JPH0511811A - Feedforward device by inverse function generator - Google Patents

Abstract

PURPOSE:To reduce the influence of known disturbance upon a controlled variable by finding the precedent signal of a manipulated variable from a static characteristic model of an object of process control and inputting all values of known disturbance when an inverse function is found. CONSTITUTION:A closed loop system for estimating a controlled variable 10(u) by the static characteristic model 13 and approximating the estimated value 14 (y<0>) to a command 3 (r) is constituted and at this time, a coefficient multiplier 15 is arranged in parallel to the static characteristic model 13 to approximate the sum of both their outputs to the command. Consequently, the manipulated variable 10 (u) which can suppress variation in controlled variable 2 (y) when the known disturbance 11 (x, w) is applied to the object part 1 of process control is obtained. The coefficient value of the coefficient multiplier 15 which is arranged in parallel to the static characteristic model 13 is the reciprocal of the gain (k) of the closed loop system and inverted in sign.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a feedforward device using an inverse function generator, and is particularly useful when applied to each control of process products.

[0002]

2. Description of the Related Art FIG. 2 is a block diagram showing a representative example of a process control target portion and its control system. As shown in the figure, the control amount 2 (y) which is the output of the process control target unit 1
Is compared with the target value 3 (r) by the subtracter 4, and the control deviation 5
Calculate (ε). The control deviation 5 is input to a proportional-plus-integral action controller (hereinafter, PI controller) 6 and its output 7
(U ″) is added to the output 8 (u ⁰ ) of the coefficient unit 12 to be described later by the adder 9 to become the manipulated variable 10 (u). This manipulated variable 10 becomes the input of the process control target unit 1. At this time, for example, x and w can be considered as the known disturbance 11 of the process control target unit 1.

In the prior art shown in FIG. 2, in order to minimize the influence of the known disturbance 11 on the control amount 2, a coefficient unit 12 into which only w of the known disturbance 11 is input is provided and its output. 8 (u ⁰ ) is added to one end of the adder 9.

[0004]

In the prior art as described above, the output u ⁰ , which is the correction value, is obtained by using only the representative known disturbance 11 such as w, and this output u ⁰ is added to the output u ″. Since it is added to the process control target portion 1, there is a drawback that it is not possible to suppress the influence of other known disturbances that are not taken into consideration and sufficient control characteristics cannot be obtained.

The present invention has been made in view of the above problems of the prior art.
It is an object of the present invention to provide a feedforward device using an inverse function generator capable of ensuring good control characteristics by sufficiently considering known disturbance.

The structure of the present invention for achieving the above object is as follows:

A control deviation ε, which is a difference between a control value y output from a process control target portion to which an operation amount u is input and a target value r, is obtained, and this control deviation ε is proportionally integrated by a proportional-plus-integral action regulator. Calculated output u ″ and control amount y due to known disturbance
In order to reduce the influence on the output of the compensator, the control device that adds the output u ⁰ output from the inverse function generator to obtain the manipulated variable u has the input / output characteristics of the process control target unit. The inverse function generator is non-linear, and the inverse function generator includes a static characteristic model representing a relationship between a static control amount, an operation amount, and a known disturbance of a process control target portion, and an estimated static signal which is an output signal of the static characteristic model. A closed-loop system to bring the controlled variable close to the target value and the gain k of the closed-loop system is -1 /
It has a gain of k and a coefficient multiplier connected in parallel to the static characteristic model.

[0008]

According to the present invention having the above-described structure, it is possible to obtain the preceding signal of the manipulated variable from the static characteristic model of the process control target portion. Moreover, in this case, all the values of the known disturbance can be taken in when obtaining the inverse function, so that the influence of the known disturbance on the control amount can be reduced.

[0009]

Embodiments of the present invention will now be described in detail with reference to the drawings. It should be noted that the same parts as those of the prior art are designated by the same reference numerals and duplicate description will be omitted.

As shown in FIG. 1, the process control target unit 1
The static characteristic model 13 simulating is input with the known disturbance 11 and the output 8 (u ⁰ ) of the inverse function generator I which is the compensator, and outputs the estimated value 14 (y ⁰ ) of the static control amount. At this time, the manipulated variable 10 (u) of the process control target unit 1 is obtained by adding the output 8 (u ⁰ ) of the inverse function generator I and the output 7 (u ″) of the PI controller 6 by the adder 9. The coefficient unit 15 is arranged in parallel with the static characteristic model 13 and has an output 8 as its input.
(U ⁰ ) is input, multiplied by a coefficient (−1 / k), and output as output 16. This output 16 is an output of the static characteristic model 13 and an estimated value 14 (y ⁰ ) of the static control amount and an adder 17
Is added in. The output of the adder 17 is compared with the target value 3 (r) by the subtractor 18 and becomes an error 19 (δ). Error 1
9 (δ) is multiplied by the coefficient (k) by the coefficient unit 20, and the output 8
(U ⁰ ). The coefficient (k) at this time is an adjustment parameter and is obtained by trial error.

In the present embodiment, the non-linear process control target portion 1 is expressed by a non-linear mathematical model, and by using the non-linear mathematical model, all the signals of known disturbance are taken in, thereby controlling the process control amount. A signal that minimizes fluctuation can be calculated and supplied as part of the manipulated variable signal of the process.

More specifically, first, the static characteristic model 1
The control amount 10 (u) is estimated by 3 and the estimated value 14
A closed loop system for constantly making (y ⁰ ) close to the target value 3 (r) is configured. At that time, a coefficient unit 15 is arranged in parallel with the static characteristic model 13, and a value obtained by adding both outputs is Close to the target value. As a result, the known disturbance 11 (x, w)
Control amount 2 when is added to the process control target unit 1
A manipulated variable 10 (u) capable of suppressing the variation in (y) is obtained.

The coefficient value of the coefficient unit 15 arranged in parallel with the static characteristic model 13 is the reciprocal of the gain (k) of the closed loop system, and the sign is inverted.

The operation of this embodiment as described above can be expressed by using mathematical expressions as follows.

The static estimated value 14 (y ⁰ ) of the controlled variable can be expressed by the following equation. y ⁰ = g (u ⁰ , x, w) (1) where u ⁰ is the output of the inverse function generator I, and x and w are known disturbances.

Next, the following equation is obtained by constructing a closed loop system on the mathematical model. δ = r− {g (u ⁰ , x, w) −1 / k u ⁰ } (2) u ⁰ = kδ (3) where δ means an error, and k and −1 / k are coefficient multipliers. There are 20 and 15 parameters.

Therefore, the following relationship is obtained from the expressions (2) and (3). 1 / k u ⁰ = r−g (u ⁰ , x, w) + 1 / k u ⁰ (4) That is, r = g (u ⁰ , x, w) = y ⁰ (5), and y ⁰ is r Matches

Therefore, if u ⁰ obtained here is added to the output 7 (u ″) as the output of the inverse function generator I, the controllability can be improved.

[0019]

As described above in detail with reference to the embodiments, according to the present invention, the following effects can be obtained.
(1) Since an inverse function generator, which is a compensator, is formed by a non-linear mathematical model, and all known disturbance signals are taken in, a manipulated variable correction signal that suppresses the influence of the known disturbance on the control amount can be calculated. The control performance can be improved.
(2) The calculation process is simple because the inverse function is not directly obtained.

[Brief description of drawings]

FIG. 1 is a block diagram of an inverse function generator according to an embodiment of the present invention.

FIG. 2 is a block diagram showing a conventional control system.

[Explanation of symbols]

I Inverse function generator 1 Process control target part 2 Control amount (y) 3 Target value (r) 4 Subtractor 5 Control deviation (ε) 6 PI adjuster 7 PI adjuster output (u ″) 8 Inverse function generator Output (u ⁰ ) 9 adder 10 manipulated variable (u) 11 known disturbance (x, w) 12 coefficient device 13 static characteristic model simulating a process 14 static estimated control amount (y ⁰ ) 15 coefficient device 16 Output of coefficient unit 17 Adder 18 Subtractor 19 Error (δ) 20 Coefficient unit

Claims (1)

Claim: What is claimed is: 1. A control deviation ε, which is a difference between a control amount y output from a process control target portion to which an operation amount u is input and a target value r, is obtained, and this control deviation ε is calculated. The output u ″ calculated by the proportional-plus-integral operation controller is added to the output u ⁰ output from the inverse function generator, which is a compensator, in order to reduce the influence of the known disturbance on the control amount y. In the control device with the manipulated variable u, the process control target part has a non-linear input / output characteristic, and the inverse function generator has a relationship between a static control amount of the process control target part, a manipulated variable, and a known disturbance. Of the static characteristic model, a closed loop system for bringing the estimated static control amount, which is the output signal of the static characteristic model, close to the target value, and a gain of −1 / k with respect to the gain k of the closed loop system. Parallel to the static characteristic model. And a feed coefficient device having an inverse function generator.