CN107508506A - A kind of brshless DC motor fuzzy-adaptation PID control governing system and method - Google Patents
A kind of brshless DC motor fuzzy-adaptation PID control governing system and method Download PDFInfo
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- CN107508506A CN107508506A CN201710867664.1A CN201710867664A CN107508506A CN 107508506 A CN107508506 A CN 107508506A CN 201710867664 A CN201710867664 A CN 201710867664A CN 107508506 A CN107508506 A CN 107508506A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P6/00—Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
- H02P6/08—Arrangements for controlling the speed or torque of a single motor
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P6/00—Arrangements for controlling synchronous motors or other dynamo-electric motors using electronic commutation dependent on the rotor position; Electronic commutators therefor
- H02P6/08—Arrangements for controlling the speed or torque of a single motor
- H02P6/085—Arrangements for controlling the speed or torque of a single motor in a bridge configuration
Abstract
The present invention proposes a kind of brshless DC motor fuzzy-adaptation PID control governing system and method, including：According to fuzzy control theory, the fuzzy controller module of Speed Regulation Systems of BLDCM is established；Establish Speed Regulation Systems of BLDCM module；Establish the object function of the fuzzy controller parameter optimization of Speed Regulation Systems of BLDCM；Obtain fuzzy controller Kp、Ki、KdWith error e and error rate ecBetween fuzzy relation, according to detection error e and error rate ecValue, and fuzzy control rule, to Kp、Ki、KdThree parameters are modified.The present invention also accordingly provides fuzzy control equipment, the rotational speed regulation in PID control system is used into fuzzy-adaptation PID control by the method for the present invention, it has dynamic property good, and the rate of climb is fast, and overshoot is small, these good advantages of robustness.
Description
Technical field
The present invention relates to Motor Control Field, more particularly to a kind of brshless DC motor fuzzy-adaptation PID control governing system and
Method.
Background technology
Brshless DC motor is made up of motor body and driver, is a kind of product of electromechanical integration.Now with
In traditional pid algorithm control process, response speed is slow, and dynamic response is poor, at the uncertain and non-linear situation of system
Manage it is ineffective, it is difficult to be produced a desired effect in control.In Speed Regulation Systems of BLDCM, the effect of der Geschwindigkeitkreis is to increase
Strong system is to the antijamming capability of load change, the fluctuation of speed of drawing up, and is the major control link of system.Because traditional PI D is controlled
Parameter processed can not change according to controlled device parameter makes corresponding adjustment, so robustness is often unsatisfactory.
The content of the invention
Based on above mentioned problem, the present invention proposes a kind of brshless DC motor fuzzy-adaptation PID control governing system and method, will
The conciliation that fuzzy logic is used for brshless DC motor controls, and realizes the on-line tuning of tri- parameters of PID.
A kind of brshless DC motor fuzzy-adaptation PID control speed regulating method, including：
According to fuzzy control theory, the fuzzy controller module of Speed Regulation Systems of BLDCM is established；
Establish Speed Regulation Systems of BLDCM module；The governing system module includes rotating speed fuzzy controller mould
Block, electric current PID controller module, three-phase inversion bridge module, brshless DC motor body module and pwm control modules；
Establish the object function of the fuzzy controller parameter optimization of Speed Regulation Systems of BLDCM；
Obtain fuzzy controller Kp、Ki、KdWith error e and error rate ecBetween fuzzy relation, according to detection
Error e and error rate ecValue, and fuzzy control rule, to Kp、Ki、KdThree parameters are modified.
In described method, it is described establish Speed Regulation Systems of BLDCM fuzzy controller module be specially：Mould
The editor for pasting set and computing, use error e and error rate ecAs input, controlled quentity controlled variable Δ KpWith Δ KiAnd Δ KdMake
For output；Membership function is established, the membership function is triangular function；Fuzzy rule editor, it is fuzzy according to what is provided
Rule list, using method of expertise, carry out fuzzy rule editor；Generate fuzzy controller.
In described method, the acquisition fuzzy controller Kp、Ki、KdWith error e and error rate ecBetween
Fuzzy relation is specially：Determine that de-fuzzy handles mathematic(al) representation：
Z is variable, uc(z) membership function for being variable z, z0For integrationWith integrationRatio
Value；It can thus be concluded that go out precise volume { e, the e of fuzzy controlc, substitute into following formula and calculate：
Kp=Kp0+K1{e,ec}p
Ki=Kio+K2{e,ec}i
Kd=Kdo+K3{e,ec}d
Wherein Kp0, Ki0, Kd0For Kp, Ki, KdThe initial value of three parameters, Δ Kp=K1{e,ec}p, Δ Ki=K2{e,ec}i,
ΔKd=K3{e,ec}d。
A kind of brshless DC motor fuzzy-adaptation PID control governing system, including：Rotating speed fuzzy controller module, electric current
PID controller module, three-phase inversion bridge module, brshless DC motor body module and pwm control modules；The brushless dc
Machine body module includes counter electromotive force module, torque calculation module and rotor position measurement module.
The present invention establishes the said equipment, and then writes out the transmission function of whole control system, optimal controller parameter.Finally
Fuzzy logic is used for the adjustment control of brshless DC motor by fuzzy reasoning.
In general, traditional PI D speed adjusting technique phases are used with existing by the contemplated above technical scheme of the present invention
Than having the advantages that：In Speed Regulation Systems of BLDCM, the effect of der Geschwindigkeitkreis is that strengthening system changes to load
Antijamming capability, the fluctuation of speed of drawing up, be system major control link.Because traditional PID control parameter can not be according to quilt
Corresponding adjustment is made in control object parametric change, and robustness is often unsatisfactory.Therefore the design is by PID control system
Rotational speed regulation use fuzzy-adaptation PID control, it has dynamic property good, and the rate of climb is fast, and overshoot is small, and robustness is good, and these are excellent
Point.
Brief description of the drawings
, below will be to embodiment or prior art in order to illustrate more clearly of technical scheme of the invention or of the prior art
The required accompanying drawing used is briefly described in description, it should be apparent that, drawings in the following description are only in the present invention
Some embodiments recorded, for those of ordinary skill in the art, on the premise of not paying creative work, can be with
Other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 is the flow chart of Speed Regulation Systems of BLDCM fuzzy PID control method of the present invention；
Fig. 2 is a kind of brshless DC motor fuzzy-adaptation PID control governing system block diagram of the present invention；
Fig. 3 show a kind of brshless DC motor fuzzy-adaptation PID control speed control system structure figure；
Fig. 4 is control parameter e of the present invention Triangleshape grade of membership function figure；
Fig. 5 is control parameter e of the present inventioncTriangleshape grade of membership function figure；
Fig. 6 is control parameter Δ K of the present inventionpTriangleshape grade of membership function figure；
Fig. 7 is control parameter Δ K of the present inventioniTriangleshape grade of membership function figure；
Fig. 8 is control parameter Δ K of the present inventiondTriangleshape grade of membership function figure；
Fig. 9 schemes for fuzzy rule editor of the present invention；
Figure 10 is a kind of brshless DC motor fuzzy-adaptation PID control governing system example structure figure of the present invention；
Figure 11 is brshless DC motor body module structure chart of the present invention；
Figure 12 is counter electromotive force function structure chart of the present invention；
Figure 13 is torque calculation function structure chart of the present invention；
Figure 14 is rotor position measurement function structure chart of the present invention；
Figure 15 is electric current PID controller module of the present invention；
Figure 16 is pulse width modulation pwm function structure charts of the present invention；
Figure 17 is the response of the electric current, voltage, angular speed rad, rotating speed n under governing system no-load condition of the embodiment of the present invention
Curve map.
Embodiment
In order that those skilled in the art more fully understand the technical scheme in the embodiment of the present invention, and make the present invention's
Above-mentioned purpose, feature and advantage can be more obvious understandable, technical scheme in the present invention made below in conjunction with the accompanying drawings further detailed
Thin explanation.
Based on above mentioned problem, the present invention proposes a kind of brshless DC motor fuzzy-adaptation PID control governing system and method, will
The conciliation that fuzzy logic is used for brshless DC motor controls, and realizes the on-line tuning of tri- parameters of PID.
A kind of brshless DC motor fuzzy-adaptation PID control speed regulating method, as shown in figure 1, including：
S101：According to fuzzy control theory, the fuzzy controller module of Speed Regulation Systems of BLDCM is established；
The parameter and motor of motor, der Geschwindigkeitkreis, the transmission function of electric current loop and control system are as follows.Determine voltage U
=220V；L=0.015H；R=0.5 Ω；J=0.06kg.m^2；Cm=1.26；K Ω=0.132；Ia=53A；Rated speed
Ω=1460r/mim.Load feedback coefficient is set as 0.007, current feedback coefficient is 0.5.
The transmission function of motor is：
Due to T=L/R, L and R numerical value is substituted into formula above, can be calculated：(0.03s+1)/2；
The transmission function of der Geschwindigkeitkreis and electric current loop is all:
By kp、kiWith kdValue substitute into formula, can be calculated：23/1.02s；
Entirely the transmission function of control system is:
Value above is substituted into formula, calculating can (7.935s+264.5)/(1.3923*s*s+19.665s+264.5)；
S102：Establish Speed Regulation Systems of BLDCM module；The governing system module includes rotating speed fuzzy-adaptation PID control
Device module, electric current PID controller module, three-phase inversion bridge module, brshless DC motor body module and pwm control modules；On
State governing system module and use rotating speed and current double loop speed-regulating system；
S103：Establish the object function of the fuzzy controller parameter optimization of Speed Regulation Systems of BLDCM；To seek
One group of adjustment parameter make it that motor speed regulation system rise time in change working transient process is fast, overshoot is small, regulating time
It is short；
S104：Obtain fuzzy controller Kp、Ki、KdWith error e and error rate ecBetween fuzzy relation, according to
Detection error e and error rate ecValue, and fuzzy control rule, to Kp、Ki、KdThree parameters are modified.
In described method, it is described establish Speed Regulation Systems of BLDCM fuzzy controller module be specially：Mould
The editor for pasting set and computing, use error e and error rate ecAs input, controlled quentity controlled variable Δ KpWith Δ KiAnd Δ KdMake
For output；Membership function is established, the membership function is triangular function；Fuzzy rule editor, it is fuzzy according to what is provided
Rule list, using method of expertise, carry out fuzzy rule editor；Generate fuzzy controller.
Using " in the form of if A and B then C " express fuzzy control rule；
In described method, the acquisition fuzzy controller Kp、Ki、KdWith error e and error rate ecBetween
Fuzzy relation is specially：Determine that de-fuzzy handles mathematic(al) representation：
Z is variable, uc(z) membership function for being variable z, z0For integrationWith integrationRatio
Value；It can thus be concluded that go out precise volume { e, the e of fuzzy controlc, substitute into following formula and calculate：
Kp=Kp0+K1{e,ec}p
Ki=Kio+K2{e,ec}i
Kd=Kdo+K3{e,ec}d
Wherein Kp0, Ki0, Kd0For Kp, Ki, KdThe initial value of three parameters, Δ Kp=K1{e,ec}p, Δ Ki=K2{e,ec}i,
ΔKd=K3{e,ec}d。
Fuzzy-adaptation PID control is to find out tri- parameter K of PIDp、Ki、KdWith error e and error rate ecBetween fuzzy pass
System, in operation by constantly detecting e and ec, online modification is carried out to three parameters according to fuzzy control rule, to meet
Different e and ecWhen to control parameter difference require so that controlled device has good dynamic and static state performance.KeWithRespectively
E and ecThe ratio of universe of fuzzy sets amplitude and actual domain amplitude, K1, K2, K3Respectively Δ Kp, Δ Ki, Δ KdActual domain
The ratio of amplitude and universe of fuzzy sets amplitude.
When system deviation e is larger, to make system eliminate deviation as early as possible, no matter ecSymbol how should all take larger Kp
And Ki, to reach the purpose of rapid drop deviation.If now deviation and deviation variation rate symbol on the contrary, if should take less Kd
Or make KdIt is zero；If now they are identical, then take larger Kd, prevent deviation from continuing to become big.
If deviation e is moderate, to prevent that system overshoot is excessive, less K should be takenpAnd KiTake moderate value.If this
When deviation and deviation variation rate symbol on the contrary, larger K should be takend；It is if identical, then to take moderate Kd, prevent deviation from continuing inclined
Greatly.
When system deviation e is smaller or deviation is zero, to shorten the regulating time of system, moderate K can usep, it is less
Ki.If now deviation and deviation variation rate symbol are on the contrary, less K can be takend；If identical, moderate K is takend.Now Kd
Unsuitable excessive, otherwise system is sensitive to disturbance, vibration aggravation, and regulating time is elongated.
ΔKpFuzzy reasoning table it is as shown in the table：
ΔKiFuzzy reasoning table it is as shown in the table：
ΔKdFuzzy reasoning table it is as shown in the table：
The output obtained by fuzzy reasoning is a fuzzy set, in actual use with the value ability of a determination
Go to control executing agency, this just needs de-fuzzy to handle.And fuzzy reasoning link is using Mamdani methods as fuzzy reasoning
Method.
A kind of brshless DC motor fuzzy-adaptation PID control governing system, as shown in Fig. 2 including：Rotating speed fuzzy controller
Module 201, electric current PID controller module 202, pwm control modules 203, three-phase inversion bridge module 204 and brshless DC motor sheet
Module 205；The brshless DC motor body module includes counter electromotive force module, torque calculation module and rotor-position and surveyed
Measure module.
Give a rated speed n0, this signal inputs to rotating speed fuzzy controller module, and signal out inputs to
Electric current PID controller module, pwm Pulse width modulation modules, pwm Pulse width modulation modules are inputed to again through this module by signal
The signal of output and given d. c. voltage signal ucThree phase inverter bridge is defeated by together, and output current signal i feeds back to electricity
Stream PID controller module forms interior closed loop, and three phase inverter bridge output current signal gives brshless DC motor body module, motor sheet
Module output speed signal n feeds back to rotating speed fuzzy controller module and forms outer closed loop.
Fig. 3 show a kind of brshless DC motor fuzzy-adaptation PID control speed control system structure figure.The rated speed n of input0Letter
Number with rotating speed rpm signals, by gain that value is 0.007, then the signal value that subtracts each other to obtain is 0.007 × (n respectively0- rpm),
The signal value obtained by 0.2 gain is 0.0014 × (n0- rpm), take this partial value in scope [- 3,3], obtained letter
Number input to fuzzy controller.Signal value 0.007 × (n0- rpm) subtract its value Jing Guo transmission delay module, transmission delay mould
The time delay parameter of block is set to 0.001, initial buffer area and is sized to 1024, and obtained signal value is set to a, also passes through
0.2 gain, this partial value in scope [- 3,3] is then taken, inputs to fuzzy controller.Fuzzy controller exports three letters
Number being multiplied by 0.01,120,0.01 successively obtains Δ Kp、ΔKi、ΔKd, Kp, Ki, KdInitial value Kp0, Ki0, Kd0Take 15 successively,
0.5th, 0.2, they are added Kp0+ΔKp=Kp、Ki0+ΔKi=Ki、Kd0+ΔKd=Kd, obtain Kp, Ki, KdValue.KpRespectively with
0.007×(n0- rpm) it is multiplied, KdWith being worth the signal multiplication for a, KiWith 0.007 × (n0- rpm) product integration of taking away obtainThis three groups of signals are added to obtain electric current irefSignal output.
To be best understood from the present invention program, illustration in detail below.Speed Regulation Systems of BLDCM is entered
Row fuzzy control, it is divided into following several steps：
Step 1：The editor of fuzzy set and computing." fuzzy " is inputted in Matlab command windows, system just ejects one
Individual fuzzy logic device, this meaning are exactly to have run fuzzy reasoning tool box.For the addition input under EDIT and export, I
First under FILE menu selection use Mamdani types, deviation e and deviation variation rate ecAs input, and controlled quentity controlled variable Δ Kp
With Δ KiAnd Δ KdAs output.
Step 2：The foundation of membership function.The icon for double-clicking input or output enters membership function interface, can be with
Enter edlin to inputting and exporting membership function.Domain scope can be changed, change membership function bar number, can also change and be subordinate to letter
Number form shape, the explanation so changed can be referred to and made below these one by one.According to being actually needed, the design makes input variable e
And ecDomain be all [- 3,3], word set is { NB NM NS ZO PS PM PB }, Δ KpDomain be [- 0.3,0.3], Δ Ki
Domain be [- 0.06,0.06], Δ KdDomain be [- 3,3], their word set is also all { NB NM NS ZO PS PM
PB}.Fuzzy subset NB, NM, NS, ZO, PS, PM, PB are expressed as bearing greatly, negative small in bearing, and zero, just small, center is honest.With
It is the Linguistic Value of linguistic variable to be obtained more thin more the reason for fuzzy subset above, the performance of fuzzy controller is better, but
Shortcoming is that regular quantity is greatly increased so as to cause amount of calculation also to increase, and is weighed according to each side and considered, so the design is final
The fuzzy subset of use is with regard to as implied above.Fuzzy Toolbox's is Mamdani types reasoning side in this secondary design Matlab
Method, so variable membership degree function selection triangular form and Z-type and S types, Fig. 4, Fig. 5, Fig. 6, Fig. 7 and Fig. 8 show control ginseng
Number e, ec、ΔKp, Δ KiWith Δ KdTriangleshape grade of membership function figure.
Step 3：Carry out fuzzy rule editor.The rule options under edit options in the view of logical edit device are opened, just
Rule can be controlled with editorial logic, then carry out fuzzy reasoning.Logic control rule is just according to fuzzy reasoning table mentioned above
To edit.Using method of expertise, with " if A and B then C " form expresses fuzzy control rule.Fig. 9 show mould
Paste rule editing figure.
Example：If(e is NB)and(ec is NB)then(dkp is PB)(dki is NB)；
If(e is NB)and(ec is NM)then(dkp is PB)(dki is NB)；
·······；
·······；
Step 4：Fuzzy decision application.And (with) method is min, Or (or) method is max, Implication
(reasoning) method is min, and Aggregation (synthesis) method is max, Defuzzification (defuzzification)
Method is Centroid (gravity model appoach).
Step 5：Generate fuzzy controller.System can generate the file that a suffix is .FIS, then utilize editing machine
File/Save to Workpace, current fuzzy inference system is saved with Fuzzy.So in simulink transfers
Fast fuzzy controller model can is run.
It is exactly a kind of brshless DC motor fuzzy-adaptation PID control governing system reality to being built up using simulink shown in Figure 10
Apply a structure chart；Concrete signal flow is direct voltage source ucDC current signal is provided, three are converted into by three phase inverter bridge
Cross streams current signal ia、ib、icBrshless DC motor is inputed to, brshless DC motor output voltage signal theta is wide to pulse
Modulation module is spent, and feeds back tach signal rpm to rotating speed module, forms the outer shroud closed loop of signal.Add in rotating speed PID modules
Enter fuzzy controller to be controlled rotating speed, rotating speed module output current signal irefGive electric current PID controller module, current-mode
The carrier signal pwm of block output is given to the Pulse width modulation module electricity that Pulse width modulation module is defeated by with brshless DC motor
Press signal theta together by this module composition pwm inverter circuits, reach the effect of pulse width modulation.Pulse width modulation
Module output current signal igElectric current PID controller is fed back to, forms inner ring closed loop.
Figure 11 show brshless DC motor body module structure chart.Three-phase current signal ia、ib、icPass through 0.5 Ω respectively
The inductance of resistance and 0.015H, passing through current measurement module 1,2,3 with current signal iabcIt is defeated by torque calculation module, torque
Another input signal of computing module is given step signal TL, the initial value of this signal is 35, stop value 67, signal rank
The time of jump is 0.5s, output torque signal Te, signal W.Signal W inputs to rotor position measurement module, with voltage signal
Theta is exported, and signal W is multiplied by a gain, is exported using value for 60/ (2 × W) as tach signal rpm.Voltage signal
Theta and signal W is defeated by counter electromotive force module, with voltage signal eabcOutput.Voltage signal eabcBy equivalent voltage source ea、eb、
ecFeed back to current measurement module 1,2,3.
Figure 12 show counter electromotive force function structure chart.Voltage signal theta passes through ea_table、eb_table、ec_
Table modules, three vectorial input values are all [0 60 120 180 240 300 360], and three table datas are respectively [1
1 1-1-1-1 1], [- 1-1 11 1-1-1], [1-1-1-1 11 1], the signal of output are multiplied by signal W again
0.132 is multiplied by as signal voltage eabc。
Figure 13 show torque calculation illustraton of model.Ac current signal iabcThe absolute value of three-phase alternating current is taken respectively | ia|、
|ib|、|ic|, then 0.5 × (| ia|+|ib|+|ic|) × 1.26, this value exports as dtc signal Te, another input
This value of step signal TL, (Te-TL) ÷ 0.06 is after integration module, then takes absolute value, and is exported as signal W.
Figure 14 show rotor position measurement function structure chart.Integration module obtains input signal W with gain module successively
Signal valueWith another input signal after the function module mod that rems, obtained value be multiplied by 2 again divided by
360, finally exported with signal theta.
Figure 15 show electric current pid control module.Current input signal i and electric current iref, they are subjected to computing and is worth
0.5×(iref- i), Kp, Ki, Kd7,16,0.02 is taken respectively, by 0.5 × (iref- i) respectively with Kp, Ki, KdMultiplication respectively obtains
3.5×(iref-i)、8×(iref-i)、0.01×(iref-i).To second value integration, the 3rd value derivation, then seek three values
It is b that sum limits its value in scope [- 1,1], the value for counting output by Saturation modules.Repeating sequence moulds
Block generates pwm waveforms, and the abscissa time is set to [0 1/4,000 2/4,000 3/4,000 4/4000]；Ordinate output valve is set to
[0 1 0-1 0], the value of its function waveform output are designated as c.B and c passes through relational calculus module, and if b >=c outputs 1 are otherwise defeated
Go out 0, finally by data type conversion module outgoing carrier signal pwm.
Figure 16 show pulse width modulation pwm function structure charts.The voltage signal theta of input respectively with 0,60,
120th, 180,240,300,360 compare, and are successively：If theta >=0, output 1, otherwise exports 0；If theta ＜ 60, output
1, otherwise export 0；If theta >=60, output 1, otherwise export 0；If theta ＜ 120, output 1, otherwise export 0；if
Theta >=120, output 1, otherwise export 0；If theta ＜ 180, output 1, otherwise export 0；If theta >=180, output 1,
Otherwise 0 is exported；If theta ＜ 240, output 1, otherwise export 0；If theta >=240, output 1, otherwise export 0；if
Theta ＜ 300, output 1, otherwise export 0；If theta >=300, output 1, otherwise export 0；If theta ＜ 360, output 1,
Otherwise 0 is exported；Output 1 or 0 signal from top to bottom two-by-two one group by logical operation module with door come compared with：Only two defeated
It is all 1 to enter value, and output is only 1, and it is all 0 otherwise to export.1 or 0 signal of output, adjacent two signals (it is most upper with most under
Signal is also adjacent) it will be compared by logical operation module OR gate：Only two input values are all 0, and output is only 0, no
Then export all is 1.6 signals of output are changed by data type conversion module, the signal after conversion, start number first from above
It is individual, the 3rd, the 5th signal bring and be multiplied with the carrier wave pwm signals inputted, 3 signals of output and second, the
Four, the last output current i of the 6th one piece of signalgSignal.
Figure 17 is the response of the electric current, voltage, angular speed rad, rotating speed n under governing system no-load condition of the embodiment of the present invention
Curve map.As seen from the figure when load torque sets 35 at the beginning, start to give rotating speed PID mono- signal, phase current
The very short time can be vibrated and then tended to be steady, quickly, then slowly counter electromotive force voltage in phase current duration of oscillation raises
Decline tends to be steady.When load torque is changed into 64 when but the time is changed into 0.5s, electric current tends to be steady after slowly increasing, due to
Power is constant so voltage also tends to steadily after slowly declining.
Angular speed and speed diagram are very alike, enter at the beginning to signal from rotating speed PID inputs, it can be seen that angular speed and
Rotating speed steeply rises, and after peak is risen to, is just slowly tended to be steady under vibration quickly is several, from this point it can be seen that adding fuzzy
Interference free performance is very strong faster to recover steady than traditional PID control, interference free performance is better than traditional PID control afterwards.
When the time is 0.5s, load torque becomes big, and angular speed and rotating speed are all declining, and tends to be steady again quickly.So be not difficult to find out,
Speed-regulating function is reached.
The brshless DC motor fuzzy-adaptation PID control governing system and method that the present invention establishes, including rotating speed fuzzy-adaptation PID control
Device module, electric current PID controller module, three-phase inversion bridge module, brshless DC motor body module and pwm control modules.
Brshless DC motor body module contains 3 counter electromotive force, torque calculation, rotor position measurement modules again.And then write out whole
The transmission function of individual control system, optimal controller parameter.Fuzzy logic is used for brshless DC motor by last fuzzy reasoning
Adjustment control.
In general, traditional PI D speed adjusting technique phases are used with existing by the contemplated above technical scheme of the present invention
Than having the advantages that：In Speed Regulation Systems of BLDCM, the effect of der Geschwindigkeitkreis is that strengthening system changes to load
Antijamming capability, the fluctuation of speed of drawing up, be system major control link.Because traditional PID control parameter can not be according to quilt
Corresponding adjustment is made in control object parametric change, and robustness is often unsatisfactory.The present invention is using Double-closed loop direct-current
Governing system, therefore the rotational speed regulation in PID control system is used fuzzy-adaptation PID control by the design, has been accurately reflected dynamic and has been rung
Process is answered, the uncertain and non-linear of control system can be effectively handled, improve the antijamming capability of system, dynamic following
Can good, dynamic strong anti-interference performance, anti-disturbance performance it is good good with anti-grid disturbances effect.Control accuracy is high, anti-dry
Disturb that ability is good, system it is dynamic and static functional, it has dynamic property good, and the rate of climb is fast, and overshoot is small, robustness it is good this
A little advantages.
Although depicting the present invention by embodiment, it will be appreciated by the skilled addressee that the present invention have it is many deformation and
Change the spirit without departing from the present invention, it is desirable to which appended claim includes these deformations and changed without departing from the present invention's
Spirit.
Claims (4)
- A kind of 1. brshless DC motor fuzzy-adaptation PID control speed regulating method, it is characterised in that including：According to fuzzy control theory, the fuzzy controller module of Speed Regulation Systems of BLDCM is established；Establish Speed Regulation Systems of BLDCM module；The governing system module includes rotating speed fuzzy controller module, electricity Flow PID controller module, three-phase inversion bridge module, brshless DC motor body module and pwm control modules；Establish the object function of the fuzzy controller parameter optimization of Speed Regulation Systems of BLDCM；Obtain fuzzy controller Kp、Ki、KdWith error e and error rate ecBetween fuzzy relation, according to detection error e With error rate ecValue, and fuzzy control rule, to Kp、Ki、KdThree parameters are modified.
- 2. the method as described in claim 1, it is characterised in that the fuzzy for establishing Speed Regulation Systems of BLDCM Controller module is specially：The editor of fuzzy set and computing, use error e and error rate ecAs input, controlled quentity controlled variable ΔKpWith Δ KiAnd Δ KdAs output；Membership function is established, the membership function is triangular function；Fuzzy rule Editor, according to the fuzzy reasoning table provided, using method of expertise, carry out fuzzy rule editor；Generate fuzzy controller.
- 3. the method as described in claim 1, it is characterised in that the acquisition fuzzy controller Kp、Ki、KdWith error e and Error rate ecBetween fuzzy relation be specially：Determine that de-fuzzy handles mathematic(al) representation：<mrow> <msub> <mi>z</mi> <mn>0</mn> </msub> <mo>=</mo> <mi>d</mi> <mi>f</mi> <mrow> <mo>(</mo> <mi>z</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <msubsup> <mo>&Integral;</mo> <mi>a</mi> <mi>b</mi> </msubsup> <msub> <mi>zu</mi> <mi>c</mi> </msub> <mrow> <mo>(</mo> <mi>z</mi> <mo>)</mo> </mrow> <mi>d</mi> <mi>z</mi> </mrow> <mrow> <msubsup> <mo>&Integral;</mo> <mi>a</mi> <mi>b</mi> </msubsup> <msub> <mi>u</mi> <mi>c</mi> </msub> <mrow> <mo>(</mo> <mi>z</mi> <mo>)</mo> </mrow> <mi>d</mi> <mi>z</mi> </mrow> </mfrac> <mo>;</mo> </mrow>Z is variable, uc(z) membership function for being variable z, z0For integrationWith integrationRatio；By This can draw precise volume { e, the e of fuzzy controlc, substitute into following formula and calculate：Kp=Kp0+K1{e,ec}pKi=Kio+K2{e,ec}iKd=Kdo+K3{e,ec}dWherein Kp0, Ki0, Kd0For Kp, Ki, KdThe initial value of three parameters, Δ Kp=K1{e,ec}p, Δ Ki=K2{e,ec}i, Δ Kd =K3{e,ec}d。
- A kind of 4. brshless DC motor fuzzy-adaptation PID control governing system, it is characterised in that including：Rotating speed fuzzy controller mould Block, electric current PID controller module, three-phase inversion bridge module, brshless DC motor body module and pwm control modules；The brshless DC motor body module includes counter electromotive force module, torque calculation module and rotor position measurement mould Block.
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| CN110488600A (en) * | 2019-09-01 | 2019-11-22 | 长春工业大学 | LQR Optimization-type brshless DC motor adjusts the speed Neural network PID controller |
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