CN109445287A - A kind of internal PID fuzzy control method based on PLC board - Google Patents
A kind of internal PID fuzzy control method based on PLC board Download PDFInfo
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Abstract
The invention discloses a kind of internal PID fuzzy control methods based on PLC board, fuzzy control rule is determined by sampled data or empirical value, the degree of membership that Fuzzy processing obtains each fuzzy subset is carried out to measurement error e and error rate ec using fuzzy control rule, the degree of membership assignment table and each parameter fuzzy Controlling model of each fuzzy subset are established according to obtained degree of membership, using the fuzzy matrix table of fuzzy synthetic reason design Fractional Order PID Controller parameter, calculate the input that correction amount parameter is PID controller, the value of three control parameters is exported according to the state adjust automatically PID controller of controlled device, using error e and error rate ec as input, self-adaptive sites are carried out using output parameter of the fuzzy rule to PID controller, controlled device is set to be maintained at good dynamic, Steady stability state, user only need to input corresponding control parameter value, and without voluntarily writing PLC control program, operation difficulty is low, stability and high reliablity.
Description
Technical field
The invention belongs to the designs of the internal PID FUZZY ALGORITHMS FOR CONTROL based on PLC board, and in particular to one kind is based on PLC
The internal PID fuzzy control method of board.
Background technique
PLC is the universal industrial control device based on microprocessor, realizes industry by the instruction that it is internally integrated
Control, is widely used in industrial control field.Currently, the traditional PID control that PLC is internally integrated is easy to use, suitable
Ying Xingqiang, while precision is low when having the characteristics that processed, poor anti jamming capability, adaptivity are poor, built-in PID in traditional PLC
Control algolithm is traditional pid control algorithm, and in use, user just must voluntarily write PLC control program, realizes two
Secondary exploitation, operation difficulty is big, stability and reliability are lower.
Summary of the invention
The purpose of the present invention is to provide a kind of internal PID fuzzy control methods based on PLC board, to overcome existing skill
The deficiency of art.
In order to achieve the above objectives, the present invention adopts the following technical scheme:
A kind of internal PID fuzzy control method based on PLC board, comprising the following steps:
Step 1) determines fuzzy control rule by sampled data or empirical value；
Step 2) obtains measurement error e and error rate ec progress Fuzzy processing using fuzzy control rule
The degree of membership of each fuzzy subset；
Step 3), the degree of membership obtained according to step 2) establish the degree of membership assignment table and each parameter mould of each fuzzy subset
Controlling model is pasted, using the fuzzy matrix table of fuzzy synthetic reason design Fractional Order PID Controller parameter, calculates parameter, Δ kp、
Δki、Δkd, Δ kpFor the correction amount of the proportionality coefficient of controller, Δ kiFor the correction amount of the integral coefficient of controller, Δ kdFor
The correction amount of the differential coefficient of controller；
Step 4), the correction amount parameter, Δ k that will be obtainedp、Δki、ΔkdAs the input of PID controller, according to controlled pair
The state adjust automatically PID controller of elephant exports the value of three control parameters.
Further, specifically, obtaining fuzzy relationship matrix r by formula (1):
If measurement error e=Ai, error rate ec=Bj,
Then export fuzzy set u=Ck, i=1 ..., N1；J=1,2 ..., N2；K=1,2 ..., N2
A in formulaiThe fuzzy subset of-measurement error e；Bj-error rate ec fuzzy subset；Ck- output is fuzzy
Collect the fuzzy subset of U；N1,N2,N3Respectively fuzzy subset Ai,Bj,CkNumber；
According to the composition rule of fuzzy reasoning, the control amount of output is output fuzzy set U:
U=(A × B) × R (2)
I.e.
A-measurement error e fuzzy set；B-error rate ec fuzzy set.
Further, the corresponding membership function of different parameters is established according to family of functions, seeks the degree of membership of each parameter.
Further, the abscissa of the degree of membership and corresponding degree of membership that are obtained using step 2) calculates correction amount parameter
Δkp、Δki、Δkd；Specific calculation formula is as follows:
X, y respectively represents the deviation of different directions, and u (x), u (y) respectively indicate being subordinate to for different correction amount different directions
Degree；Z is corresponding degree of membership abscissa.
Further, the correction amount parameter, Δ k that will be obtainedp、Δki、ΔkdBring formula into
kp=kp0+Δkp
ki=ki0+Δki
kd=kd0+Δkd
The output valve of three control parameters of PID controller can be obtained.
Further, the value that PID controller exports three control parameters is obtained by following formula:
Further, measurement error e=r (k)-y (k), r (k) are control target value, and y (k) is actual measurement value of feedback；
Error rate ec=e (k)-e (k-1)；
E (k) indicates current control target value and surveys the deviation of value of feedback；E (k-1) indicate it is upper one clap control target value with
Survey the deviation of value of feedback.
Compared with prior art, the invention has the following beneficial technical effects:
A kind of internal PID fuzzy control method based on PLC board of the present invention, determines mould by sampled data or empirical value
Paste control rule, carries out Fuzzy processing to measurement error e and error rate ec using fuzzy control rule and obtains each mould
The degree of membership for pasting subset establishes the degree of membership assignment table of each fuzzy subset according to obtained degree of membership and each parameter fuzzy controls mould
Type, using the fuzzy matrix table of fuzzy synthetic reason design Fractional Order PID Controller parameter, calculating correction amount parameter is PID
The input of controller exports the value of three control parameters, according to the state adjust automatically PID controller of controlled device with error
E and error rate ec carry out self-adaptive sites as input, using output parameter of the fuzzy rule to PID controller, make by
Control object is maintained at good dynamic and static stable state, and user only needs to input corresponding control parameter value, without voluntarily writing
PLC control program, operation difficulty is low, stability and high reliablity.
Detailed description of the invention
Fig. 1 is fuzzy self-tuning structure chart.
Fig. 2 is that specific embodiment parameter realizes ladder diagram.
Fig. 3 is vagueness of regulations control rule schema.
Specific embodiment
The invention will be described in further detail with reference to the accompanying drawing:
As shown in Figure 1, a kind of internal PID fuzzy control method based on PLC board, Fuzzy Adaptive PID Control algorithm
Working principle: fuzzy-adjustable PID algorithm mainly be combined by fuzzy controller and PID controller, fuzzy controller with
Measurement error e and error rate ec is as input, using fuzzy control rule to the output parameter k of PID controllerp、ki、
kdSelf-adaptive sites are carried out, controlled device is made to be maintained at good dynamic and static stable state；Compared to traditional PID control, obscure
Self-adaptive PID is more flexibly stablized, and especially for time variation and non-linear biggish controlled device, advantage is more prominent
Out, kpFor controller proportionality coefficient, kiFor controller integral coefficient, kdFor controller differential coefficient；Fuzzy self-tuning structure
Figure is as shown in Figure 1.
Internal PID fuzzy control method based on PLC board the following steps are included:
Step 1) determines fuzzy control rule by sampled data or empirical value:
Specifically, obtaining fuzzy relationship matrix r by formula (1):
If measurement error e=Ai, error rate ec=Bj,
Then export fuzzy set u=Ck, i=1 ..., N1；J=1,2 ..., N2；K=1,2 ..., N2
A in formulaiThe fuzzy subset of-measurement error e；BjThe fuzzy subset of-error rate ec；Ck- output is fuzzy
Collect the fuzzy subset of U；N1,N2,N3Respectively fuzzy subset Ai,Bj,CkNumber；
According to the composition rule of fuzzy reasoning, the control amount of output is output fuzzy set U:
U=(A × B) × R (2)
I.e.
A-measurement error e fuzzy set；B-error rate ec fuzzy set；
Measurement error e=r (k)-y (k), r (k) are control target value, and y (k) is actual measurement value of feedback；
Error rate ec=e (k)-e (k-1)；
E (k) indicates current control target value and surveys the deviation of value of feedback；E (k-1) indicate it is upper one clap control target value with
Survey the deviation of value of feedback；
Vagueness of regulations as shown in Figure 3 controls rule schema, and measurement error e is divided into 14 grades, error rate ec
It is divided into 13 grades, output fuzzy set U is divided into 15 grades, then it is as shown in table 1 to obtain fuzzy control table by operation:
1 fuzzy control table of table
Step 2) obtains measurement error e and error rate ec progress Fuzzy processing using fuzzy control rule
The degree of membership of each fuzzy subset:
The method for building up of subordinating degree function: each parameter determines respectively to the membership function of respective subset by different families of functions
It is fixed, the respective subset of parameter refer to the parameter by man-made division at one group of fuzzy set being constituted of grade, respective subset
How much, it is determined by control precision:
If the respective subset of parameter " temperature " can be " honest, just small, bear small, bear big ", be also possible to " honest, center,
Just small, bear small, bear, bear big ", the latter is more than the former fuzzy subset, and it is higher to control precision, the respective subset of temperature deviation x
Are as follows:
Honest: the relationship of output control amount u (x) and deviation x are u (x)=1-1/ (1+0.5X2)(X>0)
Center: the relationship of output control amount u (x) and deviation x are u (x)=1/ (1+ (X-2)2)(X>0)
Just small: the relationship of output control amount u (x) and deviation x are u (x)=1/ (1+ (X-1)2)(X>0)
Positive very little: the relationship of output control amount u (x) and deviation x are u (x)=1/ (1+0.5X2)(X>0)
Negative very little: the relationship of output control amount u (x) and deviation x are u (x)=1/ (1+0.5X2)(X<0)
Bear small: the relationship of output control amount u (x) and deviation x are u (x)=1/ (1+ (X+1)2)(X<0)
In negative: the relationship of output control amount u (x) and deviation x are u (x)=1/ (1+ (X+2)2)(X<0)
Negative big: the relationship of output control amount u (x) and deviation x are u (x)=1-1/ (1+0.5X2)(X<0)
Step 3), the degree of membership obtained according to step 2) establish the degree of membership assignment table and each parameter mould of each fuzzy subset
Controlling model is pasted, using the fuzzy matrix table of fuzzy synthetic reason design Fractional Order PID Controller parameter, calculates parameter, Δ kp、
Δki、Δkd；
ΔkpFor the correction amount of the proportionality coefficient of controller, Δ kiFor the correction amount of the integral coefficient of controller, Δ kdFor control
The correction amount of the differential coefficient of device processed；Δkp、Δki、ΔkdFor 3 output valves of fuzzy controller；
Specifically, the abscissa of the degree of membership and corresponding degree of membership obtained using step 2), calculates correction amount parameter, Δ
kp、Δki、Δkd；Specific calculation formula is as follows:
X, y respectively represents the deviation of different directions, and u (x), u (y) respectively indicate being subordinate to for different correction amount different directions
Degree；Z is corresponding degree of membership abscissa；
Step 4), the correction amount parameter, Δ k that will be obtainedp、Δki、ΔkdAs the input of PID controller, according to controlled pair
The state adjust automatically PID controller of elephant exports the value of three control parameters.
It is specific: the correction amount parameter, Δ k that will be obtainedp、Δki、ΔkdBring formula into
kp=kp0+Δkp
ki=ki0+Δki
kd=kd0+Δkd
The output valve of three control parameters of PID controller, k can be obtainedp0、ki0、kd0For the initial design values of pid parameter,
By the parameter tuning method design of conventional PID controller；
Using following formula, PID controller output can be obtained:
Specific embodiment realizes ladder diagram as shown in Fig. 2, PID controller input parameter is established corresponding parameter, by PID
Controller input parameter brings operation into, and user only needs that Fuzzy PID can be realized by following programming citing operation:
D1 is the control target value of PID controller；
D2 is actual measurement value of feedback；
D80 is initialization K needed for PID arithmeticP；
D81 is initialization K needed for PID arithmetici；
D82 is initialization K needed for PID arithmeticd；
The input value error e and error rate ec that fuzzy controller needs are obtained by calculation in PLC board program.
D100 is the storage unit of PID calculated result, please be appointed as non-battery holding area, is needed before otherwise starting operation for the first time
Clear 0 processing is initialized to it, final fuzzy calculated result will be stored in D100 register.
Claims (7)
1. a kind of internal PID fuzzy control method based on PLC board, which comprises the following steps:
Step 1) determines fuzzy control rule by sampled data or empirical value；
Step 2) obtains each mould to measurement error e and error rate ec progress Fuzzy processing using fuzzy control rule
Paste the degree of membership of subset；
Step 3), the degree of membership obtained according to step 2), establish each fuzzy subset degree of membership assignment table and each parameter fuzzy control
Simulation calculates parameter, Δ k using the fuzzy matrix table of fuzzy synthetic reason design Fractional Order PID Controller parameterp、Δki、
Δkd, Δ kpFor the correction amount of the proportionality coefficient of controller, Δ kiFor the correction amount of the integral coefficient of controller, Δ kdFor control
The correction amount of the differential coefficient of device；
Step 4), the correction amount parameter, Δ k that will be obtainedp、Δki、ΔkdAs the input of PID controller, according to controlled device
State adjust automatically PID controller exports the value of three control parameters.
2. a kind of internal PID fuzzy control method based on PLC board according to claim 1, which is characterized in that specific
, fuzzy relationship matrix r is obtained by formula (1):
If measurement error e=Ai, error rate ec=Bj,
Then export fuzzy set u=Ck, i=1 ..., N1；J=1,2 ..., N2；K=1,2 ..., N2
A in formulaiThe fuzzy subset of-measurement error e；BjThe fuzzy subset of-error rate ec；Ck- output fuzzy set U's
Fuzzy subset；N1,N2,N3Respectively fuzzy subset Ai,Bj,CkNumber；
According to the composition rule of fuzzy reasoning, the control amount of output is output fuzzy set U:
U=(A × B) × R (2)
I.e.
A-measurement error e fuzzy set；B-error rate ec fuzzy set.
3. a kind of internal PID fuzzy control method based on PLC board according to claim 1, which is characterized in that according to
Family of functions establishes the corresponding membership function of different parameters, seeks the degree of membership of each parameter.
4. a kind of internal PID fuzzy control method based on PLC board according to claim 1, which is characterized in that utilize
The abscissa of degree of membership and corresponding degree of membership that step 2) is obtained calculates correction amount parameter, Δ kp、Δki、Δkd；Specific meter
It is as follows to calculate formula:
X, y respectively represents the deviation of different directions, and u (x), u (y) respectively indicate the degree of membership of different correction amount different directions；Z is
Corresponding degree of membership abscissa.
5. a kind of internal PID fuzzy control method based on PLC board according to claim 4, which is characterized in that will
The correction amount parameter, Δ k arrivedp、Δki、ΔkdBring formula into
kp=kp0+Δkp
ki=ki0+Δki
kd=kd0+Δkd
The output valve of three control parameters of PID controller can be obtained.
6. a kind of internal PID fuzzy control method based on PLC board according to claim 1, which is characterized in that PID
The value that controller exports three control parameters is obtained by following formula:
7. a kind of internal PID fuzzy control method based on PLC board according to claim 2, which is characterized in that measurement
It is worth error e=r (k)-y (k), r (k) is control target value, and y (k) is actual measurement value of feedback；
Error rate ec=e (k)-e (k-1)；
E (k) indicates current control target value and surveys the deviation of value of feedback；E (k-1) indicates that upper one claps control target value and actual measurement
The deviation of value of feedback.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110308647A (en) * | 2019-06-14 | 2019-10-08 | 南京理工大学 | The unmanned plane three-stage fuzzy PID control method of the input item containing error intergal |
| CN110764406A (en) * | 2019-10-30 | 2020-02-07 | 深圳市德沃先进自动化有限公司 | High-performance temperature control system for LED wire bonding machine |
| CN111258263A (en) * | 2020-02-24 | 2020-06-09 | 邯郸钢铁集团有限责任公司 | Secondary development design method of fuzzy controller based on Siemens _ PLC platform |
| CN111486578A (en) * | 2020-04-23 | 2020-08-04 | 五邑大学 | Air conditioner control device, method and equipment |
| CN112034700A (en) * | 2020-09-10 | 2020-12-04 | 云南电网有限责任公司电力科学研究院 | Bolt fastening compliance control method for high-voltage wire damper |
| CN112305912A (en) * | 2020-10-16 | 2021-02-02 | 贵州航天乌江机电设备有限责任公司 | Feedforward pressure control method based on reaction kettle parameter self-adjusting fuzzy PID algorithm |
| CN117193243A (en) * | 2023-09-18 | 2023-12-08 | 徐州市三禾自动控制设备有限公司 | Remote control system of PLC control cabinet |
| CN117555231A (en) * | 2023-05-30 | 2024-02-13 | 中国航空工业集团公司沈阳空气动力研究所 | Wind tunnel flow field control method based on fuzzy rule, electronic equipment and storage medium |
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110308647A (en) * | 2019-06-14 | 2019-10-08 | 南京理工大学 | The unmanned plane three-stage fuzzy PID control method of the input item containing error intergal |
| CN110308647B (en) * | 2019-06-14 | 2022-05-17 | 南京理工大学 | Unmanned aerial vehicle three-section fuzzy PID control method containing error integral input item |
| CN110764406A (en) * | 2019-10-30 | 2020-02-07 | 深圳市德沃先进自动化有限公司 | High-performance temperature control system for LED wire bonding machine |
| CN111258263A (en) * | 2020-02-24 | 2020-06-09 | 邯郸钢铁集团有限责任公司 | Secondary development design method of fuzzy controller based on Siemens _ PLC platform |
| CN111486578A (en) * | 2020-04-23 | 2020-08-04 | 五邑大学 | Air conditioner control device, method and equipment |
| CN112034700A (en) * | 2020-09-10 | 2020-12-04 | 云南电网有限责任公司电力科学研究院 | Bolt fastening compliance control method for high-voltage wire damper |
| CN112034700B (en) * | 2020-09-10 | 2023-03-14 | 云南电网有限责任公司电力科学研究院 | Bolt fastening compliance control method for high-voltage wire damper |
| CN112305912A (en) * | 2020-10-16 | 2021-02-02 | 贵州航天乌江机电设备有限责任公司 | Feedforward pressure control method based on reaction kettle parameter self-adjusting fuzzy PID algorithm |
| CN117555231A (en) * | 2023-05-30 | 2024-02-13 | 中国航空工业集团公司沈阳空气动力研究所 | Wind tunnel flow field control method based on fuzzy rule, electronic equipment and storage medium |
| CN117555231B (en) * | 2023-05-30 | 2024-04-19 | 中国航空工业集团公司沈阳空气动力研究所 | Wind tunnel flow field control method based on fuzzy rule, electronic equipment and storage medium |
| CN117193243A (en) * | 2023-09-18 | 2023-12-08 | 徐州市三禾自动控制设备有限公司 | Remote control system of PLC control cabinet |
| CN117193243B (en) * | 2023-09-18 | 2024-03-19 | 徐州市三禾自动控制设备有限公司 | Remote control system of PLC control cabinet |
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Application publication date: 20190308 |