JPS6121505A - Process controller - Google Patents

Abstract

PURPOSE:To minimize a change in a process variable against any external disturbance and to attain simple and easy conventional application by providing a gain scheduling section and a feedforward control model gain adaptive section. CONSTITUTION:The gain scheduling section 33 has a function correcting the gain of a feedback FB control output signal in response to the magnitude of an external disturbance change and relates an external disturbance compensation signal D.K to a coupling coefficient C set in response to a process variable. Then the gain of an FB control output signal is corrected sequentially in a direction corresponding to the load reduction by using a gain correcting coefficient obtained in this way so as to stabilize the control earlier. Further, a feedforward FF control model gain adaptive section 34 compares the FF control output signal with an operating signal MV so as to zero the FB control output signal, the gain of the FF control model is corrected and the optimum control to an unknown external disturbance is executed. Then the change in the process variable is minimized against any external disturbance change and simple and easy conventionality is attained.

Description

DETAILED DESCRIPTION OF THE INVENTION [Technical Field of the Invention] The present invention relates to a process control device that optimally combines feedback control and feedforward control and allows a control system to optimally adapt in response to disturbance changes.

[Technical background of the invention and its problems]

In recent years, in process control, adaptive control (adapt 1Yecontrol) has been developed that can flexibly respond to external disturbances such as load changes and environmental changes, and can optimally adapt to these changes.
The demand for this is becoming stronger.

The basic conditions of this adaptive control are (1) that changes in process quantities can be kept to a minimum even when disturbances are in a state of sudden change; Q) Ability to respond optimally to any excitability changes in the process. (3) It has a simple and general-purpose configuration. is required.

Conventional typical examples of this adaptive control include (
1) Self-tuning regulator (8TR), (
2) There is model reference adaptive control (MRAO8). However, these control methods focus on control results, that is, changes in process quantities, and modify controller parameters based on numerical analysis such as identification methods and stability theory. is the basis, and is directly affected by external disturbances. For this reason, it can only be applied to processes in which disturbance changes, process characteristics, etc. change slowly in a specific pattern, and the above three basic conditions have not been satisfied in normal processes in which various types of liquefaction occur.

This will be explained below using an example of 8TR. STR
The method identifies unknown parameters from process variables and uses the identified values to modify the parameters of the adjustment section.The specific configuration is shown in Section 3.

In the figure, a set value l and a process variable 2 are introduced into a deviation section 3, and deviation signals of both sets are supplied to an adjustment section 4,
Based on this signal, the adjustment section 4 adjusts P (proportional), ■ (integral),
A D (differential) calculation and the like are performed to obtain an adjustment output signal 5t, which is output to the adder 6. Further, the adder 6 is supplied with a search signal such as an M-sequence signal for searching the process characteristics from the search signal generator 7, and an operation signal 8 is used as an operation signal to process the process 9. and is output to the process characteristic identification mechanism 10.

On the other hand, a disturbance 11 is applied to the process 9, and the process variable 2 that changes due to this influence is fed back together with the deviation section 3 to the process characteristic identification mechanism lO. The unknown parameters of the process are sequentially estimated based on the parameters using an appropriate identification method, and outputted from P to the parameter determining mechanism 12. The PID parameter determination mechanism 12 determines a PID parameter based on this unknown parameter, which is output to the adjustment section 4, where the parameters of the adjustment section 4 are updated and corrected to the optimum control state.

The STR system configured as described above has the following fatal drawbacks as a control device for industrial applications.

(1) A PID model that focuses on changes in the process quantity 2 (because it is a parameter correction, it is directly affected by disturbances.) (2) The process characteristics are determined by looking at the process control results based on the previously output operation signals. Because a new operating signal is obtained by identifying the PID parameters and modifying the PID parameters, the process often changes by the time the operating signal is identified to the previous process characteristics, changing to a new state different from the identified value. Even the painstaking effort to correct the parameters will be wasted, and the resulting error will actually cause the control to become erratic.

In actual identification, when a new operation signal is applied 2.3 times and the same control result is obtained, the identification is performed using photons.
Until (process waste time + process time constant) x 3
It takes ~4 times as long to make a fake. For this reason, in a normal actual process where disturbances and process characteristics vary arbitrarily and rapidly, it is impossible to follow the variations and it is almost impossible to adapt.

(3) As a search signal, an M-sequence signal, etc., which has positive and negative pulses and has an average of zero and does not affect the process, is devised and added, but if the amplitude is small, the adjustment output signal 5
If it is too large, it will cause a shock to the operating end, etc.

(4) The theory of identification methods is complex, and qualitative and quantitative relationships cannot be easily understood.

[Purpose of the invention]

The present invention aims to eliminate the above-mentioned drawbacks and provide a process control device that can fully satisfy the basic conditions required for adaptive control. Take advantage of and gain from disturbances.
The effect of the information that cannot be obtained is resolved by modifying the coefficients of the feedforward control model so as to minimize the output signal of the feedback control that is output as a result.

[Summary of the invention]

In order to achieve the above object, the present invention includes a feedback control means that predicts the influence of a disturbance and performs advance control, and a gain schedule that adjusts the gain of an output signal of the feedback control according to the magnitude of a change in the disturbance. and feedforward control model gain adaptation means for automatically correcting the coefficients of the feedforward control model so that the output signal of the feedback control becomes zero.

[Embodiments of the invention]

Hereinafter, the present invention will be explained using one embodiment with reference to the drawings. Figure 1 shows the functional configuration of a process control device according to an embodiment.
FIG.

In the figure, 20 is a process to be controlled. First, the feedback control (hereinafter referred to as FB control) system for this process 20 will be explained. Process quantities such as temperature, pressure, flow rate, level, concentration, etc. output from the process 20 and representing its state are detected as control quantities by the process quantity detector 21, and a control signal Pv proportional to the quantity is output to the deviation section 22. be done. The deviation section 22 obtains the deviation between the control signal PV and the set value signal S and converts the control deviation signal into F.
It is output to the B control adjustment section 23. F/B control adjustment section 23'
performs PID or I-FD calculation or the like on the control deviation signal, and outputs an FB control output signal to the multiplier 24. The multiplier 24 multiplies this FB control output signal by a gain correction coefficient output from a gain scheduling section 33 (described later), and outputs the FB control output signal whose gain has been corrected according to the magnitude of the disturbance change to the adder 25. The adder 29 adds and synthesizes a disturbance compensation signal D-K from a feedforward control (hereinafter referred to as FF control) system, which will be described later, to this gain-corrected FB control output signal, obtains a manipulation signal MV, and processes it. It is output to 20.

Next, the FF control system will be explained. Disturbances such as load fluctuations and environmental changes are applied to the process 20, and these disturbance changes are detected by the disturbance detector 30 and output to the FF control model 31 as a disturbance signal proportional to the disturbances.

As a Komude FF control model, the setting gain KK is generally used.
There are cases in which only static compensation is used, and cases in which this static compensation is combined with dynamic compensation, which compensates for the transfer function of the vibration caused by sudden changes in disturbance. Although the former case will be explained in order to make it more accurate, it goes without saying that the latter case can be similarly applied to the static compensation part.

Then, the FF control model 31 multiplies the disturbance signal by the static compensation gain K to obtain the disturbance compensation signal D-K, which is sent to the adder 29, the gain scheduling section 33, and the f'F control model gain adaptation section. 38 respectively.

The gain scheduling unit 33 corrects the gain of the FB control output signal by 1 according to the magnitude of the disturbance change.
For example, when the process load increases, the gain of the FB control/output signal is determined in advance using a gain correction coefficient that associates the disturbance compensation signal D-, which has previously detected this disturbance information, with an optimized coupling coefficient that matches the process amount. For each increase, F
This is to solve in advance the problem of poor control due to insufficient output of the BB control output signal, and to achieve stabilization of control at an early stage. This gain scheduling can be achieved using a mathematical formula for the linear function 0, but the gain scheduling section 3 of this embodiment
In 3, it is assumed that the equation is composed of the following equation.

Here, in the above equation, FF is the input signal of the gain scheduling section 33, that is, the disturbance compensation signal D, Y is the output signal, that is, the gain correction coefficient, C is the coupling coefficient of the FF control and FB control, and Xo is the FB control control. It shows the magnitude of the disturbance compensation signal when the PID parameter of the cylinder joint portion 23 is determined.

This formula has a structure that can be applied to a wide range of processes by setting and changing the coupling coefficient C depending on the contents of the process amount. That is, (1) when O=0 is set, Y=1.0, and gain correction of the FBB control output signal is not executed, resulting in a combination control of general FB control and F F jIJIJ control.

The gain of the FB control output signal can be modified in proportion to the magnitude of the FF control output, and the target process quantities in this case are the temperature and concentration of the mixed basin process.
Optimal combination in control of and 6 becomes possible.

The rate of gain modification can be changed by the value of C, making it possible to perform optimal gain modification according to the process. The target process locations include pressure, flow rate, liquid level, etc. of non-mixing processes.

In this way, since the FBB control output signal is corrected in advance according to the change in the process caused by the gain disturbance, it is possible to output the operation signal at a level that matches the process after the change, and it is possible to realize control that follows the change in the gain. It becomes like this.

Furthermore, the FF control model gain adaptation unit 34 cannot be solved by FF control and gain scheduling.
1) It solves the prediction error of the FF control model and C) the influence of unknown disturbances. This is to reduce the inaccuracy of FII' control caused by these errors and influences to FBf.
This FBB is understood as an increase in the lj111IB force signal.
The 11i'F control model is modified so that the output signal becomes zero, and FF control is realized in accordance with the above errors and influences.

That is, the FF control model gain adaptation section 34 applies the following to the disturbance compensation signal D-, which is the output signal of the FF control model 31.
The operation signal MV, which is a composite signal of the FB/control output and the FF control output, is input, and a correction value of the FF control model is calculated so that both signals are equal.
1 and automatically corrects the gain.
An example of its specific structure is the patent application No. 59-19335.
There is something shown in the number.

This modification of the model gain may be performed continuously depending on the process characteristics, or may be performed periodically according to the change in temperature.In the latter case, the FF control model gain adaptation unit This can be realized by providing a timer circuit in 38 and configuring the correction operation to be executed based on the output thereof. Alternatively, a level detector may be provided for the FF control output signal or the operation signal, and the gain correction of the FF control model may be performed when the level exceeds a predetermined value and stabilizes at that value.

In this way, the FB that appears as the polishing of the above errors and influences
By modifying the fcFF control model so as to make the control output signal t-zero, it becomes possible to perform optimal predictive control for the portion that cannot be resolved by FF control or gain scheduling.

Next, the operation of this embodiment will be explained using FIG. 2.

FIG. 2 shows the changes in the process signal PV with respect to the set value signal Sv according to the seven combinations of control methods of this embodiment, where the solid line is for FB control only, and the dotted line is for gain scheduling. In the case of FB control, the dashed-dotted line shows the case of adding F'F control mk to the dashed-dotted line, and the dashed-double line shows the case of optimization adaptive control in which FF control model gain modification is added to the dashed-dotted line. .

First, the operation of Process 2 and the FB control system will be explained using the case where only FB control is shown as a solid line. If a disturbance, for example, a load reduction, is applied to the process 2, the process amount PV outputted from it will increase, and the deviation part An iB control output signal, which is PID-calculated by the FB control adjustment section 23 based on the control deviation signal G output from the control device 22, is outputted to the process 20 as an operation signal MY. However, with only this FB control, since changes in the process amount PV are directly corrected, fluctuations in the process amount continue, resulting in excessive control, and it is difficult to stabilize the control against disturbances. It will take a long time.

Therefore, for this FB control, the control side 1 information.

A gain scheduling section 33 is added which modifies the gain of the signal D- in advance according to the magnitude of the disturbance change, and the gain scheduling section 33 adjusts the coupling coefficient C set according to the process amount to the disturbance compensation signal D-. In relation to this, the gain of the FB control output signal is sequentially corrected using the obtained gain correction coefficient in a manner corresponding to the decrease in the negative value, thereby achieving early stabilization of the control as shown by the dotted line.

However, such FB control has poor ability to respond to disturbances and poor controllability, and increases fluctuations in process amount, resulting in a large amount of energy loss. Therefore, FF control is required to compensate for these effects in advance. In this FF control, when the disturbance detector 30 detects a load reduction, a disturbance compensation signal D- obtained by multiplying this disturbance signal by a set gain K that compensates for this is added to the 2FB control output signal in a one-point complex. This greatly improves controllability.

With this FF control and FB control with gain scheduling function, control optimization can be realized against normal predictable disturbances, but unforeseen disturbances such as errors in set gains and environmental changes due to long-term use can be realized. As a result, a slight deviation occurs in the set gain of the control model, FF controllability deteriorates, and as a result, the FB control output increases.

It becomes.

For this reason, an FF control model gain adaptation section 34 is provided, and in order to realize FF control that suits the above-mentioned errors and influences, the FF control output signal and the operation signal MY are adjusted so that the FB control output signal where this influence appears becomes zero. The gain of the FF control model is corrected based on the comparison, and optimal control for unknown disturbances is executed.

In this way, by organically combining the functions of FBIIJ control, its gain scheduling, FF control, and its control model gain automatic correction, the following effects are achieved.

(1) The ability to respond to any change in process disturbance is strong, and controllability can be maximized.

For example, in flow rate control, it is possible to respond immediately to changes in process dynamic characteristics due to sudden changes in disturbance, and in temperature control, long-term changes such as day/night changes in ambient temperature of 1 degree, seasonal changes, etc. In either case, changes in process amount can be suppressed to a minimum.

This makes it possible to significantly improve product quality and save energy and resources.

(2) 1 with a simple configuration that does not require difficult mathematical theory
．． By changing the predetermined values, it can be universally applied to various processes, and support for flexible production can be realized.

(3) No complicated and unnecessary search signals are added, the shock factor to the operating end etc. can be eliminated, and the process reliability can be greatly improved.

In the embodiment described above, FB control, FF control,
Although the explanation has been given using an example of a node configuration that realizes the functions of gain scheduling and FF control model gain adaptation, the present invention also allows these functions to be achieved by computer software.

Furthermore, the calculation processing in each function can be performed using the position signal or by mixing the position signal and the velocity shadow signal. Although the arithmetic processing is performed based on K, the same effect can be obtained even with a disturbance signal, and it goes without saying that the present invention can be modified in various ways without departing from the gist thereof.

〔Effect of the invention〕

As explained above, according to the present invention, it is possible to minimize the change in process amount in response to any disturbance change, and to realize optimized adaptive control that improves controllability to the utmost.
Moreover, it is possible to provide a process control device that is simple and easily versatile.

[Brief explanation of the drawing]

FIG. 1 is a functional block diagram showing the configuration of an embodiment of the present invention, FIG. 2 is a waveform diagram for explaining the operation of the embodiment of the present invention, and FIG. 3 is a diagram showing the configuration of a conventional example of the present invention. FIG. 20 ・・・・・・・・・・・・・・・・・・ Process 21 ・・・・・・・−・・・・・・・・・ Process amount detector 22...・・・・・・・・・・・・
・Deviation part 23 ・・・・・・・・−・・・・・・・・・・−
Feedback control adjustment section 24...
・・・・・・Multiplication section 25 ・・・・・・・・・・・・
・・・・・・Addition part 30 ・・・・・・・・・・・・・・・
...Disturbance detector 31 ......
・・・・・・ Feedforward control model 33 ・
・・・・・・・・・・・・・・・・・・ Gain scheduling section 34 ・・・・・・・・・・・・・・・・・・
・Feedforward Control Model Gain Adaptation Department Representative Patent Attorney Kensuke Chika (and others) Figure 1 v 34FF Control Model Gain/Adaptation Department Figure 2 V Figure 3

Claims (4)

[Claims] (1) A feedback control means that outputs a feedback control signal obtained by comparing and adjusting a set value and a process amount, and a feedforward control means that detects a disturbance and outputs a disturbance compensation signal that compensates for this disturbance based on a feedforward control model. a gain scheduling means for modifying the gain of the feedback control signal according to the magnitude of change in the disturbance; and an operation signal obtained by adding and synthesizing the disturbance compensation signal to the feedback control signal whose gain has been modified by the gain scheduling means. A process control device comprising feedforward control model gain adapting means for comparing the disturbance compensation signal and outputting a correction signal that makes both match, thereby correcting the gain of the feedforward control model. (2) The gain scheduling means corrects the gain of the feedback control signal by multiplying the feedback control signal by a gain correction coefficient calculated by correlating the magnitude of change in disturbance with a coupling coefficient set based on the process amount. A process control device according to claim 1, characterized in that: (3) The process control device according to claim 1, wherein the feedforward control model gain adaptation means periodically modifies the gain of the feedforward control model. (4) The feedforward control model gain adaptation means determines the magnitude of the gain of the feedback control signal or the operation signal, and modifies the gain of the feedforward control model when the gain exceeds a predetermined level. A process control device according to claim 1.