CN109856974A - A kind of four factor intelligent control methods based on controlled volume variation - Google Patents
A kind of four factor intelligent control methods based on controlled volume variation Download PDFInfo
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Abstract
The invention discloses a kind of four factor intelligent control methods based on controlled volume variation, apply control according to four size of controlled volume variation, direction, speed, trend factors, simulate the abstract logic reasoning and decision thinking of people, it solves Traditional control and is difficult to the technical issues of coordinating contradiction between " steady, fast, quasi- " Control performance standard, the purpose that dynamic response is fast, control precision is high, control is stable may be implemented.By using including: step 1, four factor variable conditions are defined；Step 2 defines control amount output algorithm；Step 3, it is regular according to empirically determined control is controlled；Step 4 is modeled using LVQ neural network；Step 5 is programmed using LVQ model parameter and realizes control algolithm.The control thinking of the control algolithm simulation people, overcomes and depends only on the shortcomings that controlled volume variation size is controlled in Traditional control, can be used in Theory of Automatic Control and technology.
Description
Technical field
The present invention relates to a kind of automation field, specifically a kind of four factor intelligent control sides based on controlled volume variation
Method.
Background technique
Current control theory method, Classical control theory, modern control theory either based on model, or without mould
The Intelligent Control Theory of type is mainly based upon deviation, change of error constitutes control algolithm.For example, the pid control algorithm of mainstream,
It is exactly the combination between the derivative of the ratio of deviation, the integral of deviation, deviation.Controlled volume deviation, change of error are only anti-
Controlled volume variation size is reflected, its change direction, trend, speed are not embodied in the algorithm.Accordingly, there exist controls to calculate
Method is single, fixes the disadvantages of controlling period, continuous closed-loop control, as long as with the presence of deviation and there is fluctuation, controller has company
Continuous, variation output, actuator are acting always, are affecting the stability of system, also affect the service life of actuator；It is difficult to coordinate
Phenomena such as contradiction between " steady, fast, quasi- " Control performance standard, the concussion of control process, overshoot, is inevitable.
The great advantage of manual control be can according to controlled volume change size, direction, four speed, trend factors
Apply control, select different control strategy, or increases control amount (be significantly increased, slightly increase)；Or reduce control
Amount (substantially reduces, slightly reduces)；Or keep control amount is constant, etc. to look at.Control process open and close ring switches at any time, control
Period processed can also adjust at any time.
For this purpose, proposing four factor intelligent control algorithms, the control thinking of people is simulated, solves the problems, such as that Traditional control exists,
Obtain excellent control effect.
Summary of the invention
The shortcoming in the prior art being previously mentioned in technology based on the above background, the present invention provides a kind of bases thus
In four factor intelligent control methods of controlled volume variation.
The present invention overcomes the above technical problem by using following technical solution, specifically:
A kind of four factor intelligent control methods based on controlled volume variation, include the following steps:
Step 1, defines four factor variable conditions, and four factors use X respectively1, X2, X3, X4It indicates；
Step 2 defines control amount output；
Step 3, according to the empirically determined control rule of control, size, direction, speed, trend four according to controlled volume variation
A factor applies control, parallel processing capability of the reflection people to information；
Step 4 is modeled using LVQ neural network；
Step 5 is programmed using LVQ model parameter and realizes control algolithm.
As a further solution of the present invention: in the step 1, the deviation of current controlled volume variation: en=r-yn, r sets
Definite value, ynControlled volume current value；Change of error: Δ en=en-en-1；Control precision (allows to control error): ε；Control limit essence
Spend (maximum allowable control error) εmax。
As further scheme of the invention: in the step 2, control amount output algorithm has following seven kinds；
(1) Uk=Kp*ek+Ki* ∫ edt；
(2) Uk=Uk-1+K* Δ u；
(3) Uk=Uk-1+Kp*ek；
(4) Uk=Uk-1-K* Δ u；
(5) Uk=Uk-1；
(6) Uk=Umin；
(7) Uk=Umax.
As the present invention further scheme: in the step 3, according to the size of controlled volume variation, direction, speed,
Four factors of trend apply control, and reflection people is to the rule of the parallel processing capability of information:
If X1 and X2 and X3 and X4 then U。
As further scheme of the invention: in the step 4, using determining control rule, with MATLAB pairs
LVQ is trained.
As further scheme of the invention: in the step 5, realizing that the process of control algolithm is, first acquisition is controlled
Current value is measured, then calculates deviation, change of error, then calculate four factor characteristic values, then by LVQ input, weight, it is special to calculate output U
Value indicative calculates control amount output finally by U characteristic value.
After using the above structure, the present invention compared to the prior art, has following advantages: simulating the control experience of people, adopts
With four factor controllings；It realizes that open and close ring cutting changes, becomes the control period；Efficiently solve " steady, fast, quasi- " Control performance standard
Between contradiction, response is fast, overshoot is small, adjustment time is short, and stability is good, increases actuator working life, anti-interference energy
Power is strong.
Detailed description of the invention
Fig. 1 is the algorithm schematic diagram of the four factor intelligent control methods changed based on controlled volume.
Fig. 2 is the real-time control curve in the four factor intelligent control methods changed based on controlled volume.
Fig. 3 is the real-time control curve of traditional PID control method.
Fig. 4 is anti-interference ability schematic diagram in the four factor intelligent control methods changed based on controlled volume.
Specific embodiment
To facilitate the understanding of the present invention, a more comprehensive description of the invention is given in the following sections with reference to the relevant attached drawings.In attached drawing
Give better embodiment of the invention.But the present invention can be realized with many different forms, however it is not limited to herein
Described embodiment.On the contrary, the purpose of providing these embodiments is that making to understand more the disclosure
Add thorough and comprehensive.
In addition, the element in the present invention referred to as " is fixed on " or " being set to " another element, it can be directly another
On one element or there may also be elements placed in the middle.When an element is considered as " connection " another element, it can be with
It is directly to another element or may be simultaneously present centering elements.Term as used herein " vertically ", " level
", "left", "right" and similar statement for illustrative purposes only, be not meant to be the only embodiment.
Embodiment 1
Please refer to Fig. 1~4, in the embodiment of the present invention, a kind of four factor intelligent control methods based on controlled volume variation, packet
Include following steps:
Step 1, defines four factor variable conditions, and four factors use X respectively1, X2, X3, X4It indicates, current controlled volume variation
Deviation: en=r-yn, r setting value, ynControlled volume current value；Change of error: Δ en=en-en-1；Control precision (allows to control
Error): ε；Control limit precision (maximum allowable control error) εmax, wherein X1For the size of controlled volume variation, there are seven
Characteristic value is respectively as follows: 3,2,1,0, -1, -2, -3, and meaning representated by seven characteristic values see the table below:
| Characteristic value | Function description | Condition | Symbol indicates |
| 3 | Deviation is honest | en> εmax | PB |
| 2 | Deviation center | ε < en≤εmax | PM |
| 1 | Deviation is just small | 0 < en≤ε | PS |
| 0 | Deviation is 0 | en=0 | PZ |
| -1 | Deviation is born small | en>-ε | NS |
| -2 | During deviation is negative | -εmax< en≤-ε | NM |
| -3 | Deviation is negative big | en≤-εmax | NB |
X2For the direction of controlled volume variation, tool contains representated by 0, -1, three characteristic values there are three characteristic value, respectively 1
Justice see the table below:
| Characteristic value | Function description | Condition |
| 1 | Controlled volume is far from given value | en*Δen> 0 |
| 0 | Equal to given value | en*Δen=0 |
| -1 | Close to given value | en*Δen< 0 |
X3For the speed of controlled volume variation, it may have three characteristic values, respectively 1,0, -1, representated by three characteristic values
Meaning see the table below:
In table, α value 0.2, β value 0.5；
X4For the trend of controlled volume variation, it may have three characteristic values, respectively 1,0, -1；Representated by three characteristic values
Meaning see the table below:
Control precision, the setting value of controlled volume are it is known that sampling controlled volume current value, calculates the variation of deviation, deviation, X1, X
2, X 3, X 4 can determine state characteristic value；
Step 2 defines control amount output, determines that control amount exports formula, wherein Δ u=1/ (Umax-Umin), control
The output of amount has diversified forms, such as manually controls, and the control amount that people can apply can be divided into following several: maximum, most
It is small, be significantly increased, substantially reduce, slightly increasing, seven kinds of situations such as slightly reducing, remain unchanged；Maximum control amount, minimum control
Amount be it is known, control amount remain unchanged be exactly it is equal, it is remaining be how description be significantly increased, substantially reduce, slightly increase
Add, slightly reduce；The situation that control amount is significantly increased occurs at one to be the initial control stage, and deviation is honest at this time；Another
It is exactly acutely to be interfered after stabilization, controlled volume is rapidly reduced, and far from given value, can use proportional-plus-integral this when
Control algolithm, description are significantly increased control amount, slightly increase control amount, and usually in stationary zones, overgauge is smaller, adjust manually
Section amplitude cannot be too big, substantially reduces control amount mainly in positive overshoot region, controlled volume generates overshoot with fast speed, at this time
It needs substantially to reduce control amount, so that controlled volume is returned to stationary zones as early as possible, slightly reduce control amount, be typically also in steady-state zone
Domain, minus deviation is smaller, and the amplitude of manually adjusting cannot be too big；Control amount remains unchanged, and is that closed-loop control turns opened loop control, controlled volume
It keeps stablizing；The output of control amount minimum, usually out of service just to use, real-time control process will not generate such situation, by
This, is described as follows above-mentioned seven kinds of control amounts:
(1) Uk=Kp*ek+Ki* ∫ edt；Output is significantly increased in control amount, and negative unstable state, e > 0, Kp, Ki refer to pid parameter
Setting method determines；
(2) Uk=Uk-1+K* Δ u；Control amount slightly increases output, negative stable state, k=1, and 2,, 10；
(3) Uk=Uk-1+Kp*ek；Control amount substantially reduces output, positive overshoot state, e < 0；
(4) Uk=Uk-1-K* Δ u；Control amount slightly reduces output, positive unstable state, k=1, and 2,, 10；
(5) Uk=Uk-1；Control amount remains unchanged, stable state, open loop；
(6) Uk=Umin；Control amount minimum exports, positive overshoot state, known to minimum control amount；
(7) Uk=Umax；Control amount maximum output, negative overshoot state, known to maximum control amount；
Control amount output has 7 kinds, is indicated with U, characteristic value serial number corresponding with above-mentioned output formula: 1,2,3,4,5,6,
7；
Step 3, according to the empirically determined control rule of control, size, direction, speed, trend four according to controlled volume variation
A factor applies control, reflects people to the parallel processing capability of information, rule is:
If X1 and X2 and X3 and X4 then U
According to the complexity of controlled system, control rule in varying numbers can be formulated, between general 10-100；
Step 4 is modeled using LVQ neural network, using determining control rule, is instructed with MATLAB to LVQ
Practice, by taking 14 kinds of combinations as an example:
X=[2 1 1-1-2-3 221 1-1-2 10；-1 -1 -1 1 1 1 -1 1 1 1 -1 -1 -1
0；1 1 0 1 1 1 -1 1 -1 1 -1 -1 -1 0；0 0 0 0 0 0 -1 -1 0 0 0 0 -1 0]；Input vector
Tc=[1 254332251545 5]；Output vector, object vector；
T=ind2vec (tc)；Matrix-vector conversion；
Net=lvqnet (10)；Create LVQ network, 10 node of hidden layer
Net.trainParam.epochs=1000；The number of iterations
Net=train (net, x, t)；
view(net)；
Y=net (x)；
Classes=vec2ind (y)；Matrix inverse conversion；
Network iteration 250 times just realizes Complete Classification, and consistent with target value, corresponding weight is as follows: w1=input layer arrives
Hidden layer weight
H1=hidden layer is to output layer weight
Input layer is obtained to hidden layer weight W1, hidden layer to output layer weight H1；
Step 5 is programmed using LVQ model parameter and realizes that control algolithm, process are, first acquire controlled volume current value, then count
Deviation, change of error are calculated, then calculates four factor characteristic values, then by LVQ input, weight, calculates output U characteristic value, finally by U spy
Value indicative calculates control amount output；Above-mentioned algorithm is realized in configuration software:
U=[X1, X2, X3, X4] T*w1*h1
For example, if U=[0,0,1,0,0] T, then take control amount output type (3): Uk=Uk-1+Kp*ek.
It should be noted that control algolithm simulation people control thinking, overcome depended only in Traditional control it is controlled
Amount variation size the shortcomings that being controlled, can be used in Theory of Automatic Control and technology, the present embodiment specifically can KingView,
Algorithm is realized in programming in the monitoring softwares such as MatLab；For PLC, realization can be programmed in PLC, be suitable for process industry and its
The control of the physical quantitys such as (such as: boiler, refrigerator, water tank etc.) temperature, pressure, flow, liquid level in other objects, with high water tank
For control, the present embodiment has built high water tank control system, and the algorithm is realized in programming in KingView software, controls water tank
Liquid level realizes " steady, fast, quasi- ", and overshoot is small, realizes Open-closed-loop switching.Fig. 2 is real-time control curve, with Fig. 3 tradition
PID control method is compared, and realizing control performances, the Fig. 4 such as overshoot is small, and adjustment time is short, Open-closed-loop switches, system is stablized is to calculate
The anti-interference ability of method, it is seen that obtain excellent antidisturbance control effect.
Only highly preferred embodiment of the present invention is described above, but is not to be construed as limiting the scope of the invention.This
Invention is not limited only to above embodiments, and specific structure is allowed to vary.In every case in the protection model of independent claims of the present invention
Interior made various change is enclosed to be within the scope of the invention.
Unless otherwise defined, all technical and scientific terms used herein and belong to technical field of the invention
The normally understood meaning of technical staff is identical.Term as used herein in the specification of the present invention is intended merely to description tool
The purpose of the embodiment of body, it is not intended that in the limitation present invention.Term " and or " used herein includes one or more
Any and all combinations of relevant listed item.
Claims (6)
1. a kind of four factor intelligent control methods based on controlled volume variation, which comprises the steps of:
Step 1, defines four factor variable conditions, and four factors use X respectively1, X2, X3, X4It indicates；
Step 2 defines control amount output；
Step 3, according to controlling empirically determined control rule, the size changed according to controlled volume, direction, speed, trend four because
Element applies control, parallel processing capability of the reflection people to information；
Step 4 is modeled using LVQ neural network；
Step 5 is programmed using LVQ model parameter and realizes control algolithm.
2. a kind of four factor intelligent control methods based on controlled volume variation according to claim 1, which is characterized in that institute
It states in step 1, the deviation of current controlled volume variation: en=r-yn, r setting value, ynControlled volume current value；Change of error: Δ en
=en-en-1；Control precision (allows to control error): ε；Control limit precision (maximum allowable control error) εmax。
3. a kind of four factor intelligent control methods based on controlled volume variation according to claim 1, which is characterized in that institute
It states in step 2, control amount output algorithm has following seven kinds；
(1) Uk=Kp*ek+Ki* ∫ edt；
(2) Uk=Uk-1+K* Δ u；
(3) Uk=Uk-1+Kp*ek；
(4) Uk=Uk-1-K* Δ u；
(5) Uk=Uk-1；
(6) Uk=Umin；
(7) Uk=Umax.
4. a kind of four factor intelligent control methods based on controlled volume variation according to claim 1, which is characterized in that institute
It states in step 3, applies control according to four size of controlled volume variation, direction, speed, trend factors, reflect people to information
The rule of parallel processing capability is:
If X1 and X2 and X3 and X4 then U。
5. a kind of four factor intelligent control methods based on controlled volume variation according to claim 1, which is characterized in that institute
It states in step 4, using determining control rule, LVQ is trained with MATLAB.
6. a kind of four factor intelligent control methods based on controlled volume variation according to claim 1, which is characterized in that institute
It states in step 5, realizes that the process of control algolithm is, first acquire controlled volume current value, then calculate deviation, change of error, then calculate
Four factor characteristic values, then by LVQ input, weight, output U characteristic value is calculated, finally by U characteristic value, calculate control amount output.
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Cited By (1)
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| CN112947606A (en) * | 2021-03-11 | 2021-06-11 | 哈尔滨工程大学 | Boiler liquid level control system and method based on BP neural network PID predictive control |
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Application publication date: 20190607 |