JPS60218105A - Control device - Google Patents

Abstract

PURPOSE:To strengthen suppressing force against disturbance by identifying the dynamic characteristics of a controlled system, operating and setting up a control constant through a model and PID-operating an error signal between the outputs of the model and a control system to superpose the error signal to the controlled system. CONSTITUTION:An identification signal is inputted to a system control box 16, and during the control of a closed loop, an identification signal generator 12 and an on-line identifier 14 are actuated to identify the identification parameters (ai), (bi) of the controlled system 1 in the on-line. The transmission function, integration gain, etc. of the controlled system 1 are operated by a design block 15 to which said parameters (ai), (bi), a response shape factor alpha and a robust (low sensitivity) gain gamma are inputted and the factor of a discrete time model in the control system is calculated and outputted on the basis of said operated results. A control system mode 7 calculates a model output and a compensated output obtained from a sample value PID compensator 9 is fed back to an operation from a sample value PID compensator 9 is fed back to an operation terminal by using said factor calculated by the design block 15. Consequently, the robust control system resisting against disturbance can be automatically constituted.

Description

[Detailed Description of the Invention] [Technical Field of the Invention] The present invention relates to a sample value control device for a controlled object, and in particular, to a method for identifying the dynamic characteristics of a controlled object during closed loop control and performing control based on the identification result. The present invention relates to a control device having a function of automatically adjusting (tuning) constants, and further having a function of preventing the control performance of a control system after tuning from deteriorating due to changes in the dynamic characteristics of a controlled object.

[Background technology of the invention and its problems]

A control device that controls the flow rate, temperature, pressure, etc. of a plant needs to appropriately adjust its control constants according to the dynamic characteristics of the controlled object. On the other hand, in recent years, with energy-saving operation of plants, there have been an increasing number of cases in which the dynamic characteristics of a controlled object change during operation. What has been done so far regarding changes in dynamic characteristics? ) Two control techniques are known: the Neil control method and the model-norm adaptive control method.

These two methods are control methods that belong to the class of adaptive control in a broad sense.Firstly, the former dyne schedule control method inputs auxiliary signals related to the controlled object that are directly related to changes in dynamic characteristics. This method changes the control constants according to the dyne schedule curve. Therefore, it is necessary to clarify the relationship between the dynamic characteristic change and the corresponding gain schedule in advance.

On the other hand, the model reference adaptive control method is a control method used when the dynamic characteristics of the controlled object are unknown, and the control constants of the controller are adjusted so that the error between the output of the control system and the model output of the control system is zero. This is a control method that makes adaptive adjustments. This method has the advantage that it can be used when the dynamic characteristics of the controlled object are unknown, but it is foolish and may not provide sufficient performance depending on the controlled object due to unknown disturbances, observation noise, etc. However, it takes a certain amount of time to adapt when the dynamic characteristics change, and furthermore, there are problems in that the operation signal tends to fluctuate greatly in a transient state.

[Purpose of the invention]

The present invention improves the performance of the conventional control device described above, and aims to provide a control device that is automatically tuned to a control system that is low in sensitivity or robust to changes in the dynamic characteristics of a controlled object. .

[Summary of the invention]

The present invention provides means for identifying dynamic characteristics of a controlled object during closed-loop control, means for calculating control constants using a desirable model of a control system from the identification results, and automatically configuring a desirable model for a control system. The control device is configured by performing sample value PID calculation on the error signal between the output of the desired model and the output of the control system, and using a feedper to superimpose the PID calculation output on the controlled object.

〔Effect of the invention〕

By adopting the above-mentioned configuration, the control system as a whole is not sensitive to changes in the dynamic characteristics of the controlled object, or is susceptible to disturbances applied to the control system. , its suppressive power will be strengthened. Since the system is automatically tuned to such a control system, it is possible to significantly save the manpower involved in design and adjustment.

In addition, since the control system can be made less sensitive (robust) to changes in the dynamic characteristics of the controlled object, there is no need for gain scheduling, and there is no need to constantly adapt the control constants to changes in the dynamic characteristics. The response of operation signals and outputs when dynamic characteristics change can also be made smooth.

[Embodiments of the invention]

Fig. 1 is a block diagram showing one embodiment of the present invention.

First, to explain the configuration of the embodiment, y(t) is an output signal of the controlled object 1, u(t) is an input signal or an operation signal, and the controlled object 1 has a disturbance a(t) on the operation signal side. It has been entered. The output signal y (t) is sampled by the first sensor 2 at every sampling period τ to generate a discrete time output signal y (k). Here, k means τ=t. Also, r
(t) is a target value signal of the control system, which is similarly sampled by the second sampler 3, and is a discrete time target value r*←)
is generated. The deviation calculator 4 calculates r*(k) and y*(
k) Calculate the deviation #*(k) according to the first equation.

to e)=y~)-y"(k)...The first equation main integral calculator 5 integrates the deviation e"(k) using the integrator in K, and outputs the integral output U. *Calculate (k).

u%) = u''(k-1) 10-e(k) -...
Second Formula % Formula % The feedback compensator F(i-1) 6 inputs the output signal y~) and calculates u/''(k).

u 1Oc) -F('g-1') ・y''Qc) ・
...In the third equation control system model 7, the model number 4 parameters set by the design block 15 described later and r*(k)
The model output y:(k) is calculated using

yM%)=GM(Z-' + τ+'rα2.α,
・")-r"(k)...Fourth formula The output error calculator 8 calculates the error ε-) between the output y*(k) and the model output yyei) as follows.

to e) = y ~) - y 謹) ・・・5th formula sample value PI
In the D compensator 9, the output error -(k) is input, and using the standard meter set in the design pro 15, the U-
[Yes]) is calculated as follows.

ug%)=H(Z-', r, a, α2.α5
＋・”e Kr r)” “QC)...
The sixth equation ug*(k) is added to the above-mentioned uih> in an adder 10, and the added output is calculated as an integral output, "(k), etc., in an adder/subtractor 11, and becomes an input signal." (k) is generated.

u%)=u,%)+v%)-u/ (k)-u-(k)
. . . Equation 7) is a signal generated by the identification signal generator 12 and used to identify the controlled object 1.

The input signal ``(k) is held for a second sample period by the zero-order hold 13 and becomes the input signal u(1).In the online identifier 14, the input U~) and the output y*(k)
Input the time series data of , and calculate the coefficient as(i=x) of the following discrete time model of controlled object 1.

2 #...' l nl) bl (1-1+"'e
nl) ), however, A ('r, -, 1') y*(
k)=B (z-1) u*Qc) ”・Identify the eighth equation using the online least squares method.

In the design block 15, the identified discrete-time model coefficients al and b1 of the controlled object 1, the parameter α that defines the response shape of the control system, and the robust dyne r are inputted to the integral dyne of the main integral calculator 5. and the coefficients 10 + / 1 r of the feedback compensator 6 and τ, σ, α1 . used in the control system model r. coefficients such as α2°, τ, σ, α4, etc. used in the sample value PID compensator 9. α2. ...,
Coefficients such as r are designed. In the system control block 16, the identification start is started.
In response to the signal, the operating status of the identification signal generator 12, online identifier 14, etc. is managed.

Next, the operation of this control device will be explained. First, the integral dyne and feedback coefficient f. , f are set to appropriate constants for stable operation of the control system, and an open 1th signal is input to the system control block xg. The identification signal generator 12 and online identifier 14 are operated during closed loop control.

At the same time, an exciting identification signal V~) is generated and injected into the control system. Therefore, since the input u''(k) contains an exciting signal component that is independent of the output y*o=), the input U~) and the output y even during closed loop control.
”k) to the coefficient a1.J of the discrete-time model of controlled object 1
is identified by the following online least squares filter9- As the identification progresses, the identification error signal η(k) becomes smaller, and the change in the unknown/mother meter vector (k) becomes smaller. The system controller 16 detects this, stops the operation of the identification signal generator 12 and the online identifier 14, and also stops the identification signal generator 12 and online identifier 14.
Activate the design block 15 into which J, response shape coefficient α, and pbust dyne r are input. In the design block 15, first, the transfer function QP(a) of the controlled object 1 is calculated from the identified parameters al, J and the sampling period τ.

Next, partial model matching is performed using the control system model GM (m + σ, α,) defined by the response shape coefficient α and the sampling period τ, and the integral 10− gain and feedback coefficient are f. , fl,
From the start-up time σ of the control system determined at this time, the coefficients σ, α2°α6, of the discrete time model of the control system. ..., is calculated and output.

Based on these coefficients, first, in control system model 7,
A model output "M" (k) is output based on the fourth equation. On the other hand, σ, α calculated in design block 15
2. α3. ..., r, K, the sample value PID
The compensator 9 inputs the output error ε(k) and calculates ug''(
k). This signal u,1) is composed of the disturbance applied to the control system and the change in the dynamic characteristics of the controlled object 1.By feeding back this signal u-(k) to the operating end, the dynamic characteristics can be changed. A robust control system that is resistant to changes and also to disturbances will be automatically constructed.

In addition, in the design block 15, α2. α3. While designing α4, σ, fo
, f, etc. are designed.

In addition, the reference model for control system design is GM (s, σ,
α2. α, ) then GM(lI, σ, α2.α3...)=110+σ@
剌z(σB)2+α3(σl)3+α4(σs)'
-1-...), we can construct a discrete-time model.

GM(Z-' r τ* ' *α2 +α51"')
For (8+ ' r α2 r α5 t"')1゜...
・Equation 15 Next, K*IO*f is designed by the following calculation.

(11) ... Using the positive minimum machine σ of Equation 16, K r for fl is calculated as follows.

Also, σ, τ, α1 (1=1.2
．． ...), γ, the arithmetic unit of the sampled value PID compensator 9 is calculated as 13- (12) As described above, in the present invention, the transfer function of the controlled object is identified on-line during closed-loop control, and from the identification result, , since each compensator and the desired model of the control system are configured, after the compensator is configured, the control system becomes robust against changes in the dynamic characteristics of the controlled object, so a robust control system is automatically configured. It turns out.

In this embodiment, a robust I-PD control device has been described, but it is also possible to configure a robust PID control device using a sample value PID control calculator as a main control calculator.

[Brief explanation of the drawing]

The figure is a pull diagram of a control device according to an embodiment of the present invention. DESCRIPTION OF SYMBOLS 1... Controlled object, 2, 3... Sampler, 5... Main integral calculator, 6... Feedback compensator, 7...
Control 14- Control system model, 8... Output error calculator, 9... Sample value PID compensator, 12... Identification signal generator, 14.
...Online Identifier, 15...Design Block.

Claims (1)

[Claims] a control calculator that calculates a control calculation output signal from a target value signal and an output signal of a controlled object; a dynamic model of a control system that receives the target value signal and calculates an output signal on the control system; a subtracter that calculates an output error signal from the difference between the output signal and the model output signal; and a PID calculation unit that inputs the output error signal and performs a PID (proportional, integral, differential) calculation. A subtracter that subtracts the output signal of the control calculation output signal from the control calculation output signal, and a control device that uses the output of the subtracter as an operation signal for the controlled object, an identification signal generator, and an online identification signal generator that identifies the dynamic characteristics of the controlled object. an identifier, and a design block that calculates control constants used in the control calculation unit, control constants of the PID calculation unit, and parameters of the dynamic model from the identification results, and the design block calculates the dynamic characteristics of the controlled object during closed-loop control. identify,
A control device characterized by having a function of automatically calculating each constant from the identification results.