculate the control input uc(k).

[0035] In step S3, the ideal output calculator 10 combines the control input uc(k) and the input-output model Gm(z) represented by equation (19). -1 The ideal output yr(k) is calculated by multiplying the two numbers.

[0036] In step S4, detector 12 detects the control output y(k) output from control loop 50 as a response to control input uc(k).

[0037] In step S5, the subtractor 8 calculates the difference A by subtracting the ideal output yr(k) from the control output y(k) detected by the detector 12.

[0038] In step S6, the parameter adjuster 9 uses recursive least squares to calculate the static gain f0 and dynamic gain (Kp, KD) to minimize the difference A. After step S6, the process returns to step S1. Thus, the static gain f0 and dynamic gain (Kp, KD) are adjusted successively.

[0039] Thus, according to control device 1, the input-output model Gm(z) representing the ideal input-output characteristics of control input uc(k) and control output y(k) is used. -1 The ideal output yr(k) corresponding to the control input uc(k) is calculated, and the static gain f0 of the static compensator 5 and the dynamic gain (Kp, KD) of the dynamic compensator 6 are adjusted to minimize the difference A between the ideal output yr(k) and the control output y(k). Therefore, even if the input-output characteristics of the controlled object 100 change significantly, the input-output characteristics of the control input uc(k) and the control output y(k) can be maintained at the ideal input-output characteristics designed for the controller 4. Thus, even if the input-output characteristics of the controlled object 100 change significantly, the controlled object 100 can be appropriately controlled using the controller 4 designed in the original configuration. This simplifies the design of the controller 4 and allows for the smooth development of the control device 1.

[0040] Furthermore, the present invention can be adapted to the following variations.

[0041] (1) The parameter adjuster 9 can use a database-driven control method to adjust the static gain f0 and the dynamic gain (Kp, KD). The database-driven control method is a method of calculating parameters suitable for the current state of the controlled object based on parameters that have been calculated in the past and stored in the database.

[0042] In this method, the control device 1 also includes a database storing previously calculated static gain f0 and dynamic gain (Kp, KD). The parameter adjuster 9 retrieves a request point representing the current state of the controlled object 100 from the memory 11. The request point may include, for example, the control output y(k) and ideal output yr(k) from one sample to several samples prior. The parameter adjuster 9 calculates the distance between each request point and the parameter set stored in the database, and extracts k parameter sets in ascending order of distance. Each parameter set includes, for example, a set of static gain f0, proportional gain Kp, and differential gain KD. The parameter adjuster 9 calculates weighting coefficients for each of the extracted k parameter sets, with the shorter the distance, the larger the value. The parameter adjuster 9 averages the calculated weighting coefficients across the k parameter sets to calculate the final parameter set, which is then used as the static gain f0 and dynamic gain (Kp, KD).

[0043] (2) The formula used by the dynamic compensator 6 to calculate the dynamic compensation input may include the product of the second derivative of the control output y(k) and the second derivative gain. Moreover, the formula may include the value obtained by adding the product of the i-th derivative of the control output y(k) and the i-th derivative gain from i=1 to i=n (n is a positive integer).

[0044] (Example)

[0045] Next, embodiments of the present invention will be described. First, the design of the control loop 50 will be described. Figure 3 This is a block diagram representing the feedback system that constitutes control loop 50. The feedback system is represented by the following formula.

[0046] [Formula 1]

[0047] u p (k)=f0(k)u c (k)-K P (k)t(k)-K D (k)Δy(k) (1)

[0048] Here, up(k), y(k), uc(k), and P represent the actual input, control output, control input, and controlled object, respectively. Furthermore, Δ represents the difference operator, and the backoff operator z is used. -1 And expressed as Δ=1-z -1f0(k), Kp(k), and KD(k) represent the parameters. The parameter adjuster 9 adjusts the parameters of f0(k), Kp(k), and KD(k) online using a recursive least squares method. The advantage of the recursive least squares method is its low computational cost. The parameter adjuster 9 calculates the parameters of the static compensator 5 and the dynamic compensator 6 based on the operating data (actual input up(k) and control output y(k)).

[0049] Secondly, we will explain the method for adjusting parameters based on operational data. Assuming that f0(k) is not 0, equation (1) is transformed as follows.

[0050] [Formula 2]

[0051]

[0052] =θ1(k)u p (k)+θ2(k)y(k)+θ3(k)y(k-1) (3)

[0053]

[0054] In equation (3), θ1(k), θ2(k), and θ3(k) are represented by equation (4).

[0055] Furthermore, the input-output model Gm(z-) will represent the transfer function of the ideal control loop 50 with the control input uc(k). 1 The response obtained when yr(k, θ(k)) is taken as the ideal output yr(k, θ(k)). In this case, the ideal output yr(k, θ(k)) is represented by equation (5).

[0056] [Formula 3]

[0057] y r (k, θ(k))=G m (z -1 )u c (k, θ(k)) (5)

[0058] Based on the relationship between equations (3) and (5), the following equation is obtained.

[0059] [Formula 4]

[0060]

[0061]

[0062]

[0063] The evaluation function J is defined as follows.

[0064] [Formula 5]

[0065]

[0066] Here, N is the total number of data points. The parameter θ(k) is adjusted by minimizing the evaluation function J to make the control output y(k) follow the ideal output yr(k). Thus, by utilizing the optimized parameters, the input-output characteristics of the control loop 50, which includes the static compensator 5, the dynamic compensator 6, and the controlled object 100, can be made to match the input-output model Gm(z). -1 The input and output characteristics are consistent.

[0067] Secondly, in order to minimize the sum of squares of equation (9), the recursive least squares method shown below is applied.

[0068] [Formula 6]

[0069] θ(k)=θ(k-1)+K(k){y(k)-y r (k,θ(k))} (10)

[0070]

[0071]

[0072] ω is the forgetting coefficient. θ(k) and ψ(k) are expressed by the following formula.

[0073] [Formula 7]

[0074] θ(k)=[θ1(k) θ2(k) θ3(k)] T (13)

[0075] ψ(k)=G m (z -1 )[u p (k) y(k) y(k-1)] T (14)

[0076] The initial values ​​Γ(0) of the error covariance matrix Γ(k) and the initial values ​​θ(0) of the estimated value θ(k) are specified by the following formula.

[0077] [Formula 8]

[0078] Γ(0)=αI (15)

[0079] θ(0)=[θ1(0) θ2(0) θ3(0)] T (16)

[0080] α is any real number satisfying α>0. I is a 3×3 identity matrix. θi(0) is any real number. θi(0) is defined as not being 0 based on the condition that f0 is not 0.

[0081] Next, the configuration of the control device 1 involved in this embodiment will be explained. The control device 1 consists of... Figure 1 express.

[0082] Control loop 50 is a downstream control loop consisting of a feedback proportional-integral (F-PD) control system. Controller 4 is an upstream control loop. Controller 4 consists of a PID (proportional-integral-derivative) control system with fixed control parameters.

[0083] exist Figure 1 In its configuration, the input-output characteristics of the control loop 50 are made to match the input-output model Gm(z). -1 The parameters of the static compensator 5 and the dynamic compensator 6 are adjusted in a manner consistent with the input-output characteristics of the model Gm(z). Thus, the downstream control loop 50 has a characteristic consistent with the input-output model Gm(z). -1 It has the same input-output characteristics. As a result, it can be derived from the ideal input-output model Gm(z). -1 Design the upstream controller 4.

[0084] In this embodiment, the controller 4 is composed of a PID control system represented by equation (17).

[0085] [Formula 9]

[0086]

[0087] e(k)=r(k)-y(k) (18)

[0088] kc represents the proportional gain, TI represents the integral time [s], and TD represents the derivative time [s].

[0089] Next, a simulation of applying the control device 1 involved in the embodiment to the hydraulic motor control system will be described.

[0090] Figure 4 This is a hydraulic circuit diagram of a hydraulic motor control system used as the controlled object 100. The hydraulic motor control system includes an electric motor 401 (servo motor), a hydraulic pump 402, piping 403, a hydraulic motor 404, an inertial body 405, a hydraulic sensor 406, a safety valve 407, an oil tank 408, and a control device 1.

[0091] Control device 1 inputs an indicated rotational speed Np, represented by an analog voltage, to motor 401. Motor 401 is driven according to this indicated rotational speed Np. Hydraulic pump 402 is connected to motor 401 and rotates based on the power of motor 401. Based on the rotation of hydraulic pump 402, working oil flows from oil tank 408 into pipe 403. Based on the hydraulic pump 402, the working oil is forced out at a discharge flow rate Qp, generating pressure Pm within pipe 403. Based on this pressure Pm, hydraulic motor 404 rotates with hydraulic power T.

[0092] The rotational speed of the hydraulic motor 404 is represented by Nm, and the moment of inertia and viscous damping coefficient of the inertial body 405 are represented by I and D, respectively. The working oil used to power the hydraulic motor 404 is returned to the oil tank 408 and reused by the hydraulic pump 402.

[0093] Control device 1 detects the rotational speed Nm via detector 12 and calculates the indicated rotational speed Np in a manner that makes the detected rotational speed Nm the target rotational speed. The indicated rotational speed Np is equivalent to the actual input up(k), and the rotational speed Nm is equivalent to the control output y(k).

[0094] Secondly, the verification of this embodiment based on the simulation model that models the hydraulic motor control system is explained.

[0095] In this verification, the ideal input-output model Gm(z-) of the control loop 50 is designed as follows. 1 ).

[0096] [Formula 10]

[0097]

[0098] Denominator P(z) -1 The coefficients p1 and p2 are expressed using the following formula.

[0099] [Formula 11]

[0100] P(z -1 )=1+ρ1·z -1 +ρ2·z -2 (20)

[0101]

[0102] Ts represents the sampling time, and σ and δ represent the dynamic parameters of the controlled object 100, such as its rise and decay characteristics. These dynamic parameters are arbitrarily set by the designer based on the input and output characteristics of the controlled object 100.

[0103] Secondly, the simulation results will be explained. Figure 5 This is a graph showing the application results of control device 1 to the hydraulic motor control system. Figure 6It is a chart showing the adjustment results of static gain f0, proportional gain Kp, and differential gain KD. Figure 7 It is an enlarged representation Figure 6 The chart.

[0104] like Figure 5 As shown, in this simulation, after 40 seconds from the start, the moment of inertia of inertial body 405 is changed to 1 / 10. Here, for practical machine applications, the control output y decreases in a ramp-like manner as the ideal output yr changes from 100 to 0. Figure 5 In this process, the ideal output yr, control output y, control input uc, actual input up, pressure Pm, and discharge flow rate Qp are normalized.

[0105] exist Figure 5 In the transient response shown, it can be seen that the control output y, which represents the rotational speed Nm of the hydraulic motor 404, follows the ideal output yr even after the moment of inertia changes. This is because, as Figure 6 and Figure 7 As shown, the static gain f0, proportional gain Kp, and differential gain KD were adjusted according to the change in moment of inertia.

[0106] On the other hand, such as Figure 5 As shown, it can be seen that the control input uc from controller 4 does not change significantly before and after the change in moment of inertia. Therefore, it can be concluded that the upstream controller 4 is not affected by the changes in the input-output characteristics of the downstream control loop 50 and operates accordingly.

[0107] Thus, in this embodiment, since the static gain f0, proportional gain Kp, and differential gain KD are adjusted online, even if the characteristics of the controlled object 100 change, the input-output characteristics of the control loop 50 remain consistent with the input-output model Gm(z). -1 The ideal input-output characteristics are consistent with those of the input-output model Gm(z). As a result, it is possible to determine the optimal input-output model Gm(z). -1 The controller 4 is designed. Therefore, the design of controller 4 becomes easier, enabling the smooth development of control device 1. Furthermore, it can suppress the impact of variations in the input / output characteristics of the downstream control loop 50 on the overall control device 1.

[0108] (Summary of Implementation Methods)

[0109] One aspect of the present invention relates to a control device for controlling a controlled object, comprising: a controller for calculating a control input for making the deviation between a control output output from the controlled object and a target output zero; a static compensator for calculating a static compensation input for compensating for variations in the static characteristics of the controlled object based on static parameters and the control input; a dynamic compensator for calculating a dynamic compensation input for compensating for variations in the dynamic characteristics of the controlled object based on dynamic parameters and the control output; a synthesizer for synthesizing the static compensation input and the dynamic compensation input to calculate an actual input and input it to the controlled object; an ideal output calculator for calculating an ideal output corresponding to the control input using an input-output model that defines an ideal input-output relationship between the control input and the control output; and a parameter adjuster for adjusting the static parameters and the dynamic parameters respectively in a manner that minimizes the difference between the control output and the ideal output.

[0110] According to this configuration, since the static and dynamic parameters are adjusted and not fixed, even if the input-output characteristics of the controlled object change significantly, the controller designed during the design of the control device can still appropriately control the controlled object. That is, using an input-output model representing the ideal input-output characteristics of the control input and control output, the ideal output corresponding to the control input is calculated, and the static parameters of the static compensator and the dynamic parameters of the dynamic compensator are adjusted in a way that minimizes the difference between the ideal output and the control output. Therefore, even if the input-output characteristics of the controlled object change significantly, the input-output characteristics of the control input and control output are maintained at the ideal input-output characteristics. Thus, even if the input-output characteristics of the controlled object change significantly, the controller designed during the design process can still appropriately control the controlled object. This makes controller design easier and control device development smoother.

[0111] Furthermore, according to this configuration, static and dynamic parameters are adjusted using the ideal output and control output calculated during the operation of the controlled object. Therefore, online adjustment of static and dynamic parameters during operation can be achieved without stopping the operation of the equipment containing the controlled object. In Patent Document 1, since no parameters for adjusting the compensator are predetermined, the operation of the equipment must be stopped in order to adjust the parameters.

[0112] Furthermore, since the control input is corrected by dynamic compensation input calculated based on dynamic parameters and control output, variations in the dynamic characteristics of the controlled object, such as rise and decay characteristics, can be compensated. Moreover, since the control input is corrected by static compensation input calculated based on control input and static parameters, variations in the static characteristics of the control characteristics, such as changes in the magnitude of the control input due to the synthesis of dynamic compensation input, can be suppressed.

[0113] In the above control device, the dynamic parameters may include proportional gain and derivative gain. The dynamic compensator can use the sum of the value obtained by multiplying the control output by the proportional gain and the value obtained by multiplying the derivative value of the control output by the derivative gain as the dynamic compensation input for calculation. The parameter adjuster can adjust the static parameters, the proportional gain and the derivative gain respectively in a way that minimizes the difference between the control output and the ideal output.

[0114] According to this configuration, since the sum of the control output multiplied by the proportional gain and the differential value of the control output multiplied by the differential gain is calculated as the dynamic compensation input, it is possible to accurately compensate for changes in the dynamic characteristics of the controlled object. Furthermore, the control input is corrected using static parameters, proportional gain, and differential gain adjusted in this manner. Therefore, even if the input-output characteristics of the controlled object change significantly, the controlled object can be appropriately controlled using the controller designed in this way.

[0115] In the above control device, the parameter adjuster can adjust the static parameters and the dynamic parameters using the recursive least squares method.

[0116] Based on this configuration, since the static and dynamic parameters are adjusted using the recursive least squares method, they are adjusted in real time. As a result, when the input and output characteristics of the controlled object change, the static and dynamic parameters can be adjusted quickly, enabling appropriate control of the controlled object.

[0117] In the aforementioned control device, the synthesizer can use the value obtained by subtracting the dynamic compensation input from the static compensation input as the actual input for calculation.

[0118] According to this configuration, since the actual input is calculated by subtracting the dynamic compensation input from the static compensation input, the actual input can be easily calculated.

[0119] In the above-mentioned control device, the controlled object may be a hydraulic system, which may include a hydraulic pump, an electric motor that drives the hydraulic pump, and an actuator that operates based on working oil supplied from the hydraulic pump. The hydraulic system may output the state value of the actuator as the control output, and the synthesizer may calculate the command value of the electric motor as the actual input.

[0120] The input-output characteristics of a hydraulic system can sometimes vary significantly due to factors such as changes in the temperature of the working oil. For example, in the case of a hydraulic excavator, where the bucket scoops up sand and soil, the mass and inertia change, causing the input-output characteristics of the hydraulic system to fluctuate considerably. In this configuration, by adjusting the static and dynamic parameters to accommodate such fluctuations, the hydraulic system can be appropriately controlled.

Claims

1. A control device for controlling a controlled object, characterized in that... include: The controller calculates the control input used to make the deviation between the control output from the controlled object and the target output zero; A static compensator calculates a static compensation input for compensating for variations in the static characteristics of the controlled object by multiplying the control input by a static parameter. The dynamic compensator calculates the dynamic compensation input by multiplying the control output by the proportional gain and the differential value of the control output by the differential gain, using this sum as the dynamic compensation input to compensate for changes in the dynamic characteristics of the controlled object. The synthesizer calculates the actual input by subtracting the dynamic compensation input from the static compensation input and inputs the actual input to the controlled object; An ideal output calculator uses an input-output model that defines the ideal input-output relationship between the control input and the control output to calculate the ideal output corresponding to the control input. as well as, A parameter adjuster uses recursive least squares to adjust the static parameter and the dynamic parameter, which includes the proportional gain and the derivative gain, respectively, in a manner that minimizes the difference between the control output and the ideal output.

2. The control device according to claim 1, characterized in that: The controlled object is a hydraulic system. The hydraulic system includes a hydraulic pump, an electric motor that drives the hydraulic pump, and an actuator that operates based on working oil supplied from the hydraulic pump, wherein... The hydraulic system outputs the state value of the actuator as the control output. The synthesizer uses the command value of the motor as the actual input for calculation.

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