JPS59133605A - Pid controller of sample value - Google Patents

Abstract

PURPOSE:To make a monitor or an expensive monitor equipment unnecessary by providing a characteristic change detecting part, which detects the characteristic change of a process, to monitor the characteristic change of the process in on-line. CONSTITUTION:The operation signal which is subjected to PID operation in a sample value control operating part 5 is applied to an operating process 1 through a sample holding part 2 to control the process 1 so that a deviation signal is reduced for every sample period K. In this case, if the characteristic of the operating process is not changed, model errors of a characteristic change detecting part 13 are zero, and estimated model error signals have DC components because they are deviated. If only, for example, a gain of the characteristic of the operating process is changed, DC components are generated in the detecting part 13, and the model error for the case, where the gain is changed, out of estimated model errors becomes zero, and error models for the other cases are not zero. That is, the characteristic change of the operating process is detected by the fact that estimated model errors for cases become zero.

Description

[Detailed description of the invention] [Technical field to which the invention pertains] This invention relates to sample value PID control that has a function of identifying process dynamic characteristics during closed-loop control and automatically adjusting optimal control constants based on the identification results. The present invention relates to a device, and particularly to a sample value PID control device that can detect changes in characteristics of a process during operation and automatically readjust control constants.

[Prior art and its problems]

Since the conventional sample value PID control device manually activates the automatic checkoning function of the control constants, there are the following problems in readjusting the control constants in response to changes in the characteristics of the process during operation.

(1) Workers must constantly monitor changes in process characteristics, so manpower cannot be omitted. Furthermore, expensive equipment such as a monitoring recorder and a television monitor is required.

(2) If the process is operated without noticing changes in process characteristics, there are problems such as a decrease in product quality, a decrease in plant efficiency, and a decrease in safety.

(3) Even if a change in process characteristics is noticed, the automatic chicorning function is activated manually, making it impossible to make prompt adjustments.

[Purpose of the invention]

In order to solve the above problems, the present invention provides a sample value PI
By equipping the D control device with a characteristic change detection unit that detects changes in process characteristics and conducting online monitoring of changes in process characteristics, the conventionally required monitors or expensive monitoring equipment can be omitted. Furthermore, by configuring multiple estimation models for processes with different characteristics from the process specifications after identification is completed, and detecting changes in characteristics from these estimation models, control constants can be automatically determined without performing an identification test. It is necessary to readjust the In this way, on-the-fly monitoring of changes in process characteristics during operation and readjustment of control constants can be fully automated, allowing plant operation without deteriorating product quality, plant efficiency, or safety. Moreover, it is an object of the present invention to provide a sample value PID control device that can save manpower.

[Summary of the invention]

ShunIn the present invention, since the unknown parameters of the gross process become known after the identification paper is completed, characteristic change models of multiple processes are constructed based on this, model errors are calculated, and then the parameters of the processes in operation are calculated. This is a sample value PID control device that performs an identification test based on a characteristic change model of a process in which the model error in estimating the characteristic change becomes zero, and readjusts the control constant. Further, the sample value PID control device uses an auto-tickoning function to readjust control constants when all model errors of the estimated process characteristic change model are not zero.

〔Effect of the invention〕

, the effects of the sample value PID control device of the present invention are shown below.

(1) Detection of changes in process characteristics can be automatically monitored online, which saves manpower and does not require expensive monitoring equipment.

(2) Since changes in process characteristics are not overlooked, high product quality and plant safety can be maintained at all times.

(3) The readjustment of control constants when process characteristics change can be automated, allowing prompt response. What's more, you can also save on manpower at this time.

[Example of the present invention]

An embodiment of the present invention will be described with reference to FIG.

FIG. 1 is a block diagram showing the configuration of a sample value PID control device of the present invention.

Process 1 to be controlled constitutes a closed loop system with a sample value control calculation section as shown in the figure. r (t) in the figure is the target value,
e (t) is the deviation, u (t) is the operation signal, y (t)
is the process output, and ci(t) is the disturbance that changes the equilibrium point of the process [7]. Note that the letter tg in 0 indicates a real time signal, and k indicates a signal ramped by the sampler 4.

Process 1 during operation generates a deviation signal e every sample period.
The operation signal U (k) (Uo (k)
= U(k)) is added and controlled via sample hold 2. The l1iii difference signal e (t) is obtained by adding the target value r (t) and the process output y (t) at addition point 3.

Auto-determines the control constants of this sample value control calculation section.
1. In the case of auto-tuning, first, the initial values of the proportional gain integral time constant and the differential time constant (Kco) are input to the sample value control calculation unit 5 when auto-tuning is performed.

Ti□, Tdo), and further determine the F'orgetting Factor λ of the pulse transfer function identification unit 9 and the amplitude of the identification coefficient of the identification signal generation unit 7, and apply the data to each block of the sample value PID control device as indicated by the dotted line in the figure. Start it as shown.

When this pressure is applied, a persistently exciting identification signal vO(k) that satisfies the identification conditions of a closed-loop system process is added to the operation signal UO(k) and is injected into the process as shown in the figure.

At this time, the input signal U (k) of the process and the sampler 8
The process output signal y(k) sampled in is time-series processed by a pulse transfer function identification unit 9, which will be described later, to calculate two-region pulse transfer functions, and the result is transmitted to a transfer function calculation unit 10 to identify pulses in the S region. The result is converted into a transfer function, and the result is further used to calculate a PID control constant in the sample value control constant calculation section 11, and is set in the sample value control calculation section 5.

By sequentially performing the above processing every sample period, it is possible to determine the optimal control constants that match the characteristics of the process to be controlled.

Here, as process identification progresses, tuning is stopped until the parameters of the transfer function in the S region reach a constant value.

Then, the injection of the identification signal vo(k) from the identification signal generator 7 is stopped, and only the operation signal UO(k) which is subjected to pure control calculation is applied to the process 1. Furthermore, the pulse transfer function identification unit 9, transfer function calculation unit 10, and sample value control constant calculation unit 11 are stopped, and the control constant (
Kc, Ti', Td).

Therefore, since the input signal is not a persistent or egressive signal, the characteristics of process 1 cannot be identified even if the characteristics of process 1 during operation change. Identification including point D (t). A pulse transfer function identification section 9 is used. Pulse transfer function 1? A process model of the J1 constant section 9 is shown in FIG. As shown in the figure, process model, noise model,
and a disturbance model that changes the equilibrium point.

Here, U(k) is the operation signal, ε(k) is the white noise, and D
is a DC signal and y(k) is a process output.

The process model in Figure 2 is identified using the equation ε(k
-i)+ε(k)+kan (1) Here, YO indicates the equilibrium point of the process output, and do indicates the equilibrium point of the process input.

Transforming equation (1), Y(k) = similar to ψ('-1) + ε(k)'
<31"?' = (Ω+ "' + Q +bl
+ ...I Q, E+ + ..., a, D)
(4) ψ()c)=(-Y(k-1) ,-・,-Y
, (-to-m), U(k-i-1).

-, U(k-11-m), ・++, U(k-11-
m), t(k-1)-,-.

ε(k-m) , 1) (5)
Identification is performed as follows.

The pulse transfer function Gp (Z'') of the process is as follows.

The sample value PID control constant is parameter = ai (i = 1
...m), bx (1=L-nee n).

Next, a method for detecting characteristic changes in the process of the present invention will be explained in detail. As mentioned above, after the process has been identified, the parameters k(z') cold <z'), D, are known and do not change unless the characteristics of the process change or the equilibrium point of the process changes. . In addition,
Since the process output and input of (Y(k)) and (U(k)l can be measured, the public (Z21) after the identification is completed,
The model error can be calculated as follows using (Z')+, (÷(k)), and (k).

(7) Characteristic change detection section 1 in FIG. ．． 3 is a block that calculates formula (9).

If there is a characteristic change in the process during operation, a direct current component will occur in the model error, and the characteristic change can be monitored online.

Next, a method for readjusting the control constants when the characteristics of the process during operation change will be explained in detail.

The above equation (6) can be converted into an S-domain pulse transfer function by the transfer function calculation unit 10 as follows.

Here, the parameter of S (go'+'C+g2+g3
+...) represents the gain and time constant of the process. For example, the gain is 1/go and the time constant is gt, /go.

In general, if the characteristics of the process during operation change by a factor of 10, readjustment of the control constants is required.

Therefore, since changes in process characteristics are generally continuous, in the present invention, if only the process gain changes by ±10 degrees,
A process model is created by estimating combinations of changes in the characteristics of the process, such as when only the time constant changes by ±101, and when the gain and time constant change by ±10%.

In other words, the transfer function of the process in the case of a 1% change is estimated as follows.

Here, for the gain, the delay time is 11JIL, and the time constant is 1'f.
By estimating +T21T3, go +g1'
Estimate tg2'9g3'.

The characteristic estimation calculation unit 15 in FIG. 1 is a block that performs this, and the characteristic change estimation coefficient is initially set by the controller 14.

Furthermore, the following 2-conversion to the Z domain is performed from equation (9) to obtain the estimated process parameter '(z'>).

l^t Find B(Z').

In this way, characteristic change models of a plurality of processes are constructed using the estimated parameters obtained, and the Sodel error of each is calculated in the same way as in the characteristic change detecting section 13.

1=1 Yo=constant The estimation error calculation unit 16 in FIG. 1 is a block that calculates the model error of equation (11) obtained from the process model of equation (8).

In this way, if the characteristics of the process during operation do not change, the model error of the characteristic change detection section is zero;
Since the estimated model error signal is shifted, there is a direct current component.

However, if the characteristics of the process during operation change, for example, only the gain changes by 10 degrees, a DC component will occur in the characteristic change detection section, and among the estimated model errors, the model error in the case where the gain changes by 10 degrees will be zero. In other cases it will not be zero.

In other words, when the model error for the estimated case becomes zero, changes in the characteristics of the process during operation can be seen. Furthermore, the control constant can be quickly determined based on equation (9) estimated for that case. Therefore, the control constants can be readjusted without overhauling.

The above explanation is shown in FIG. 3 in relation to model errors.

It can be seen from the figure that cases of changes in process characteristics during operation can be quickly determined from model errors.

As described above, the present invention is a sample value PID control device that can adjust control constants in response to changes in process characteristics during operation by estimating changes in process characteristics and calculating model errors. .

In addition, if the characteristic change of the process changes more than estimated, the model error of the characteristic change detection section will be larger than the initial model error of the estimated characteristic change, so this will be detected and the sample value PID controller will automatically This allows the chiconing function to be started automatically.

[Brief explanation of the drawing]

Fig. 1 is a block diagram showing the configuration of the sampled value PID control device of the present invention, Fig. 2 is an explanatory diagram of a process model for parameter identification used in the sampled value PID control device of the present invention, and Fig. 3 is a block diagram showing the configuration of the sampled value PID control device of the present invention. FIG. 4 is a characteristic change detection according to the invention and an explanatory diagram thereof. 1... Process, 2... Sample hold, 5...
- Sample value control calculation section, 7...Identification signal generation section, 9
...Pulse transfer function calculation unit, 10...Transfer function calculation unit, 11...Sample value control constant calculation unit, 12...
Identification end determination unit, 13...Characteristic change detection unit, 14...
・Control unit, 15...Characteristic estimation calculation unit, 16.
...Estimation error calculation unit. Agent Patent Attorney Kensuke Chika (l.1 or 1 person) Figure 1 Figure 2 Figure 3

Claims (1)

[Claims] In a device having a sample value PID control calculation unit for controlling a process to be controlled by a sample value, an identification signal consisting of a versistine exciter signal is provided in a control loop controlled by the sample value PID control calculation unit. an identification signal generation section to apply, an operation signal obtained by adding the identification signal generated by the identification signal generation section to the output signal of the sandal value PID control calculation section, and an operation signal obtained by sampling the control amount of the process. A pulse transfer function identification unit that inputs process signals and identifies parameters of the process from these operation signals and process signals, and a region of the Laplace operator S from the pulse transfer function of the process obtained by this pulse transfer function identification unit. a transfer function calculation unit that calculates a transfer function of the transfer function calculation unit; a sample value control constant calculation unit that calculates a control constant of the sample value PID control calculation unit from the calculation result of the transfer function calculation unit; and a result of the transfer function calculation unit. an identification end determination section that determines the end of identification based on the identification end; and a characteristic change detector that calculates a model error of the process from the parameters of the pulse transfer function identification section after the end of the identification, the operation signal of the process after the end of the identification, and the output signal of the process. a characteristic estimation calculation unit that estimates and calculates the change axis of the process by changing the parameters of the transfer function calculation unit after the completion of the identification; Sample value PI equipped with an estimation error calculation unit that calculates a model error of the estimated process
D control device.