CN111371356A - PMSM rotor observation method based on variable parameter PI control - Google Patents

PMSM rotor observation method based on variable parameter PI control Download PDF

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CN111371356A
CN111371356A CN202010259439.1A CN202010259439A CN111371356A CN 111371356 A CN111371356 A CN 111371356A CN 202010259439 A CN202010259439 A CN 202010259439A CN 111371356 A CN111371356 A CN 111371356A
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controller
pmsm
proportional
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CN111371356B (en
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吴少风
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Shanghai Wanli Electronic Technology Co ltd
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Shanghai Zhizhe Intelligent Control Technology Co ltd
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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
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/0003—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
    • 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
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/0003—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
    • H02P21/0014—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control using neural networks
    • 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
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/13—Observer control, e.g. using Luenberger observers or Kalman filters
    • 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
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
    • H02P21/18—Estimation of position or speed
    • 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
    • H02P6/14—Electronic commutators
    • H02P6/16—Circuit arrangements for detecting position
    • H02P6/18—Circuit arrangements for detecting position without separate position detecting elements
    • H02P6/182—Circuit arrangements for detecting position without separate position detecting elements using back-emf in windings
    • 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
    • H02P2203/00—Indexing scheme relating to controlling arrangements characterised by the means for detecting the position of the rotor
    • H02P2203/03—Determination of the rotor position, e.g. initial rotor position, during standstill or low speed operation

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Feedback Control In General (AREA)
  • Control Of Electric Motors In General (AREA)

Abstract

The invention relates to a PMSM rotor observation method based on variable parameter PI control, which obtains the extended back electromotive force of PMSM through an observer, and obtains the rotor position and the rotating speed through the calculation of a phase-locked loop according to the extended back electromotive force, and the proportional parameters of the observer and a PI controller in the phase-locked loop are adjusted in real time according to one or more parameters of the PMSM rotor position, the PMSM rotor rotating speed and the controller input deviation. Compared with the prior art, the invention has the advantages of wide application range and the like.

Description

PMSM rotor observation method based on variable parameter PI control
Technical Field
The invention relates to the technical field of motor control, in particular to a PMSM rotor observation method based on variable parameter PI control.
Background
For the directional control FOC of the PMSM magnetic field, the rotating position of a rotor is required to be detected in real time. Usually, a rotary encoder is used to detect the position of the rotor, but the external encoder increases the cost, reduces the reliability, and has limited application occasions, so that a position sensor-free method is required in some applications. At present, the common position-sensorless method based on a motor mathematical model in the high-speed stage of the motor comprises the following steps: SMO (sliding mode observer), EKF (extended Kalman Filter), MRAS (reference model adaptive method), and the like. These methods have various advantages and disadvantages: the SMO method is simple in calculation and good in robustness, but buffeting exists, and various methods adopted by the academic world can only reduce influence but cannot eliminate the buffeting; the EKF method has excellent anti-interference performance, but has large calculation amount, high requirement on the calculation capability of a microcontroller and difficult realization; the MRAS has a simple structure, but the position is obtained by velocity integration, so that the problem of error accumulation exists; meanwhile, because the motor and the model are actually nonlinear, the fixed observer control law parameters can keep better control performance only when the rotating speed of the rotor is within a certain range, the control performance comprises steady-state error, dynamic performance and robustness, and the applicable rotating speed range is narrow.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provide a PMSM rotor observation method based on variable parameter PI control, and the PMSM rotor observation method is wide in application range.
The purpose of the invention can be realized by the following technical scheme:
a PMSM rotor observation method based on variable parameter PI control obtains the extended back electromotive force of PMSM through an observer, and obtains the position and the rotating speed of a rotor through a phase-locked loop according to the extended back electromotive force calculation, the proportional parameters of the observer and a PI controller in the phase-locked loop are adjusted in real time according to one or more parameters of the rotating speed of the PMSM rotor and the input deviation of the controller, or a variable parameter proportional link is connected in series at the input end or the output end of the PI controller under the condition of not changing the proportional parameter of the PI controller, and the control effect same as that of adjusting the proportional parameter of the PI controller is achieved.
The proportional parameter of the PI controller is adjusted by connecting a variable parameter proportional link in series at the input end or the output end of the PI controller.
The observer comprises a PMSM model and a PI controller, and is used for measuring two-phase voltage [ u ] under a two-phase static coordinate systemauβ]TInputting actual PMSM and PMSM model, and correspondingly obtaining [ iaiβ]TAnd
Figure BDA0002438737570000021
PI controller in observer with [ i ]aiβ]TAnd
Figure BDA0002438737570000022
as input, outputs an extended back-emf
Figure BDA0002438737570000023
The expanded back electromotive force is fed back to the PMSM model to generate a control action so that the output deviation of the actual PMSM and the actual PMSM model is zero;
the phase-locked loop comprises a comparison link, a PI controller, a low-pass filter, an integration link and a feedback link which are sequentially connected to form a loop, wherein the comparison link takes an expanded counter potential as input and outputs a phase difference, the phase difference is input into the PI controller in the phase-locked loop and outputs a PMSM rotor rotation speed omegarSaid low pass filter pair ωrFiltering to suppress omegarThe integrating element is filtered omegarAnd the PMSM rotor position theta is input and output, and the sine and cosine of the theta are fed back to the comparison link by the feedback link.
Further, the state equation of the PMSM model adopted in the observer is:
Figure BDA0002438737570000024
Figure BDA0002438737570000025
wherein iaAnd iβIs two-phase current in a two-phase static coordinate system, R is phase resistance, LsIs a phase inductance,. psirFor rotor flux linkage, omegarThe rotating speed of the PMSM rotor is shown, and theta is the position of the PMSM rotor;
in the observer, ignore ψrSaid extended back-emf and ωrProportional relation, therefore, the PI controller in the observer is only within a certain range of omegarTo achieve better performance, Kp1Should sum ωrProportional change, in the phase-locked loop, the closed loop pole will expand with the counter potential or omegarChange in size, Kp2And ωrIn inverse proportion; adjusting K in real time according to set rulesp1And Kp2The same excellent performance can be achieved over a wider speed range, where ωrThe output can be obtained by a phase-locked loop, the square sum root of the expanded counter electromotive force can be obtained, and the rotation position can be differentiated.
Further, the calculation formula for adjusting the proportional parameter according to the PMSM rotor speed is as follows:
Figure BDA0002438737570000031
wherein, Kp1Proportional parameters, x, for PI controllers in the observer1、x2A and b are constants, ωrpuIs the per unit value, K, of the PMSM rotor speedp11Is omegarpuWhen 1 is Kp1A value;
Figure BDA0002438737570000032
wherein, Kp2Proportional parameter, x, of PI controller in phase-locked loop3And x4Is a constant number, Kp21Is omegarpuWhen 1 is Kp2A value;
because of the omega of the actual PMSMrIs of maximum extent, and Kp1And Kp2Too small a parameter will lose control and too large will cause oscillation, so for Kp1And Kp2The upper and lower boundary limits are made because the phase-locked loop input introduces omega simultaneouslyrThe information of the size and the direction of the motor can cause the reversal position to be reversed, namely the position of a motor rotor is theta, the calculation result is-theta, the motor is not rotated, and therefore Kp2The change law contains both velocity and direction information to correct the phase reversal.
Further, the calculation formula for adjusting the proportional parameter according to the input deviation of the controller is as follows:
Figure BDA0002438737570000033
wherein, Kp1Proportional parameters of PI controllers in the observer, epuFor the controller input per unit value of the deviation, x5、x6、x7M and n are constants, Kp11Is epuK when (m + n)/2p1A value;
Figure BDA0002438737570000034
wherein, Kp2For proportional parameters of PI controllers in phase-locked loops, Kp21Is epuK when (m + n)/2p2The value is obtained.
Further, the proportional parameter is controlled and adjusted through a neural network according to the input deviation of the controller and the rotation speed of the PMSM rotor, the neural network is a single-layer neural network formed by 2 neurons, and e is calculatedpuAnd ωrpuAs input, output Kp1And Kp2K is obtained by calculation according to the formula (3) and the formula (5) and superposition according to a certain weightp1K is obtained by calculation according to formula (4) and formula (5) and superposition according to certain weightp2。
Further, the proportional parameter is adjusted by a fuzzy control method according to the input deviation of the controller and the rotation speed of the PMSM rotor, and the fuzzy control method specifically comprises the following steps:
inputting the per unit value e of the deviation into the controllerpuAnd per unit value omega of PMSM rotor speedrpuFuzzification, respectively constructing proportional parameter K of PI controller in observerp1Proportional parameter K of PI controller in phase-locked loopp2With respect to epuAnd ωrpuObtaining K from the fuzzy rule tablep1And Kp2Establishing a de-fuzzy rule table, and obtaining K according to the fuzzy grade and the de-fuzzy rule tablep1And Kp2。
Further, K is adjusted by a fuzzy control method according to the input deviation and the PMSM rotor speedp1And Kp2The method specifically comprises the following steps:
e is to bepuAnd ωrpuFuzzification of each of the constructs Kp1And Kp2With respect to epuAnd ωrpuObtaining K from the fuzzy rule tablep1And Kp2Establishing a de-fuzzy rule table, and obtaining K according to the fuzzy grade and the de-fuzzy rule tablep1And Kp2。
Compared with the prior art, the invention has the following beneficial effects:
(1) the invention sets a first PI controller in an observer, inputs the output deviation of the actual PMSM and the PMSM model into the first PI controller, outputs the expanded back electromotive force, inputs the expanded back electromotive force into a phase-locked loop to obtain the position and the rotating speed of a PMSM rotor, wherein a second PI controller is added into the phase-locked loop, and the proportionality coefficient K of the first PI controllerp1And the proportionality coefficient K of the second PI controllerp2The method has the advantages that real-time adjustment is carried out according to one or more parameters of the PMSM rotor speed and the input deviation, and the expanded back electromotive force is in direct proportion to the rotor speed, so that the application range of the rotor speed is expanded, and the same excellent steady-state error, dynamic performance and robustness can be achieved in a wider rotor speed range;
(2) the invention adjusts K in real time through the parameter adjusting modulep1And Kp2While at the same time limiting Kp1And Kp2Upper and lower boundaries of, avoiding Kp1And Kp2Too large leads to unstable rotating speed of a motor rotor, or too small leads to loss of control of a PI controller, the motor cannot rotate, and simultaneously, because the rotating speed and the direction information are introduced into the phase-locked loop input at the same time, the reverse position is reversed, and K is adjustedp2The rotating speed and direction information of the rotor are referred, the reverse position phase reversal can be corrected, and the normal operation of the motor is ensured;
(3) the invention adopts a single-layer neural network consisting of two neurons to optimize Kp1And Kp2The stability is good in the adjusting process of (2);
(4) the invention integrates the rotor speed and the deviation input into the PI controller, adopts a fuzzy control method and has good robustness.
Drawings
FIG. 1 is a schematic view of the structure of an observer;
FIG. 2 is a schematic diagram of a phase-locked loop;
FIG. 3 is a schematic diagram of a PI controller;
FIG. 4 is epuFuzzification schematic diagram;
FIG. 5 is ωrpuFuzzification schematic diagram;
FIG. 6 is a schematic diagram of a neural network architecture;
FIG. 7 is a schematic structural diagram of a series connection of variable parameter ratio links at the output end of a PI controller;
fig. 8 is a schematic structural diagram of a series connection of variable parameter ratio links at the input end of the PI controller.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
A PMSM rotor observation method based on variable parameter PI control obtains an extended back electromotive force of a PMSM through an observer, obtains a rotor position and a rotating speed through a phase-locked loop according to the extended back electromotive force, and the proportional parameters of a PI controller in the observer and the phase-locked loop are adjusted in real time according to one or more parameters of the rotating speed of the PMSM rotor and input deviation of the controller.
As shown in FIG. 1, the observer comprises a PMSM model and a PI controller, and converts two-phase voltage [ u ] in a two-phase static coordinate systemauβ]TInputting actual PMSM and PMSM model, and correspondingly obtaining [ iaiβ]TAnd
Figure BDA0002438737570000051
PI controller in observer with [ i ]aiβ]TAnd
Figure BDA0002438737570000052
as input, outputs an extended back-emf
Figure BDA0002438737570000053
And will expand the back-emfFeeding back to the PMSM model to generate a control action so that the output deviation of the actual PMSM and the PMSM model is zero;
referring to fig. 2, the pll comprises a comparison unit, a PI controller, a low pass filter, an integration unit, and a feedback unit connected in sequence to form a loop, wherein the comparison unit takes an expanded back emf as an input to output a phase difference, the phase difference is input to the PI controller in the pll to output a PMSM rotor rotation speed ωrLow pass filter pair omegarFiltering to suppress omegarHigh frequency noise above, integration element with filtered omegarAnd the PMSM rotor position theta is input and output, and the sine and cosine of the theta are fed back to the comparison link by the feedback link.
The observer and the controller in the phase locked loop both adopt the structure shown in fig. 3, kpTo adjustable proportionality coefficient, TiFor adjusting the integral constant, as shown in fig. 7 and 8, a variable parameter proportional link is connected in series at the input end or the output end of the PI controller without changing the proportional parameter of the PI controller, so as to achieve the same control effect as adjusting the proportional parameter of the PI controller.
The state equation of the PMSM model adopted in the observer is as follows:
Figure BDA0002438737570000061
Figure BDA0002438737570000062
wherein iaAnd iβIs two-phase current in a two-phase static coordinate system, R is phase resistance, LsIs a phase inductance,. psirFor rotor flux linkage, omegarThe rotating speed of the PMSM rotor is shown, and theta is the position of the PMSM rotor;
in the observer, ignore ψrExpanding the back emf and ωrProportional relation, therefore, the PI controller in the observer is only within a certain range of omegarTo achieve better performance, Kp1Should sum ωrProportional change, in the phase-locked loop, the closed loop pole will expand with the counter potential or omegarSize and breadthChange by change, Kp2And ωrIn inverse proportion; adjusting K in real time according to set rulesp1And Kp2The same excellent performance can be achieved over a wider speed range, where ωrThe output can be obtained by a phase-locked loop, the square sum root of the expanded counter electromotive force can be obtained, and the rotation position can be differentiated.
The calculation formula for adjusting the proportional parameter according to the PMSM rotor speed is as follows:
Figure BDA0002438737570000063
wherein, Kp1Proportional parameters, x, for PI controllers in the observer1、x2A and b are constants, ωrpuIs the per unit value, K, of the PMSM rotor speedp11Is omegarpuWhen 1 is Kp1A value;
Figure BDA0002438737570000064
wherein, Kp2Proportional parameter, x, of PI controller in phase-locked loop3And x4Is a constant number, Kp21Is omegarpuWhen 1 is Kp2A value;
because of the omega of the actual PMSMrIs of maximum extent, and Kp1And Kp2Too small a parameter will lose control and too large will cause oscillation, so for Kp1And Kp2The upper and lower boundary limits are made because the phase-locked loop input introduces omega simultaneouslyrThe information of the size and the direction of the motor can cause the reversal position to be reversed, namely the position of a motor rotor is theta, the calculation result is-theta, the motor is not rotated, and therefore Kp2The change law contains both velocity and direction information to correct the phase reversal.
The calculation formula for adjusting the proportional parameter according to the input deviation of the controller is as follows:
Figure BDA0002438737570000071
wherein, Kp1Proportional parameters of PI controllers in the observer, epuFor the controller input per unit value of the deviation, x5、x6、x7M and n are constants, Kp11Is epuK at 0.005p1A value;
Figure BDA0002438737570000072
wherein, Kp2For proportional parameters of PI controllers in phase-locked loops, Kp21Is epuK at 0.005p2The value is obtained.
The proportional parameter is controlled and adjusted through a neural network according to the input deviation of the controller and the PMSM rotor speed, as shown in figure 6, the neural network is a single-layer neural network formed by 2 neurons, and e ispuAnd ωrpuAs input, output Kp1And Kp2K is obtained by calculation according to the formula (3) and the formula (5) and superposition according to a certain weightp1K is obtained by calculation according to formula (4) and formula (5) and superposition according to certain weightp2。
And adjusting the proportional parameter according to the input deviation of the controller and the PMSM rotor speed by a fuzzy control method, wherein the fuzzy control method specifically comprises the following steps:
inputting the per unit value e of the deviation into the controllerpuAnd per unit value omega of PMSM rotor speedrpuFuzzification, respectively constructing proportional parameter K of PI controller in observerp1Proportional parameter K of PI controller in phase-locked loopp2With respect to epuAnd ωrpuObtaining K from the fuzzy rule tablep1And Kp2Establishing a de-fuzzy rule table, and obtaining K according to the fuzzy grade and the de-fuzzy rule tablep1And Kp2。
Adjusting K according to the input deviation and PMSM rotor speed by fuzzy control methodp1And Kp2The method specifically comprises the following steps:
as shown in FIG. 4, epuAnd Kp1Fuzzification, which is divided into 3 fuzzy sets with small, medium and large average values, and the intervals are 0-0.002, 0.001-0.01 and 0 correspondingly.More than 008; as in fig. 5, will ωrpuAnd Kp2Fuzzification, which is divided into 6 fuzzy sets of-large, -medium, -small, small and medium, wherein the intervals are correspondingly below-1, -1.2 to-0.1, -0.25 to 0.25, 0.1 to 1.2 and more than 1; respectively construct Kp1And Kp2With respect to epuAnd ωrpuFuzzy rule table of, Kp1The fuzzy rule of (1):
TABLE 1Kp1Fuzzy rule table
Figure BDA0002438737570000081
Kp2The fuzzy rule of (1) is as in table 2:
TABLE 2Kp2Fuzzy rule table
Figure BDA0002438737570000082
Obtaining Kp1And Kp2Establishing a de-fuzzy rule table, and obtaining K according to the fuzzy grade and the de-fuzzy rule tablep1And Kp2The deblur rule is shown in table 3:
TABLE 3 deblurring rules Table
Figure BDA0002438737570000083
Wherein, K is K with better effect at medium speedp1Value sum Kp2The value is obtained.
The embodiment provides a PMSM rotor observation method based on variable parameter PI control, which is applied to digital control on a micro-control chip of a PMSM controller.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.

Claims (9)

1. A PMSM rotor observation method based on variable parameter PI control is characterized in that an observer obtains an extended back electromotive force of a PMSM, a phase-locked loop calculates and obtains a rotor position and a rotating speed according to the extended back electromotive force, and proportional parameters of a PI controller in the observer and the phase-locked loop are adjusted in real time according to one or more parameters of the rotating speed of the PMSM rotor and input deviation of the controller.
2. The PMSM rotor observation method adopting the variable parameter PI controller as claimed in claim 1, wherein the state equation of the PMSM model adopted in the observer is as follows:
Figure FDA0002438737560000011
Figure FDA0002438737560000012
wherein iaAnd iβIs two-phase current in a two-phase static coordinate system, R is phase resistance, LsIs a phase inductance,. psirFor rotor flux linkage, omegarThe PMSM rotor speed is shown, and theta is the PMSM rotor position.
3. The PMSM rotor observation method adopting the variable parameter PI controller as claimed in claim 1, wherein the calculation formula for adjusting the proportional parameter according to the PMSM rotor rotation speed is as follows:
Figure FDA0002438737560000013
wherein, Kp1Proportional parameters, x, for PI controllers in the observer1、x2A and b are constants, ωrpuIs the per unit value, K, of the PMSM rotor speedp11Is omegarpuWhen 1 is Kp1A value;
Figure FDA0002438737560000014
wherein, Kp2Proportional parameter, x, of PI controller in phase-locked loop3And x4Is a constant number, Kp21Is omegarpuWhen 1 is Kp2The value is obtained.
4. The PMSM rotor observation method adopting the variable parameter PI controller as claimed in claim 1, wherein the calculation formula for adjusting the proportional parameter according to the controller input deviation is as follows:
Figure FDA0002438737560000021
wherein, Kp1Proportional parameters of PI controllers in the observer, epuFor the controller input per unit value of the deviation, x5、x6、x7M and n are constants, Kp11Is epuK when (m + n)/2p1A value;
Figure FDA0002438737560000022
wherein, Kp2For proportional parameters of PI controllers in phase-locked loops, Kp21Is epuK when (m + n)/2p2The value is obtained.
5. The PMSM rotor observation method using a variable parameter PI controller as claimed in claim 1, wherein the scaling parameter is adjusted by neural network control based on controller input deviation and PMSM rotor speed.
6. The PMSM rotor observation method using a variable parameter PI controller as in claim 1, wherein the scaling parameter is adjusted by a fuzzy control method based on controller input deviation and PMSM rotor speed.
7. The PMSM rotor observation method adopting the variable parameter PI controller as claimed in claim 6, wherein the fuzzy control method specifically comprises:
inputting the per unit value e of the deviation into the controllerpuAnd per unit value omega of PMSM rotor speedrpuFuzzification, respectively constructing proportional parameter K of PI controller in observerp1Proportional parameter K of PI controller in phase-locked loopp2With respect to epuAnd ωrpuObtaining K from the fuzzy rule tablep1And Kp2Establishing a de-fuzzy rule table, and obtaining K according to the fuzzy grade and the de-fuzzy rule tablep1And Kp2。
8. The PMSM rotor observation method adopting the variable parameter PI controller as claimed in claim 1, further comprising adjusting the proportional parameter of the PI controller by connecting a variable parameter proportional link in series at the input end of the PI controller.
9. The PMSM rotor observation method adopting the variable parameter PI controller as claimed in claim 1, further comprising adjusting the proportional parameter of the PI controller by connecting a variable parameter proportional link in series at the output terminal of the PI controller.
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