JPH0756609A - Controller - Google Patents

Abstract

PURPOSE:To provide a controller of an IMC structure which can correct the gain of an internal model and to secure the stabilized control even when an identification error is included in the internal model. CONSTITUTION:The target value (r) is supplied to a target value filter part 2 and the feedback value (e) is subtracted from the output of the part 2 through a 1st subtraction processing part 3. Based on the result of subtraction, a manipulated variable (u) is operated by a manipulated variable operation part 4. Then the reference controlled variable (ym) is subtracted from a controlled variable (y) at a 2nd subtraction processing part 8 so that the value (e) is acquired. A step width calculating part 9 calculates the step width of the variables (y) and (ym). A response start area detecting part 10 detects the response start areas of both variables (y) and (ym) based in those calculated step widths and the controlled variable given from a noise processing part 10 and undergone the noise processing. Then a model gain calculating part 11 calculates a correction gain based on the variables (y) and (yn) of the response start areas and sends the gain to an internal model storage part 6a. Thus the gain of an internal model is corrected.

Description

Detailed Description of the Invention

[0001]

The present invention relates to an IMC (Internal Model)
The present invention relates to a controller using a control algorithm having a control structure, and particularly to a controller capable of correcting destabilization of control due to an identification error of an internal model.

[0002]

2. Description of the Related Art Conventionally, there has been proposed a controller using an IMC structure control algorithm for performing control by incorporating an internal model in which a control target process is expressed by a mathematical expression.
If this IMC controller is used, a large dead time (time from when hot air comes out of the air conditioner to when the indoor temperature rises) in the process to be controlled (e.g., if this controller is an indoor air conditioner corresponds to the indoor environment) It has an excellent advantage that it can be dealt with even if it exists.

FIG. 12 is a block diagram of a control system using a conventional IMC controller. Reference numeral 33 denotes a first subtraction processing unit that subtracts a feedback amount, which will be described later, from a target value (indoor temperature setting value), and 32 denotes a filter unit that prevents a change in the output of the first subtraction processing unit 33 from being rapidly transmitted. ,
Reference numeral 34 is an operation unit for calculating an operation amount (temperature of hot air or cold air coming out of the indoor air conditioner) which is the output of the controller based on the output of the filter unit 32, and 36 is a mathematical expression approximating the control target process. And a second subtraction process for outputting a feedback amount by subtracting the reference control amount from the internal model 36 from the control amount, and outputting a reference control amount corresponding to the control amount (indoor temperature) as a control result. Part 40 is a process to be controlled.

Further, F, Gc, Gm, and Gp are the transfer function of the filter unit 32, the operating unit 34, the internal model 36, and the process 40 to be controlled, r is the target value, u is the manipulated variable, and d is the d.
Is, for example, a disturbance corresponding to the outdoor environment with respect to the indoor environment,
y is a control amount, ym is a reference control amount, and e is a feedback amount.

Next, the operation of such an IMC controller will be described. First, the first subtraction processing unit 33 subtracts the feedback amount e from the target value r, and the result is output to the filter unit 32. Next, the operation amount u is calculated by the operation unit 34 from the output of the filter unit 32, and is output to the control target process 40 and the internal model 36 of the controller. Then, the second subtraction processing unit 38 subtracts the reference control amount ym from the internal model 36 that approximates the control target process 40 from the control amount y of the control target process 40, and the result is the feedback amount e. A feedback control system that is fed back to the first subtraction processing unit 33 is configured as.

Ideally, the internal model 36 of such an IMC controller is mathematically expressed so as to be exactly the same as the control target process 40, and the operating unit 34 is also used.
Is ideally the inverse characteristic (1 / Gm) of the transfer function of the internal model 36, but the inverse of the dead time element of the internal model 36 is not possible, so normally the dead time element is ignore. Therefore, the control amount y can be obtained by the following equation from the target value r and the disturbance d with such a configuration. y = F * Gp * Gc * r / {1 + F * Gc * (Gp-Gm)} + (1-F * Gm * Gc) * d / {1 + F * Gc * (Gp-Gm)} ... (1 )

Here, the transfer function Gm of the internal model 36 is equal to the transfer function Gp of the control target process 40, and the transfer function Gc of the operating section 34 is the reciprocal of the transfer function of the internal model 36 (1 / Gm = 1 / Gp). Assuming an ideal state equal to, equation (1) becomes y = F × r + (1-F) × d (2)

Further, under ideal conditions where the target value r does not change suddenly, the filter unit 32 is unnecessary and F = 1 can be set, so that the control amount y becomes equal to the target value r (y =
r), it is possible to realize the control without any influence of the disturbance d. Focusing on the disturbance d, the controlled process 4
0 and the internal model 36 have the same dead time with respect to the manipulated variable u even if there is a large dead time, the feedback amount e output from the second subtraction processing unit 38 is equal to the disturbance d.
It is understood that the disturbance d can be suppressed.

Such an IMC controller is usually
Robust stability showing stability when the model identification error between the controlled object process 40 and the internal model 36 becomes large,
And similarly, the design is performed based on the design condition for the robust performance indicating the performance when the error becomes large. In addition, the internal model 36
When determining, the model identification error of the internal model 36 with respect to the control target process 40 is unavoidable to some extent, but control is not performed as expected when the estimation of the model identification error is incorrect. Is done by experts with control knowledge.

[0010]

Since the conventional IMC controller is configured as described above, if there is an error in the internal model identification and the estimation is improper, the controller does not operate as expected and fails. There is a problem in that the operator becomes stable and an operator other than an expert having control knowledge has to give up the use of the IMC controller. In addition, it is particularly effective to correct the gain of the internal model when there is an error in the identification of the internal model, but there is no specific index for correcting the gain and there is the problem that trial and error must be used. It was In order to solve the above problems, the present invention provides a controller having an IMC structure capable of automatically correcting the gain of the internal model to stabilize the control even when the internal model identification includes an error. With the goal.

[0011]

According to the present invention, there is provided a target value filter section for outputting an input target value for control with a characteristic of a time delay of a transfer function, and subtracting a feedback amount from the output of the target value filter section. 1 subtraction processing unit, a target value / disturbance filter unit that outputs the output of the first subtraction processing unit with a time delay characteristic of the transfer function, and an output of the target value / disturbance filter unit based on the parameters of the internal model. When the internal model parameters are stored and the internal model parameters are stored and the internal model parameters are stored, the internal model gain in the parameters is set to this modified gain. An internal model storage unit to be updated, an internal model output calculation unit that calculates a reference control amount from an operation amount based on the parameters of the internal model, and an internal model from the control amount of the control target process A second subtraction processing unit that subtracts the reference control amount output from the force calculation unit and outputs a feedback amount, and an initial value and settling of the control amount and the reference control amount based on the target value, the control amount, and the reference control amount. A step width calculation unit that calculates a step width that is a difference from the value, a noise processing unit that performs processing for reducing noise in the control amount, step widths of the control amount and the reference control amount, and noise output from the noise processing unit. A response start area detection unit that detects the start time and the end time of the response start area where the control quantity and the reference control quantity start to change based on the processed control quantity and the reference control quantity, and the start time and the end time of the response start area And a model gain calculation unit that calculates a modified gain of the internal model from the change rate of the control amount and the reference control amount specified by and outputs the correction gain to the internal model storage unit.

Further, instead of the response start area detection unit, the start time of the response start area is determined based on the dead time of the internal model in the parameters stored in the internal model storage unit, and the step is determined. The step width of the control amount and the reference control amount output from the width calculation unit, the control amount after the noise processing output from the noise processing unit, the end point of the response start region of the control amount based on the reference control amount, the reference control amount It has a dead time reference type response start area detection unit for detecting the start time and end time of the response start area.

Further, instead of the model gain calculation unit, the gain calculated from the rate of change of the control amount and the reference control amount specified by the start time point and the end time point of the response start region and the parameters stored in the internal model storage unit. An incomplete follow-up model gain calculation unit that calculates a modified gain of the internal model by weighting the gain of the internal model therein and outputs the corrected gain to the internal model storage unit is provided.

[0014]

According to the present invention, the target value is input to the target value filter unit, the feedback amount is subtracted from the output of the target value filter unit in the first subtraction processing unit, and the operation amount calculation unit outputs the first feedback value. The operation amount is calculated from the output of the subtraction processing unit and output to the control target process and the internal model output calculation unit. Next, the second subtraction processing unit subtracts the reference control amount from the internal model output calculation unit from the control amount of the control target process, and the result is output as the feedback amount to the first subtraction processing unit. Is configured. Then, the step width of the control amount and the reference control amount is calculated by the step width calculation unit, and the control amount and the control amount based on the control amount after the noise processing output from the noise processing unit are calculated by the response start area detection unit. By detecting the response start region of the reference control amount, the model gain calculation unit calculates the modified gain of the internal model from the control amount of the response start region and the rate of change of the reference control amount, and outputs it to the internal model storage unit. , The internal model gain is modified.

In addition, in the dead time reference type response start area detection section instead of the response start area detection section, the start time of the response start area of the controlled variable is determined based on the dead time of the internal model stored in the internal model storage section. Determined, the step width from the step width calculator, the control amount after noise processing, the end time of the response start region of the control amount, the start time and the end time of the response start region of the reference control amount are detected based on the reference control amount. To be done.

Further, in the incomplete follow-up model gain calculating section instead of the model gain calculating section, the gain calculated from the change rate of the control amount and the reference control amount in the response start area and the internal model storage section are stored. By weighting the gain of the internal model, the modified gain of the internal model is calculated and output to the internal model storage unit.

[0017]

1 is a block diagram of an IMC structure controller showing an embodiment of the present invention, and FIG. 2 is a block diagram of a control system using the IMC structure controller. Figure 1
1 is a target value input section for inputting a target value r set by an operator (not shown) to this controller, and 2 is a transfer function for the target value r from the target value input section 1.
The target value filter unit 3 that outputs with the characteristic of the next delay is a first subtraction processing unit that subtracts the feedback amount e from the output of the target value filter unit 2, and 4 is a first subtraction processing unit based on a parameter from an internal model storage unit that will be described later. The operation amount calculation unit 5 for calculating the operation amount u from the output of the subtraction processing unit 3 of 1 is an operation amount calculation unit 4
This is a signal output unit for outputting the manipulated variable u output from the control target process to a control target process (not shown in FIG. 1).

Further, 6a is an internal model storage unit for storing the parameters of the internal model of the controller, and 6b is an operation as an internal model based on the parameters output from the internal model storage unit 6a and outputs a reference control amount ym. An internal model output operation unit, 7 is a control amount input unit for inputting a control amount y from a control target process to this controller, and 8 is an internal model output operation unit 6b based on the control amount y output from the control amount input unit 7. Output reference control amount ym
The second subtraction processing unit 9 which subtracts from the output value e to output the feedback amount e. The control value y and the reference control amount ym are based on the target value r, the control amount y, and the reference control amount ym. It is a step width calculation unit that calculates a step width that is a difference up to a settling value.

Further, 10 is a noise processing unit for performing processing for reducing noise of the control amount y, 11 is a step width of the control amount y and the reference control amount ym, the control amount after noise processing output from the noise processing unit 10. A response start area detection unit that detects a start time point and an end time point of a response start area, which will be described later, based on the reference control amount ym; Amount ym
Is a model gain calculation unit that calculates a modified gain of the internal model from the rate of change of the internal model and corrects the gain of the internal model stored in the internal model storage unit 6a.

In FIG. 2, reference numeral 4a is inside the manipulated variable calculating unit 4, and the transfer function of the output of the first subtraction processing unit 3 is 1
Target value / disturbance filter unit that outputs with the characteristics of the next delay, 4b
Is also inside the target value / disturbance filter unit 4a.
An operation unit for calculating the manipulated variable u from the output of F, an internal model 6 including an internal model storage unit 6a and an internal model output operation unit 6b, F1 a transfer function of the target value filter unit 2, and F2 a target value / disturbance filter unit. 4a is a transfer function. Also,
du is a manipulated variable disturbance, and can be treated as equivalent to the controlled variable disturbance d by setting the disturbance d = Gp × du.

FIG. 2 shows the target value filter unit 2 of FIG.
The basic configuration of the controller of this IMC structure including the first subtraction processing unit 3, the manipulated variable calculation unit 4, the internal model storage unit 6a, the internal model output calculation unit 6b, and the second subtraction processing unit 8 has a control target process. 40, the disturbance d, and the manipulated variable disturbance du are rewritten as a control system.

Next, the operation of the basic structure of such a controller will be described. The target value r is set by the operator of this controller or the like, and is input to the target value filter unit 2 via the target value input unit 1. The target value filter unit 2 outputs the target value r with the characteristic of the transfer function F1 as shown in the following equation, the time constant of which is T1. F1 = 1 / (1 + T1 × s) (3)

The time constant T1 is the dead time L of the internal model 6 which will be described later, excluding the preset initial value.
With the change of m, it is set as the following equation. T1 = 4 × α × Lm (4) Here, α is a proportional constant, for example, α = 0.3.

Next, the first subtraction processing unit 3 subtracts the feedback amount e output from the second subtraction processing unit 8 from the output of the target value filter unit 2. The target value / disturbance filter unit 4a in the manipulated variable calculation unit 4 includes the first subtraction processing unit 3
Of the transfer function F2 with the time constant T2. F2 = 1 / (1 + T2 × s) (5)

The time constant T2 is also set by the target value filter unit 2
Similar to the time constant T1 of (1), it is changed as shown in the following equation with the change of the dead time Lm excluding the initial value. T2 = α × Lm (6) That is, the time constant T1 is set to four times the time constant T2 as a standard setting.

Similarly, the operation unit 4 in the operation amount calculation unit 4
b is the manipulated variable u from the output of the target value / disturbance filter unit 4a.
Of the internal model storage unit 6
The following expression is obtained by the gain and time constant of the internal model 6 output from a, and is the reciprocal of the transfer function Gm of the internal model 6 excluding the elements of the dead time Lm as in the example of FIG. Gc = (1 + Tm × s) / Km (7) where Km and Tm are gains of the internal model 6, respectively.
It is a time constant.

Therefore, the transfer function of the operation amount computing section 4 as a whole is given by the following equation. F2 × Gc = (1 + Tm × s) / {Km × (1 + T2 × s)} (8) In this way, the manipulated variable u is calculated from the output of the first subtraction processing unit 3 and the signal output unit It is output to the control target process 40 via 5 and is also output to the internal model output calculation unit 6b.

Next, the control target process 40 assumes that the transfer function Gp has the elements of the first-order delay and the dead time.
Can be expressed by the approximate transfer function as follows. Gp = Kp × exp (−Lp × s) / (1 + Tp × s) (9) where Kp, Lp, and Tp are the gain, dead time, and time constant of the controlled process 40, respectively.

The internal model 6 is a mathematical expression of the control target process 40 as described above by these parameters including the gain Km, the time constant Tm, and the dead time Lm stored in the internal model storage unit 6a. Then, the internal model output operation unit 6b calculates the reference control amount ym from the operation amount u output from the operation amount operation unit 4. The transfer function Gm is given by the following equation. Gm = Km × exp (−Lm × s) / (1 + Tm × s) (10)

Next, the second subtraction processing unit 8 subtracts the reference control amount ym from the internal model output calculation unit 6b from the control amount y from the controlled object process 40 input via the control amount input unit 7. Then, the feedback amount e is output. Then, this feedback amount e is input to the first subtraction processing unit 3 as described above. This completes the feedback control system, which is the basic configuration of the controller with this IMC structure.

In such a control system, the step width calculating section 9, the noise processing section 10, the response start area detecting section 11,
The model gain calculation unit 12 corrects the gain Km of the internal model 6 in the first half of the response to the input target value r as follows. FIG. 3A is a diagram showing the target value followability of the control amount y for explaining the operation of the step width calculation unit 9, and FIG. 3B is a diagram showing the target value followability of the reference control amount ym. is there.

Y0 is an initial value of the control amount y, ym0 is an initial value of the reference control amount ym, rm is a set value of the reference control amount ym corresponding to the target value r, and ST is a target value r and an initial value of the control amount y. The step width STm, which is the difference from y0, is the step width that is the difference between the settling value rm and the initial value ym0 in the reference control amount ym.

In FIG. 3A, at time 0 (initial state), the target value r, which is a step input, is input, and the operation amount u is output from the controller to the controlled process 40. As a result, the control amount y is initialized to y0. It is shown that the state changes from and finally matches the target value r and shifts to the settling state.
Further, FIG. 3B also shows a state in which the reference control amount ym output from the internal model output operation unit 6b is similarly settled to the settling value rm.

Then, the step width calculation unit 9 calculates the step width ST of such a control amount y as in the following equation. ST = | r−y0 | (11) Similarly, the step width STm of the reference control amount ym is calculated by the following equation. STm = | rm-ym0 | (12)

Here, the control amount y of the controlled process 40 and the reference control amount ym output from the internal model 6 can be obtained from the target value r and the disturbance d by the following equation. y = F1 * F2 * Gp * Gc * r / {1 + F2 * Gc * (Gp-Gm)} + (1-F2 * Gm * Gc) * d / {1 + F2 * Gc * (Gp-Gm)} ... (13) ym = F1 * F2 * Gm * Gc * r / {1 + F2 * Gc * (Gm-Gp)} + (-F2 * Gm * Gc) * d / {1 + F2 * Gc * (Gm-Gp)}.・ ・ (14)

Then, assuming that the initial value of the gain Km of the internal model 6 is Km0, the initial value ym0 of the reference control amount ym is given by the following equations (13) and (14). ym0 = (y0-d) × Km0 / Kp (15) From the equation (15), if the disturbance d = 0, the control amount initial value y0
And the reference control amount initial value ym0 match the ratio between the gain Kp (here, the estimated value) of the controlled process 40 and the initial gain value Km0 of the internal model 6 as in the following equation. Kp / Km0 = y0 / ym0 (y0 ≠ 0, ym0 ≠ 0) (16)

Therefore, the gain K of the controlled process 40
p can be estimated as in the following equation. Kp = Km0 × y0 / ym0 (17) Further, similarly, the set value r of the target value r and the reference control amount ym is similarly set.
The ratio with m matches the ratio between the gain Kp and the initial gain value Km0. Kp / Km0 = r / rm (18)

Therefore, the equation (12) is expressed by the equations (16)-
From (18), it can be transformed into the following equation. STm = | rm-ym0 | = | r × Km0 / Kp-y0 × Km0 / Kp | = | r-y0 | × Km0 / Kp = | (r × ym0 / y0) -ym0 | (19) Thus The step width calculation unit 9 calculates the step width ST of the control amount y and the step width STm of the reference control amount ym from the formula (1
1) and (19), and outputs them to the response start area detection unit 11.

Next, the response start area detector 11 determines the control amount y and the reference control amount y based on the step widths ST and STm.
Although a response start region of m described later is detected, noise may be added to the control amount y output from the control amount input unit 7. In such a case, the detection of the response start region becomes inaccurate. The gain Km of the internal model 6 will not be corrected properly. Such noise of the controlled variable y includes, for example, noise measured by a sensor that measures the controlled variable y and outputs it to the controlled variable input unit 7.

Therefore, the noise processing section 10 which is a low-pass filter reduces the noise by damping the control amount y as in the following equation. yd (i) = {y (i) + Td × yd (i-1)} / (1 + Td) (20) where yd (i) is the control after the damping process at the sampling time i of this control system. The quantities y and y (i) are the control quantities y at the sampling time i. Further, Td is a damping time constant, and for example, if the sampling period is 1 second, Td = 5 seconds.

Then, the control amount y after this damping process
d (i) is input to the response start area detection unit 11. Next, the response start area detection unit 11 outputs the operation amount u from the operation amount calculation unit 4 in response to the input of the response start area of the control amount y and the reference control amount ym, that is, the target value r, and thus the control amount y. , Reference control variables ym are initial values y0 and ym, respectively.
A region that starts changing from 0 is detected.

FIG. 4A is a diagram showing the response start area of the control amount y for explaining the operation of the response start area detector 11.
FIG. 4B is also a diagram showing the response start region of the reference control amount ym, where i1 and i2 are the start and end points of the response start region of the control amount y, and im1 and im2 are the responses of the reference control amount ym. The start time and the end time of the start area. Further, each number of 1, 2, ... Ny, Ny + 1 ... N, n + 1 is the sampling time i, and the start time of the response start area is 1. FIGS. 4A and 4B correspond to enlarged views of the change start portion in FIGS. 3A and 3B, respectively.

First, the response start area detection unit 11 outputs the step width S of the control amount y output from the step width calculation unit 9.
T, based on the control amount yd (i) after the damping process output from the noise processing unit 10, the start time point i1 of the response start region of the control amount y is detected as in the following equation. | Yd (i) −yd (0) |> β × ST (21) Here, β is a proportional constant, for example, β = 0.05.

That is, the start time point i1 of the response start region of the controlled variable y is the current controlled variable y (see FIG. 4A) as shown in FIG.
In (a), the control amount yd obtained by performing noise processing on y (i))
The difference between (i) and its initial value yd (0) is the threshold value β × S.
It is the first sampling point that exceeds T.

Then, the start time point im1 of the response start area of the reference control amount ym is similarly detected by the following equation. | Ym−ym0 |> β × STm (22) That is, the start time point i of the response start region of the reference control amount ym
m1 is the first sampling time when the difference between the current reference control amount ym and its initial value ym0 exceeds the threshold value β × STm as shown in FIG.

Next, the end time point i2 of the response start area of the controlled variable y is from the start time points i1 to n of the response start area of the controlled variable y.
It is either the time point after sampling (for example, n = 9) or the first sampling time point that satisfies the following equation, whichever is detected first. | Yd (i) −yd (0) |> δ × ST (23) Here, δ is a proportional constant, for example, δ = 0.20. Then, when the sampling time point by the equation (23) is set to the end time point i2, the number of samplings from the start time point i1 to the end time point i2 is set to Ny.

That is, the end time point i2 of the response start region of the controlled variable y is the time point after 9 samplings in the present embodiment (n + 1 time point in FIG. 4A) or the controlled variable yd (i) after the damping process. Of the initial sampling time (Ny + 1 time point in FIG. 4A) when the difference between the initial value yd (0) and the initial value yd (0) exceeds 20% of the step width ST, and thus the Ny + 1 time point in FIG. 4A. Is the end time point i2 of the response start area.

The end time point im2 of the response start area of the reference control amount ym is n sampling points after the start time point im1 of the response start area of the reference control amount ym, or is the same as the sampling number Ny obtained above. From the start time to the time after Ny sampling, whichever is earlier. Therefore, the start time i of the response start region of the controlled variable y
The number of samplings from 1 to the end time i2 and the start time im1 to the end time im of the response start region of the reference control amount ym
The sampling numbers up to 2 match.

As described above, the detection of the end time point is the earlier of the two points. If only the detection by the fixed sampling number n is performed, the control amount y approaches the settling state earlier and the gain Km described later is obtained. This is because the correction of may become too late. Response start area detector 1
1 outputs the start time points i1, im1 and the end time points i2, im2 of the response start area thus detected to the model gain calculation unit 12.

Next, the model gain calculation unit 12 stores the control amount y after the initial value y0, and the control amount y specified by the start time point i1 and the end time point i2 of the response start area, that is, the response start area. Control amount y (i1)
y (i2) is analyzed by the method of least squares, and the control amount change rate (slope) Ay1 is calculated. Similarly, the initial value ym0
The subsequent reference control amount ym is stored, and the reference control amounts ym (im1) to ym (im2) in the response start area are analyzed by the least square method to calculate the reference control amount change rate Aym1.

Then, the model gain calculating section 12 calculates the correction gain Km1 of the internal model 6 by the following equation. Km1 = ρ × Km0 × Ay1 / Aym1 (24) Here, ρ is a safety factor, for example, ρ = 2.0.

The correction gain Km1 is output to the internal model storage unit 6a, so that the gain initial value Km0 stored in the internal model storage unit 6a is updated to the correction gain Km1. Such gain Km (K
The correction of m0) is performed once when the response start region ends for both the control amount y and the reference control amount ym. Therefore, the correction of the gain Km by the step width calculation unit 9, the noise processing unit 10, the response start area detection unit 11, and the model gain calculation unit 12 is performed in the first half of the response to the input of the target value r.

The reason why the gain Km of the internal model 6 is modified as described above is as follows. The target value r, which is a step input, is input to the operation unit 4b through a transfer function filter unit having a delay of about 1st to 2nd order (in the embodiment, the target value filter unit 2 and the target value / disturbance filter unit 4a cause a 2nd order delay) In this case, the first half, which is the response to the input high frequency included in the target value r, is the most unstable state in the overall response.

Therefore, in the IMC controller, it is important for the stability that the error between the internal model 6 and the controlled process 40 is small in the first half of the response including the response start region. Therefore, the gain Km of the internal model 6 is corrected so that the rate of change of the control amount y of the control target process 40 and the rate of change of the reference control amount ym of the internal model 6 in the first half of the response are close to each other as shown in Expression (24). . If the gain Km is corrected in the first half of the response according to the detection result of the response start area, the effect is sufficiently obtained.

By the correction of the gain Km, the change rates of the control amount y and the reference control amount ym may not match from the latter half of the response to the final settling time, but in the latter half of the response approaching the settling state. Since the input of the target value r to the operation unit 4b has a frequency sufficiently lower than that in the first half of the response, the control stability is not so affected. Therefore, the gain Km of the internal model 6 is corrected only once.

When calculating the control amount change rate Ay1, the control amount y (i) before the damping process is used instead of the control amount yd (i) after the damping process. This is because a safe operation is achieved when the control amount change rate Ay1 is calculated to be large, and the influence of noise can be eliminated by using the least squares method. Also, the correction gain Km1
A safer operation can be obtained by using the safety factor ρ for calculating.

Therefore, by controlling the gain Km of the internal model 6 as described above, the process under control 40
It is possible to obtain a stable response even when the model identification of (1) includes an error, and it is possible to avoid deterioration of the control characteristic even if noise is added to the control amount y at such time.

FIG. 5 is a diagram showing target value followability when the controller of this embodiment is used for controlling the height of the liquid level in the tank, and FIG. 6 is output from the control amount input section 7 of this controller. FIG. 7 is a diagram showing the control amount y, and FIG. 7 is a diagram showing the target value followability of the conventional IMC controller. As the conventional IMC controller, the controller of this embodiment that does not correct the gain Km of the internal model 6 is used.

5 and 7, the target value r (dotted line) at 0 second
Enter as a step input of 4 cm of liquid level,
This is a simulation result in which a control amount yt (solid line) which is the height of the liquid surface of the control result is obtained, and this control amount yt is a true control amount before being measured by a sensor not shown.
In FIG. 6, the control amount yt is measured by the sensor, and the control amount y input from the sensor to the control amount input unit 7 is shown, showing that measurement noise by the sensor is added.

Here, the gain Kp of the controlled object process 40, which is the liquid in the tank, is Kp = 0.8 × y + 6.
4, that is, it changes in association with the control amount y.
Further, the time constant Tp of the controlled object process 40 is set to 20 seconds, the dead time Lp is set to 10 seconds, the gain Km of the internal model 6 of this embodiment and the conventional IMC controller is 5, and the time constant Tm is set.
Is 40 seconds and the dead time Lm is 10 seconds. Therefore, there is a model identification error in the gain Km and the time constant Tm.

The time constant T1 of the target value filter unit 2 of this embodiment and the conventional IMC controller is 24 seconds, the time constant T2 of the target value / disturbance filter unit 4a is 6 seconds, and the sampling cycle is 1 second. . The measurement noise is random noise having a maximum amplitude of 0.4 (10% of the step width ST) and an average value of 0. As is clear from the comparison of FIGS.
According to the controller of the present embodiment, it can be seen that a stable response can be obtained as compared with the conventional IMC controller even when the model identification includes an error and the control amount y includes measurement noise.

In the example of FIG. 1, random noise having an amplitude of about 5% at maximum with respect to the step width ST of the control amount y can be applied, but noise having an amplitude larger than this cannot be dealt with. The following measures are required. 8 is a block diagram of a controller having an IMC structure showing another embodiment of the present invention, and the same parts as those in FIG. 1 are designated by the same reference numerals.

Reference numeral 20 denotes a noise processing section similar to the example of FIG. 1 but having a different damping time constant Td. Reference numeral 21 denotes a dead time reference type response start area detection unit, which determines the start time point i1 of the response start area of the controlled variable y based on the dead time Lm of the internal model 6 stored in the internal model storage unit 6a, and the step width Start time im1 of the response start region based on ST, STm, control amount yd (i) after noise processing, and reference control amount ym
And the end time points i2 and im2 are detected. Reference numeral 22 denotes a model gain calculation unit that calculates the correction gain Km1 of the internal model 6 from the rate of change of the control amount y and the reference control amount ym in consideration of noise with an amplitude larger than that in the example of FIG.

The configuration of the controller of the IMC structure of this embodiment is the same as that of the example of FIG. 1 except for the noise processing section 20, the dead time reference type response start area detecting section 21, and the model gain calculating section 22. The basic operation is the same as in the example of FIG. 1, and the noise processing unit 20 also performs the damping process of the control amount y using the equation (20) as in the example of FIG. Is added to the control amount y, the damping time constant Td is Td = 10 seconds when the sampling period is 1 second, for example.

Next, the dead time reference type response start area detector 21 controls the control amount y and the reference control amount ym as follows.
The response start area of is detected. FIG. 9A is a diagram showing the response start area of the control amount y for explaining the operation of the dead time reference type response start area detection unit 21, and FIG. 9B is the response start area of the reference control amount ym. FIG.

First, the dead time reference type response start area detecting unit 21 knows the dead time Lp of the controlled process 40,
That is, the internal model 6 stored in the internal model storage unit 6a
Assuming that there is no identification error in the dead time Lm, the first time when the dead time Lm elapses from the sampling time 0 when the target value r is input as shown in FIG. 9A, the start time of the response start region of the control amount y. i1.

Then, the start time point im1 of the response start area of the reference control amount ym is calculated by using the equation (22) as in the example of FIG. 1, and the difference between the current reference control amount ym and its initial value ym0 is the threshold value. This is the first sampling time point exceeding β × STm.

Next, the end time point i2 of the response start region of the controlled variable y is the first sampling time point that satisfies the following equation. | Yd (i) -yd (0) |> ε × ST (25) Here, ε is a proportional constant, for example, ε = 0.15. The number of samplings from the start time point i1 to the end time point i2 is Ny.

The end time point im2 of the response start area of the reference control amount ym is the time point after Ny sampling from the start time point im1 of the response start area of the reference control amount ym. The dead time reference type response start area detector 21 starts the start points i1, im1 and end point i of the response start area thus detected.
2 and im2 are output to the model gain calculation unit 22.

Next, the model gain calculation unit 22 stores the control amount y after the initial value y0, and the j control amounts y from the rear in the response start region, that is, the control amount y (i2-j).
+1) to y (i2) are analyzed by the least squares method, and the control amount change rate Ay2 is calculated. However, the integer value j is, for example, 2
When 0 and j> Ny + 1, j = Ny + 1 is set and the total control amount y in the response start region is used.

Similarly, the reference control amount ym after the initial value ym0 is stored, and j reference control amounts ym from the front in the response start area, that is, the reference control amount ym (im1).
ym (im1 + j-1) is analyzed by the least squares method, and the reference control amount change rate Aym2 is calculated. However, j> Ny
When +1 is set, j = Ny + 1 is used and the total reference control amount ym in the response start region is used.

Then, the model gain calculating section 22 calculates the correction gain Km1 of the internal model 6 as in the following equation. Km1 = ρ × Km0 × Ay2 / Aym2 (26) This correction gain Km1 is output to the internal model storage unit 6a, and the subsequent operation is the same as in the example of FIG.

As described above, the reason why the start time point i1 of the response start area of the control amount y is calculated from the dead time Lm is that the start time point i1 cannot be detected from the control amount y due to a large noise, and as a result, the response is returned. The detection of the start area is easier than that of the example of FIG. Therefore, even if the noise is small, if the dead time Lp of the controlled process 40 is known and the fluctuation is small, the calculation time and the memory amount required for the detection can be reduced by applying the present embodiment.

In addition, the control amount change rate Ay2 is calculated by using the rear side control amount y in the response start area so that the change rate Ay2 is calculated to be larger than that calculated in the entire area, and the reference control amount change Since the reference control amount ym on the front side in the region is used to calculate the rate Aym2, the change rate Aym2 is calculated to be small, so that the correction gain Km according to the equation (26) is calculated.
The calculation of 1 is larger than that of the example of FIG. 1, that is, it is calculated on the safe side. In this way, it is possible to cope with noise larger than the example of FIG.

FIG. 10 is a diagram showing the target value followability when the controller of this embodiment is used to control the height of the liquid level in the tank as in the example of FIG. 5, and FIG. 11 is the control amount of this controller. 6 is a diagram showing a control amount y output from the input unit 7. FIG. Here, the measurement noise is random noise having a maximum amplitude of 1.2 (30% of the step width ST) and an average value of 0,
All other parameters are the same as in the example of FIG. Figure 1
As is clear from 0, according to the controller of the present embodiment, a stable response can be obtained even when the model identification includes an error and the control amount y includes measurement noise larger than the example of FIG. .

The correction gain Km1 in the examples of FIGS. 1 and 8 may include an error due to the influence of disturbance, etc.
When the model identification is performed with sufficient accuracy, a sudden correction of the gain Km of the internal model 6 may have an adverse effect. Therefore, it is necessary to perform a process that follows the change with time of the control target process 40 while preventing a sudden correction of the gain Km.

Therefore, instead of the model gain calculating unit 22 of FIG. 8, an incomplete follow-up model gain calculating unit for performing the above-described processing is provided to stabilize the control. The configuration of the controller in the present embodiment is exactly the same as the example of FIG. 8 except for the incomplete follow-up model gain calculation unit instead of the model gain calculation unit 22, so this is referred to as an incomplete follow-up model gain calculation unit 22a. The operation will be described using the same reference numerals as those in FIG.

Incomplete follow-up model gain calculation section 22a
Is the control amount y in the response start region detected by the dead time reference type response start region detection unit 21 as in the example of FIG.
(I2-j + 1) to y (i2) are analyzed by the least squares method, and the control amount change rate Ay2 is calculated. Further, the reference control amounts ym (im1) to ym (im1 + j-1) are analyzed by the least squares method, and the reference control amount change rate Aym2 is calculated.

Then, the correction gain Km1 of the internal model 6
Is calculated by the following equation. Km1 = (1−W) × Km0 + W × ρ × Km0 × Ay2 / Aym2 (27) Here, W is a weight and is set within the range of 0 ≦ W ≦ 1. The modified gain Km1 is output to the internal model storage unit 6a, and the subsequent operation is the same as that in the example of FIG.

Therefore, in the example of FIG. 8, the control amount change rate A
The correction gain Km1 based on y2 and the reference control amount change rate Aym2 is directly used as the gain Km of the internal model 6, but in the present embodiment, the gain ρ calculated from the initial gain value Km0 of the internal model 6 and the change rates Ay2 and Aym2. × K
By weighting m0 × Ay2 / Aym2 with the weight W and setting it as the correction gain Km1, a rapid change is prevented. Although the correction of the gain Km is applied to the example of FIG. 8 in the present embodiment, it can be applied to the example of FIG.

[0081]

According to the present invention, the gain of the internal model is automatically corrected during the target value tracking control operation even when the model identification of the controlled process includes an error, so that the control with high accuracy and reliability is performed. Therefore, it is possible to deal with the characteristic change of the control target process. Further, in such a case, deterioration of control characteristics can be avoided even if noise is added to the control amount. Further, since it is possible to prevent the occurrence of troubles due to the identification error of the process to be controlled, it is possible to reduce the work load on the operator who does not have specialized control knowledge.

Further, a dead time reference type response start area detecting section is provided instead of the response start area detecting section, and the start time of the response start area of the controlled variable is determined from the dead time of the internal model stored in the internal model storage section. Therefore, even if noise with large amplitude is added to the control amount, deterioration of control characteristics can be avoided.

In addition, an incomplete follow-up model gain calculation section is provided in place of the model gain calculation section to prevent abrupt correction of the gain of the internal model. It is possible to carry out safe control.

[Brief description of drawings]

FIG. 1 is a block diagram of a controller having an IMC structure showing an embodiment of the present invention.

FIG. 2 is a block diagram of a control system using the controller having the IMC structure of FIG.

FIG. 3 is a diagram showing target value followability of a control amount and a reference control amount.

FIG. 4 is a diagram showing a response start region of a control amount and a reference control amount.

FIG. 5 is a diagram showing a target value followability of a controller having the IMC structure of FIG. 1.

6 is a diagram showing a control amount output from a control amount input unit in FIG.

FIG. 7 is a diagram showing a target value followability of a conventional IMC controller.

FIG. 8 is a block diagram of an IMC structure controller according to another embodiment of the present invention.

FIG. 9 is a diagram showing a response start region of a control amount and a reference control amount.

FIG. 10 is a diagram showing target value followability of a controller having the IMC structure of FIG.

11 is a diagram showing a control amount output from the control amount input unit of FIG.

FIG. 12 is a block diagram of a control system using a conventional IMC controller.

[Explanation of symbols]

 2 Target value filter unit 3 First subtraction processing unit 4 Manipulation amount calculation unit 4a Target value / disturbance filter unit 4b Operation unit 6 Internal model 6a Internal model storage unit 6b Internal model output calculation unit 8 Second subtraction processing unit 9 Steps Width calculation unit 10, 20 Noise processing unit 11 Response start area detection unit 12, 22 Model gain calculation unit 21 Dead time reference type response start area detection unit

Claims (3)

[Claims] 1. A reference control amount corresponding to a control amount of a control target process, which is a control result, is calculated by calculating an operation amount to be output to a control target process from a control target value, and using an internal model expressing the control target process by a mathematical expression. Control is performed by calculating and feeding back the difference between the control amount and the reference control amount I
In a controller having an MC structure, a target value filter unit that outputs a target value of input control with a characteristic that a transfer function has a time delay, and a first subtraction processing unit that subtracts a feedback amount from the output of the target value filter unit. , A target value / disturbance filter unit that outputs the output of the first subtraction processing unit with a time delay characteristic of the transfer function, and an operation amount is calculated from the output of the target value / disturbance filter unit based on the parameters of the internal model. An operation amount calculation unit including an operation unit that outputs the internal model, and a parameter for the internal model is stored. When a correction gain of the internal model is input, the gain of the internal model in the parameter is updated to the correction gain. A model storage unit, an internal model output computing unit that computes a reference controlled variable from the manipulated variable based on the parameters of the internal model, and a controlled process A second subtraction processing unit that subtracts the reference control amount output from the internal model output calculation unit from the control amount and outputs the feedback amount; and a control amount and a control amount based on the target value, the control amount, and the reference control amount. A step width calculation unit that calculates a step width that is a difference between an initial value and a set value of a reference control amount, a noise processing unit that performs a process of reducing noise of the control amount, and a step of the control amount and the reference control amount A width, a control amount after noise processing output from the noise processing unit, and a response start region detection unit that detects a start time and an end time of the response start region where the control amount and the reference control amount start to change based on the reference control amount. , A model gain that calculates a correction gain of the internal model from the rate of change of the control amount and the reference control amount specified by the start time point and the end time point of the response start region and outputs the correction gain to the internal model storage unit. Controller; and a down calculator. 2. The controller according to claim 1, wherein instead of the response start area detection unit, the response start area where the control amount starts to change based on the dead time of the internal model in the parameters stored in the internal model storage unit. Of the control amount output from the step width calculation unit and the step width of the reference control amount, the control amount after noise processing output from the noise processing unit, and the response start of the control amount based on the reference control amount A controller comprising a dead time reference type response start area detection unit for detecting an end time of an area, a start time and an end time of a response start area of a reference control amount. 3. The controller according to claim 1, wherein instead of the model gain calculation unit, it is calculated from a change rate of a control amount and a reference control amount specified by a start time point and an end time point of a response start region. Gain and the gain of the internal model in the parameters stored in the internal model storage unit are weighted to calculate the modified gain of the internal model and output to the internal model storage unit. A controller characterized by having.