CN108132603A - A kind of Self-tuning Fuzzy PID Control and system - Google Patents
A kind of Self-tuning Fuzzy PID Control and system Download PDFInfo
- Publication number
- CN108132603A CN108132603A CN201711393916.8A CN201711393916A CN108132603A CN 108132603 A CN108132603 A CN 108132603A CN 201711393916 A CN201711393916 A CN 201711393916A CN 108132603 A CN108132603 A CN 108132603A
- Authority
- CN
- China
- Prior art keywords
- signal
- self
- error
- differentiator
- fuzzy
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Feedback Control In General (AREA)
Abstract
This application discloses a kind of Self-tuning Fuzzy PID Controls, and error tracking signal and error differential signal are obtained including being utilized respectively tracker and differentiator;Tracker and differentiator are mutual indepedent;Using fuzzy selftuning PID algorithm, signal is tracked according to error and error differential signal carries out pid parameter Self-tuning System, total control amount is calculated, and export to controlled device according to the pid parameter after Self-tuning System, controlled device to be adjusted control.The application uses mutually independent tracker and differentiator, it can be by rationally setting tracker and the respective relevant parameter of differentiator, to obtain the preferable error tracking signal of performance and error differential signal respectively, the contradiction between noise amplification, wave distortion problem when avoiding phase delay problem when carrying out signal trace and carrying out signal differentiation, and then effectively improve whole control effect.Disclosed herein as well is a kind of Self-tuning Fuzzy PID Control System, equally with above-mentioned advantageous effect.
Description
Technical field
This application involves automatic control technology field, more particularly to a kind of Self-tuning Fuzzy PID Control and system.
Background technology
PID control technology is still the elementary process control technology generally used in industry spot at present.Fuzzy self- turning
PID control technology combines fuzzy intelligentcontrol technology and pid parameter Self-tuning System skill on the basis of classical PID control technology
Art exports rational total control amount according to the differential signal of error signal and error signal, and controlled device is made to have relatively
Good dynamic property and static properties.
In the prior art, in order to solve the contradiction during PID control between rapidity and overshoot, active disturbance rejection control is utilized
Nonlinear Tracking Differentiator in system comes to the error signal of system into line trace and differential, so as to according to obtained tracking signal and differential
Signal carries out fuzzy self-turning PID control.
But due to being to come output tracking signal and differential signal using same Nonlinear Tracking Differentiator in the prior art, i.e.,
It is identical with for generating the relevant parameter of differential signal for generating the relevant parameter of tracking signal, and same set of parameter is
It can not obtain perfectly tracking signal and differential signal simultaneously, so the phase delay problem of tracking signal and differential signal
Noise amplification, wave distortion problem can not always solve simultaneously so that there is contradictions between two signals.
It can be seen that using which kind of Self-tuning Fuzzy PID Control so as to simultaneously solve carry out signal trace when phase
Noise amplification, wave distortion problem when position delay issue and progress signal differentiation, and then control effect is improved, it is this field skill
The important technological problems solved required for art personnel.
Invention content
The application's is designed to provide a kind of Self-tuning Fuzzy PID Control and system, effectively to solve simultaneously
Certainly noise amplification during phase delay problem and signal differentiation during signal trace, wave distortion problem, and then improve control effect
Fruit.
In order to solve the above technical problems, the application provides a kind of Self-tuning Fuzzy PID Control, including:
It is utilized respectively tracker and differentiator obtains error tracking signal and error differential signal;The tracker and described
Differentiator is mutual indepedent;
Using fuzzy selftuning PID algorithm, signal is tracked according to the error and the error differential signal carries out PID ginsengs
Number Self-tuning System calculates total control amount according to the pid parameter after Self-tuning System, and exports to controlled device, so as to described controlled pair
As control is adjusted.
Optionally, it is described to be utilized respectively that tracker and differentiator obtain error tracking signal and error differential signal includes:
The first tracking signal and the system for being utilized respectively the first tracker and the second tracker acquisition system input signal are defeated
Go out the second tracking signal of signal;It is utilized respectively the first differentiator and the second differentiator obtains the first of the system input signal
Second differential signal of differential signal and the system output signal;
The difference of described first tracking signal and the second tracking signal is tracked into signal as the error;By described
The difference of one differential signal and second differential signal is as the error differential signal.
Optionally, the expression formula of the tracker is:
Wherein, v is the input signal of the tracker;V1 is the tracking signal of v;V2 is the differential signal of v1;T1 is institute
State the integration step of tracker;R1 is the velocity factor of the tracker;H1 is the filtering factor of the tracker;N is forecast
Compensate step-length, n>1.
Optionally, n ∈ [2,2h1T1].
Optionally, the expression formula of the differentiator is:
Wherein, u is the input signal of the differentiator;U1 is the tracking signal of u;U2 is the differential signal of u1;T2 is institute
State the integration step of differentiator;R2 is the velocity factor of the differentiator;H2 is the filtering factor of the differentiator.
Optionally, T1=T2, h1=h2 and r1=r2.
Optionally, the fuzzy self-turning PID control algorithm is the fuzzy self-turning PID control algorithm of discrete domain.
Optionally, the fuzzy self-turning PID control algorithm is two dimension fuzzy self-regulated PID control algorithm.
Optionally, the pid parameter according to after Self-tuning System calculates total control amount and includes:
The total control amount is calculated according to following PID control calculation formula:
Wherein, U(k+1)Total control amount for the k+1 moment;Kp (k+1)、Ki (k+1)And Kd (k+1)It is the PID ginsengs at k+1 moment
Number;e(i)The error for the i moment tracks signal;The error differential signal for the k+1 moment.
Present invention also provides a kind of Self-tuning Fuzzy PID Control System, including:
Tracker:For obtaining error tracking signal;
Differentiator:For obtaining error differential signal;The tracker and the differentiator are mutual indepedent;
Fuzzy Self-Tuning PID Controller:For use fuzzy selftuning PID algorithm, according to the error track signal and
The error differential signal carries out pid parameter Self-tuning System;Total control amount is calculated, and export extremely according to the pid parameter after Self-tuning System
Controlled device, so that control is adjusted to the controlled device.
Self-tuning Fuzzy PID Control provided herein includes:It is utilized respectively tracker and differentiator is obtained and missed
Difference tracking signal and error differential signal;The tracker and the differentiator are mutual indepedent;It is calculated using fuzzy selftuning PID
Method tracks signal according to the error and the error differential signal carries out pid parameter Self-tuning System, according to the PID after Self-tuning System
Parameter calculates total control amount, and exports to controlled device, so that control is adjusted to the controlled device.
As it can be seen that compared with the prior art, in Self-tuning Fuzzy PID Control provided herein, using mutually solely
Vertical tracker and differentiator obtain error tracking signal and error differential signal respectively, so as to by rationally set with
Track device and the respective relevant parameter of differentiator to obtain the preferable error tracking signal of performance and error differential signal respectively, are kept away
Phase delay problem when having exempted to carry out signal trace and wave distortion when carrying out signal differentiation, between noise scale-up problem
Contradiction, and then effectively improve the whole control effect of system.
Description of the drawings
In order to illustrate more clearly of the technical solution in the prior art and the embodiment of the present application, below will to the prior art and
Attached drawing to be used is needed to make brief introduction in the embodiment of the present application description.Certainly, the attached drawing in relation to the embodiment of the present application below
Part of the embodiment in only the application of description, to those skilled in the art, is not paying creativeness
Under the premise of labour, other attached drawings can also be obtained according to the attached drawing of offer, the other accompanying drawings obtained also belong to the application
Protection domain.
The flow chart of a kind of Self-tuning Fuzzy PID Control that Fig. 1 is provided by the embodiment of the present application;
The control block diagram of a kind of Self-tuning Fuzzy PID Control that Fig. 2 is provided by the embodiment of the present application;
The oscillogram of a kind of system input signal that Fig. 3 is provided by the embodiment of the present application;
Fig. 4 is the oscillogram that the error according to obtained from system shown in Figure 3 input signal tracks signal;
Fig. 5 is the oscillogram of the error differential signal according to obtained from system shown in Figure 3 input signal;
Fig. 6 is the oscillogram of the system output signal according to obtained from system shown in Figure 3 input signal;
The oscillogram of another system input signal that Fig. 7 is provided by the embodiment of the present application;
Fig. 8 is the oscillogram that the error according to obtained from system shown in Figure 7 input signal tracks signal;
Fig. 9 is the oscillogram of the error differential signal according to obtained from system shown in Figure 7 input signal;
Figure 10 is the oscillogram of the system output signal according to obtained from system shown in Figure 7 input signal;
The structure diagram of a kind of Self-tuning Fuzzy PID Control System that Figure 11 is provided by the embodiment of the present application.
Specific embodiment
The core of the application is to provide a kind of Self-tuning Fuzzy PID Control and system, effectively to solve simultaneously
Certainly wave distortion during phase delay problem and signal differentiation during signal trace, noise scale-up problem, and then improve control effect
Fruit.
In order to more clearly and completely be described to the technical solution in the embodiment of the present application, below in conjunction with this Shen
Attached drawing that please be in embodiment, is introduced the technical solution in the embodiment of the present application.Obviously, described embodiment is only
Some embodiments of the present application, instead of all the embodiments.Based on the embodiment in the application, those of ordinary skill in the art
All other embodiments obtained without making creative work shall fall in the protection scope of this application.
It please refers to Fig.1, the flow chart of a kind of Self-tuning Fuzzy PID Control that Fig. 1 is provided by the embodiment of the present application,
It mainly includes the following steps that:
Step 1:It is utilized respectively tracker and differentiator obtains error tracking signal and error differential signal.
Wherein, tracker and differentiator are mutual indepedent.
Specifically, error is equally tracked signal and error by the Self-tuning Fuzzy PID Control provided in the application
Differential signal is for carrying out fuzzy self-turning PID control, to eliminate the lance during PID control between rapidity and overshoot problem
Shield.But different from the prior art, the application specifically using mutually independent tracker and differentiator, is distinguished using the two
The error tracking signal and error differential signal of acquisition system.Therefore, the tracker in the application and differentiator can be adopted respectively
With respectively parameter the most suitable, signal and error differential signal are tracked to respectively obtain error the most accurate.
What needs to be explained here is that fuzzy self-turning PID control is a kind of closed-loop control with output feedback, control
Target is to enable the stable output signal of system in the input signal of system.Here the error being previously mentioned and hereinafter, which is each meant, is
Error between the input signal of system and the output signal of system.
Certainly, after the structure for employing mutually independent tracker and differentiator, the concrete kind of tracker and differentiator
Type voluntarily can also be selected and set according to actual conditions by those skilled in the art.For example, due in active disturbance rejection algorithm with
Track differentiator has the function of following function and differential simultaneously, thus can still be specifically chosen Nonlinear Tracking Differentiator as tracker or
Person's differentiator;For another example it can also select to obtain differential signal such as the differentiator of orthogonal mixing scheduling algorithm using other.
Step 2:Using fuzzy selftuning PID algorithm, signal is tracked according to error and error differential signal carries out pid parameter
Self-tuning System calculates total control amount, and export to controlled device, to be carried out to controlled device according to the pid parameter after Self-tuning System
Adjusting control.
Specifically, fuzzy selftuning PID algorithm can be tracked according to the error of system signal and error differential signal and
Preset fuzzy rule carries out Self-tuning System, to obtain the preferable PID of instant control effect to the pid parameter during PID control
Parameter, and using the pid parameter output controlled quentity controlled variable after adjusting, act on controlled device, its stable output signal is made to believe in input
Number, reach control targe state.
As it can be seen that in the Self-tuning Fuzzy PID Control that the embodiment of the present application is provided, using mutually independent tracker
Error tracking signal and error differential signal are obtained respectively with differentiator, so as to by rationally setting tracker and differential
The respective relevant parameter of device to obtain the preferable error tracking signal of performance and error differential signal respectively, avoids and carries out letter
Phase delay problem during number tracking and wave distortion when carrying out signal differentiation, the contradiction between noise scale-up problem, and then
Effectively improve the whole control effect of system.
Self-tuning Fuzzy PID Control provided herein, on the basis of above-described embodiment:
It please refers to Fig.2, the controller chassis of a kind of Self-tuning Fuzzy PID Control that Fig. 2 is provided by the embodiment of the present application
Figure.
As shown in Fig. 2, as a kind of preferred embodiment, it is utilized respectively tracker and differentiator obtains error tracking signal e
With error differential signalIncluding:
It is utilized respectively the first tracker and the second tracker obtains the first tracking signal x1 and system of system input signal x
The second tracking signal y1 of output signal y;It is utilized respectively the first differentiator and the second differentiator obtain system input signal x the
The second differential signal y2 of one differential signal x2 and system output signal y;
Using the difference of the first tracking signal x1 and the second tracking signal y1 as error tracking signal e;By the first differential signal
The difference of x2 and the second differential signal y2 are as error differential signal
Specifically, because error is the error of system input signal x and system output signal y, it is possible to utilize two
Tracker obtains the second tracking signal y1 of the first tracking signal x1 and system output signal y of system input signal x respectively, so
Afterwards by subtracting each other to obtain error tracking signal e.
Similarly, two differentiators can be utilized to obtain the first differential signal x2 and system of system input signal x respectively
The second differential signal y2 of output signal y, then by subtracting each other to obtain error tracking signal
In addition, those skilled in the art can also add the control method of single differentiator only with single tracker, i.e., will be first
Input signal x and system output signal y unite after difference obtains error signal, is being utilized respectively tracker and differentiator to error
Signal obtains error tracking signal e and error differential signal into line trace and differentialCertainly, the tracking object of both methods
Difference, obtained error tracking signal e and error differential signalOccurrence it is also different.In fact, double tracker adds double differential
The control method of device is advanced line trace, difference is remake after smooth tracking result is obtained, therefore it is compared to single tracker
Add the control method of single differentiator that there is the effect of controls in advance, can more effectively inhibit overshoot.
As a kind of preferred embodiment, the expression formula of tracker is:
Wherein, v is the input signal of tracker;V1 is the tracking signal of v;V2 is the differential signal of v1;T1 is tracker
Integration step;R1 is the velocity factor of tracker;H1 is the filtering factor of tracker;N be compensation prediction step-length, n>1.
Specifically, as previously mentioned, the tracker that the embodiment of the present application is provided, specifically may be used in Active Disturbance Rejection Control
The identical structure of Nonlinear Tracking Differentiator, then the tracking signal that the v1 exported is obtained required for being.Compared to it is conventional without
The Nonlinear Tracking Differentiator of compensation prediction (i.e. compensation prediction step-length n is 1), Nonlinear Tracking Differentiator adopted here are walked by compensation prediction
Long n>1 setting can further speed up tracking process, and to the input signal of tracker into line trace, output tracking signal has
Effect solves the problems, such as the phase delay of error tracking signal.
In above-mentioned expression formula, fhan functions are the time-optimal control comprehensive functions in automation field, it can be reasonable
Ground arranges control terminal transient process, achievees the effect that solve the contradiction between response speed and overshoot.Fhan functions it is specific
Expression formula is:
As a kind of preferred embodiment, n ∈ [2,2h1T1].
Specifically, when carrying out compensation prediction, the value of compensation prediction step-length n cannot be excessive simply, otherwise will cause tight
Situations such as overshoot is even shaken again.Rule of thumb, the value range of compensation prediction step-length n that the embodiment of the present application is provided is preferred
For n ∈ [2,2h1T1].Certainly, those skilled in the art can voluntarily select best compensation prediction according to practical situations
Step-length n, to obtain preferable control effect, the embodiment of the present application is not defined this.
As a kind of preferred embodiment, the expression formula of differentiator is:
Wherein, u is the input signal of differentiator;U1 is the tracking signal of u;U2 is the differential signal of u1;T2 is differentiator
Integration step;R2 is the velocity factor of differentiator;H2 is the filtering factor of differentiator.
Similarly, according to described previously, differentiator provided in the embodiment of the present application equally can with selected as with from anti-
The identical structure of Nonlinear Tracking Differentiator in algorithm is disturbed, then the u2 exported as needs obtained differential signal.
It should be noted that due to for differentiator, emphasis is to utilize its differential fuction output differential signal, there is no need to
Rapidity is excessively pursued, in order to avoid influencing the quality of differential signal, causes noise amplification and wave distortion, therefore, differential here
Device is different from the tracker introduced above, specifically using the structure of the Nonlinear Tracking Differentiator without compensation prediction, that is, forecasts
Compensate step-length n=1.
As a kind of preferred embodiment, T1=T2, h1=h2 and r1=r2.
Specifically, in the embodiment of the present application, tracker and differentiator are actually needed to same signal respectively into line trace
And differential, therefore, other than compensation prediction step-length n this parameter differences, tracker and remaining corresponding parameter of differentiator are excellent
It is selected as unanimously, i.e., the integration step of the two, velocity factor and filtering factor difference are equal.
Certainly, those skilled in the art can also select the differentiator of other forms according to practical situations, such as adopt
Differentiator with orthogonal mixing method etc., and can voluntarily select and set the specific value of relevant parameter, the embodiment of the present application pair
This is not defined.
As a kind of preferred embodiment, fuzzy self-turning PID control algorithm is the fuzzy self-turning PID control of discrete domain
Algorithm.
Specifically, using the fuzzy self-turning PID control algorithm of discrete domain, calculation amount can be effectively largely reduced,
Simplify control process improves control effect.
As a kind of preferred embodiment, fuzzy self-turning PID control algorithm is two dimension fuzzy self-regulated PID control algorithm.
Specifically, it is secondary micro- can also further to ask for error in the technology of the embodiment of the present application by those skilled in the art
Sub-signal, to carry out three-dimensional fuzzy self-turning PID control, but its calculating process is complex.In contrast, using two dimension
The fuzzy self-turning PID control of structure, obtained control accuracy meet general demand for control enough, do not influence control effect
Fruit, while computation burden will not be increased again, therefore use is more extensive.
As a kind of preferred embodiment, total control amount is calculated according to the pid parameter after Self-tuning System and is included:
Total control amount is calculated according to following PID control calculation formula:
Wherein, U(k+1)Total control amount for the k+1 moment;Kp (k+1)、Ki (k+1)And Kd (k+1)It is the pid parameter at k+1 moment;
e(i)Error for the i moment tracks signal;Error differential signal for the k+1 moment.
Specifically, the Self-tuning Fuzzy PID Control that the embodiment of the present application is provided, in the calculating for carrying out total control amount
When, in order to further eliminate the adverse effect of integration, the integration control during classical PID is controlled is replaced for control of summing, can
Integration control lag issues are effectively eliminated,.
The fuzzy self-turning PID control side that the embodiment of the present application is provided is introduced below in conjunction with specific controlled device
A kind of Application Example of method.
If controlled device is a second-order system, transmission function is:
Then according to such as Fig. 2 controller chassises control method shown in figure, to y points of system input signal x and system output signal
Not into line trace and differential, the first tracking signal x1 and the first differential signal x2 and the system for obtaining system input signal x are defeated
Go out the second tracking signal y1 and the second differential signal y2 of signal y, and then error tracking signal e and error differential letter are obtained as difference
NumberThe discrete domain Fuzzy Self-Tuning PID Controller of two dimension is input to, master control is exported after pid parameter Self-tuning System has been carried out
Measure U.
When carrying out pid parameter and adjusting, to the error discrete domains that specifically set of tracking signal e as [- 6, -5, -4, -
3, -2, -1,0,1,2,3,4,5,6], the fuzzy subset specifically set is { NB (negative big), NM (in negative), NS (negative small), NZ
(negative zero), PZ (positive zero), PS (just small), PM (center), PB (honest) }, wherein, the membership function such as table of each fuzzy subset
Shown in 1;To error differential signalAnd the fine tuning variable Δ K of pid parameterp、ΔKiWith Δ KdThe discrete domain specifically set
It is [- 3, -2, -1,0,1,2,3] that the fuzzy subset specifically set is { NB (negative big), NM (in negative), NS (negative small), ZO
(zero), PS (just small), PM (center), PB (honest) }, error differential signalFinely tune variable Δ Kp、ΔKiOr Δ KdIt is each
The membership function of fuzzy subset is as shown in table 2.
Table 1
Table 2
In pid parameter difference when carrying out Self-tuning System to three pid parameters, obtained after specifically adjusting by fuzzy control
For:
Wherein, Kp (k)、Ki (k)And Kd (k)It is the pid parameter at k moment;Finely tune variable Δ Kp、ΔKiWith Δ KdSpecifically by accidentally
Difference tracking signal e, error differential signalAnd corresponding fuzzy tuning rule list determines.Table 3, table 4 and table 5 are respectively Δ Kp、
ΔKiWith Δ KdFuzzy tuning rule list.
Table 3
Table 4
Table 5
Signal e and error differential signal are tracked according to errorMembership function table and fine tuning variable Δ KpIt is fuzzy whole
Determine rule list, fine tuning variable Δ K can be obtainedpSpecific control table, as shown in table 6.
Table 6
Signal e and error differential signal are tracked according to errorMembership function table and fine tuning variable Δ KiIt is fuzzy whole
Determine rule list, fine tuning variable Δ K can be obtainediSpecific control table, as shown in table 7.
Table 7
Signal e and error differential signal are tracked according to errorMembership function table and fine tuning variable Δ KdIt is fuzzy whole
Determine rule list, fine tuning variable Δ K can be obtaineddSpecific control table, as shown in table 8.
Table 8
After pid parameter after being adjusted by above-mentioned tuning process, you can calculated according to previously described PID control
Formula calculates the total control amount U for being input to controlled device, so that the system output signal y to controlled device is adjusted, reaches
To control targe.
If system input signal x is unit step signal, as shown in figure 3, the obtained mistake in this application embodiment
Difference tracking signal e and error differential signalOscillogram respectively as shown in Figure 4 and Figure 5;And final system output signal y
Oscillogram is as shown in Figure 6.
From fig. 4 to fig. 6 it is found that the obtained error tracking signal e of the embodiment of the present application and error differential signalCurve
Smooth, signal quality is preferable;And also the same smooth and non-overshoots of system output signal y, control effect are preferable.
If system input signal x is the unit step signal with white noise, as shown in fig. 7, in this application embodiment
In obtained error tracking signal e and error differential signalOscillogram respectively as shown in Figure 8 and Figure 9;And final system
The oscillogram of output signal y is as shown in Figure 10.
From Fig. 7 to Figure 10 it is found that the obtained error tracking signal e of the embodiment of the present application and error differential signalIt is being
Input signal x unite there are during serious noise jamming, can still obtain relatively smooth curve, there is preferable filtering to make
With with noise suppression ability;Thus simultaneously but also also the same smooth and non-overshoots of system output signal y, there is preferable control to imitate
Fruit.
The Self-tuning Fuzzy PID Control System provided below the embodiment of the present application is introduced.
Please refer to Fig.1 the structure diagram that 1, Figure 11 is a kind of Self-tuning Fuzzy PID Control System provided herein;Packet
Include tracker 1, differentiator 2, Fuzzy Self-Tuning PID Controller 3 and controlled device 4;
Tracker 1 tracks signal for obtaining error;
Differentiator 2 is used to obtain error differential signal;Tracker 1 and differentiator 2 are mutual indepedent;
Fuzzy Self-Tuning PID Controller 3 is used for using fuzzy selftuning PID algorithm, and signal and error are tracked according to error
Differential signal carries out pid parameter Self-tuning System;Total control amount is calculated, and export to controlled device according to the pid parameter after Self-tuning System
4, controlled device to be adjusted control.
As it can be seen that Self-tuning Fuzzy PID Control System provided herein, using mutually independent tracker 1 and differential
Device 2 tracks signal and error differential signal to obtain error respectively, so as to by rationally setting tracker 1 and differentiator 2
Respective relevant parameter to obtain the preferable error tracking signal of performance and error differential signal respectively, avoids carry out signal
Phase delay problem during tracking and noise amplification when carrying out signal differentiation, the contradiction between wave distortion problem, Jin Eryou
Imitate the whole control effect of raising system.
The specific embodiment of Self-tuning Fuzzy PID Control System provided herein obscures certainly with as described above
Tuning PID Controller method can correspond reference, just repeat no more here.
Each embodiment is described by the way of progressive in the application, the highlights of each of the examples are with other realities
Apply the difference of example, just to refer each other for identical similar portion between each embodiment.For system disclosed in embodiment
Speech, since it is corresponded to the methods disclosed in the examples, so description is fairly simple, related part is referring to method part illustration
.
It should be noted that in present specification, the relational terms of such as " first " and " second " etc are used merely to
One entity is either operated and is distinguished with another entity or operation, without necessarily requiring or implying these entities or
There are any actual relationship or orders between person's operation.In addition, term " comprising ", "comprising" or its any other
Variant is intended to non-exclusive inclusion, so that process, method, article or equipment including a series of elements are not only
Including those elements, but also including other elements that are not explicitly listed or further include as this process, method, object
Product or the intrinsic element of equipment.In the absence of more restrictions, the element limited by sentence "including a ...",
It is not precluded in the process, method, article or apparatus that includes the element that also there are other identical elements.
Technical solution provided herein is described in detail above.Specific case used herein is to this Shen
Principle and embodiment please is expounded, the explanation of above example is only intended to help understand the present processes and its
Core concept.It should be pointed out that for those skilled in the art, in the premise for not departing from the application principle
Under, can also to the application, some improvement and modification can also be carried out, these improvement and modification also fall into the protection of the application claim
In the range of.
Claims (10)
1. a kind of Self-tuning Fuzzy PID Control, which is characterized in that including:
It is utilized respectively tracker and differentiator obtains error tracking signal and error differential signal;The tracker and the differential
Device is mutual indepedent;
Using fuzzy selftuning PID algorithm, signal is tracked according to the error and the error differential signal carries out pid parameter certainly
Adjust, total control amount calculated, and export to controlled device according to the pid parameter after Self-tuning System, so as to the controlled device into
Row adjusting control.
2. Self-tuning Fuzzy PID Control according to claim 1, which is characterized in that described to be utilized respectively tracker
Error tracking signal is obtained with differentiator and error differential signal includes:
It is utilized respectively the first tracker and the second tracker obtains the first tracking signal of system input signal and system output letter
Number second tracking signal;It is utilized respectively the first differentiator and the second differentiator obtains the first differential of the system input signal
Second differential signal of signal and the system output signal;
The difference of described first tracking signal and the second tracking signal is tracked into signal as the error;It is micro- by described first
The difference of sub-signal and second differential signal is as the error differential signal.
3. Self-tuning Fuzzy PID Control according to claim 1, which is characterized in that the expression formula of the tracker
For:
Wherein, v is the input signal of the tracker;V1 is the tracking signal of v;V2 is the differential signal of v1;T1 for it is described with
The integration step of track device;R1 is the velocity factor of the tracker;H1 is the filtering factor of the tracker;N is compensation prediction
Step-length, n>1.
4. Self-tuning Fuzzy PID Control according to claim 3, which is characterized in that n ∈ [2,2h 1/T 1].
5. Self-tuning Fuzzy PID Control according to claim 3, which is characterized in that the expression formula of the differentiator
For:
Wherein, u is the input signal of the differentiator;U1 is the tracking signal of u;U2 is the differential signal of u1;T2 is described micro-
Divide the integration step of device;R2 is the velocity factor of the differentiator;H2 is the filtering factor of the differentiator.
6. Self-tuning Fuzzy PID Control according to claim 5, which is characterized in that T1=T2, h1=h2 and r1=
r2。
7. Self-tuning Fuzzy PID Control according to claim 5, which is characterized in that the fuzzy selftuning PID control
Algorithm processed is the fuzzy self-turning PID control algorithm of discrete domain.
8. Self-tuning Fuzzy PID Control according to claim 7, which is characterized in that the fuzzy selftuning PID control
Algorithm processed is two dimension fuzzy self-regulated PID control algorithm.
9. according to claim 1 to 8 any one of them Self-tuning Fuzzy PID Control, which is characterized in that the basis is certainly
Pid parameter after adjusting calculates total control amount and includes:
The total control amount is calculated according to following PID control calculation formula:
Wherein, U(k+1)Total control amount for the k+1 moment;Kp (k+1)、Ki (k+1)And Kd (k+1)It is the pid parameter at k+1 moment;
e(i)The error for the i moment tracks signal;The error differential signal for the k+1 moment.
10. a kind of Self-tuning Fuzzy PID Control System, which is characterized in that including:
Tracker:For obtaining error tracking signal;
Differentiator:For obtaining error differential signal;The tracker and the differentiator are mutual indepedent;
Fuzzy Self-Tuning PID Controller:For using fuzzy selftuning PID algorithm, signal and described is tracked according to the error
Error differential signal carries out pid parameter Self-tuning System;Total control amount is calculated according to the pid parameter after Self-tuning System, and is exported to controlled
Object, so that control is adjusted to the controlled device.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201711393916.8A CN108132603A (en) | 2017-12-21 | 2017-12-21 | A kind of Self-tuning Fuzzy PID Control and system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201711393916.8A CN108132603A (en) | 2017-12-21 | 2017-12-21 | A kind of Self-tuning Fuzzy PID Control and system |
Publications (1)
Publication Number | Publication Date |
---|---|
CN108132603A true CN108132603A (en) | 2018-06-08 |
Family
ID=62392084
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201711393916.8A Pending CN108132603A (en) | 2017-12-21 | 2017-12-21 | A kind of Self-tuning Fuzzy PID Control and system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN108132603A (en) |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109634336A (en) * | 2018-11-07 | 2019-04-16 | 广东核电合营有限公司 | A kind of differential summing circuit and electrical equipment |
CN110147129A (en) * | 2019-05-16 | 2019-08-20 | 湖北问天软件系统有限公司 | The adaptive temperature controller and control method of baking tray |
CN111965971A (en) * | 2020-08-21 | 2020-11-20 | 北京石油化工学院 | Expert control system creating method and device |
CN112346334A (en) * | 2019-08-06 | 2021-02-09 | 北京东土科技股份有限公司 | Configuration method, device and equipment of fuzzy control parameters and storage medium |
CN112436571A (en) * | 2020-11-12 | 2021-03-02 | 中国海洋大学 | Charging control method, device and system based on fuzzy self-adaptive PID control |
-
2017
- 2017-12-21 CN CN201711393916.8A patent/CN108132603A/en active Pending
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109634336A (en) * | 2018-11-07 | 2019-04-16 | 广东核电合营有限公司 | A kind of differential summing circuit and electrical equipment |
CN110147129A (en) * | 2019-05-16 | 2019-08-20 | 湖北问天软件系统有限公司 | The adaptive temperature controller and control method of baking tray |
CN112346334A (en) * | 2019-08-06 | 2021-02-09 | 北京东土科技股份有限公司 | Configuration method, device and equipment of fuzzy control parameters and storage medium |
CN111965971A (en) * | 2020-08-21 | 2020-11-20 | 北京石油化工学院 | Expert control system creating method and device |
CN112436571A (en) * | 2020-11-12 | 2021-03-02 | 中国海洋大学 | Charging control method, device and system based on fuzzy self-adaptive PID control |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN108132603A (en) | A kind of Self-tuning Fuzzy PID Control and system | |
Yu et al. | Barrier Lyapunov functions-based command filtered output feedback control for full-state constrained nonlinear systems | |
Mehedi et al. | Two degrees of freedom fractional controller design: Application to the ball and beam system | |
CN108205259B (en) | Composite control system based on linear extended state observer and design method thereof | |
Yuan et al. | Fixed-time SOSM controller design with output constraint | |
You et al. | Command filter-based adaptive fuzzy finite-time tracking control for uncertain fractional-order nonlinear systems | |
CN101375219A (en) | Techniques for switching between controllers | |
CN108828950A (en) | A kind of adaptive Auto-disturbance-rejection Control, device and equipment | |
CN102540887A (en) | Control method of non-linear parameterization system | |
CN109946979A (en) | A kind of self-adapting regulation method of servo-system sensitivity function | |
CN108803310A (en) | A kind of PID control method, device and equipment | |
CN109901511A (en) | A kind of control algolithm of servo-system profile errors | |
CN111123709A (en) | Active-disturbance-rejection control method for hearth pressure system of coking furnace | |
CN105867125A (en) | Optimization control method and apparatus of refining apparatus coupling unit | |
WO2019087554A1 (en) | Feedback control method and motor control device | |
JP3950015B2 (en) | Process control device | |
Wang et al. | Robust H/sub/spl infin//filtering for LPV discrete-time state-delayed systems | |
Zhang et al. | Adaptive asymptotic tracking control design for high-order uncertain nonlinear systems | |
Chen et al. | Adaptive neural dynamic surface control with fixed-time prescribed performance for uncertain nonstrict-feedback stochastic switched systems | |
Xin et al. | Finite time adaptive learning for tracking control of constraint nonlinear systems via command filtered output feedback | |
CN112904798B (en) | Two-axis motion system contour error compensation method and device based on time-frequency analysis | |
Aravinth et al. | Disturbance suppression based quantized tracking control for periodic piecewise polynomial systems | |
CN112987561B (en) | Robust filter type iterative learning control method for finite time trajectory tracking | |
Xia et al. | Event-based adaptive fuzzy control for stochastic nonlinear systems with prescribed performance | |
Park et al. | Decentralized output-feedback controller for uncertain large-scale nonlinear systems using higher-order switching differentiator |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180608 |