CN115296571A

CN115296571A - Permanent magnet synchronous motor control parameter optimization method

Info

Publication number: CN115296571A
Application number: CN202210738813.5A
Authority: CN
Inventors: 凌云; 黄云章; 刘颖慧; 聂辉; 周建华; 王兵; 汤彩珍
Original assignee: Hunan University of Technology
Current assignee: Shandong Zhongzhe Deyuan Intelligent Equipment Co ltd
Priority date: 2020-09-04
Filing date: 2020-09-04
Publication date: 2022-11-04
Anticipated expiration: 2040-09-04
Also published as: CN112054727B; CN112054727A; CN115296571B; CN114915217A

Abstract

The invention discloses a permanent magnet synchronous motor control parameter optimization method, wherein the speed of a permanent magnet synchronous motor is controlled by a PI speed controller, the output of a load torque observer is used for carrying out load torque compensation on the output of the PI speed controller, and the parameters of the PI speed controller and the load torque observer are optimized and set by uniformly adopting a wolf pack algorithm. The load torque observation adopts an algorithm that the feedback gain is automatically adjusted according to the variation of the load torque set value and the variation of the load torque observation value, so that when the load torque set value is changed or/and the load torque observation value is changed, the load torque observation error can be quickly reduced, the observation value is feedforward compensated to the current regulator, and the control precision of the permanent magnet synchronous motor is improved. Aiming at searching an accurate optimal solution and avoiding different optimal objects such as local optimal objects near the optimal solution, the wolf colony algorithm can carry out maximum adaptation by reasonably selecting the value of the attack step attenuation factor so as to achieve different optimization effects.

Description

Permanent magnet synchronous motor control parameter optimization method

The invention discloses a drive control system of an elevator permanent magnet synchronous motor, which is a divisional application with an original application number of 202010918629.X and an application date of 09 and 04 of 2020.

Technical Field

The invention relates to the technical field of permanent magnet synchronous motors, in particular to a control parameter optimization method of a permanent magnet synchronous motor.

Background

The permanent magnet synchronous motor has the advantages of high efficiency, large torque, good rotating speed performance and the like, and is widely applied to the fields of manufacturing, electric automobiles, industrial production and the like. The permanent magnet synchronous motor is used as the elevator traction motor, the low speed, the rapidity, the hard mechanical characteristics and the like of the permanent magnet synchronous motor are superior to those of an alternating current asynchronous motor, the service life, the energy consumption, the maintainability and the like of the permanent magnet synchronous motor are superior to those of a direct current motor, the ideal elevator driving with low rotating speed and large torque is easy to realize, and the requirements of strong elevator driving overload capacity and wide speed regulation range are met. The control method based on load torque compensation can reduce the influence of load disturbance, but when the load torque changes and given speed changes or control system internal parameter perturbation occurs, the load torque observation deviation is increased, and performance indexes such as steady state, dynamic state and speed regulation range of the speed control of the permanent magnet synchronous motor are influenced.

Disclosure of Invention

The invention aims to provide a permanent magnet synchronous motor drive control system and a permanent magnet synchronous motor control parameter optimization method, wherein the observed load torque is subjected to feedforward compensation to a current regulator, the load torque observation response speed is improved, and the torque observation volatility is reduced. The speed of the permanent magnet synchronous motor is controlled by a PI speed controller, a load torque observer observes load torque, the output of the load torque observer is used for performing load torque compensation on the output of the PI speed controller, and parameters of the PI speed controller and the load torque observer are optimized and set by uniformly adopting a wolf colony algorithm. In the wolf group algorithm, the wolf is to develop the attack on the prey according to the formula

Carrying out the following steps; wherein, i =1,2, \8230, M-1; j =1,2, \8230, N; m is the number of wolfs in the wolf group, and N is the search space dimension of the wolf group algorithm;

represents the current position of the ith wolf; z is a radical of formula _b ＝[p _b1 p _b2 … p _bN ]Indicating the current wolf location; delta is a preset threshold value, and the value range of delta is [ 0.1.0.4 ]]；z _jmax And z _jmin Respectively the maximum value and the minimum value of the j-dimension parameter value interval; stepc is the attack step size, according to formula

Calculating; wherein n is the current iteration number, and n is _max Is a set maximum number of iterations; stepc _max 、stepc _min Respectively setting a maximum attack step length and a minimum attack step length; xi is a tapping step attenuation factor, and xi is more than or equal to 1.5 and less than or equal to 10.

Load output by PI speed controllerGiven value of torque

And torque current given component i' _q Is composed of

Wherein p is the number of pole pairs of the motor, psi _f Is a permanent magnet flux linkage; k is _p Proportional coefficient, T, of PI speed controller _i Is the integral time constant of the PI speed controller; rotor angular velocity error e = ω of motor ^* -ω，ω ^* For a given rotor angular velocity, ω is the rotor angular velocity and e (t) is the rotor angular velocity error instantaneous value.

The load torque observer is

Wherein J is the moment of inertia,

is an estimated value of the angular velocity of the rotor, g is a feedback gain of the load torque observer and g is less than 0;

k _g is the sliding mode gain of the load torque observer and k _g ≤-|e ₂ /J|，

For load torque observation errors, T _L In order to be the load torque,

is a load torque observed value.

The method for compensating the output of the PI speed controller by the output of the load torque observer is to use the observed value of the load torque

Converted into torque current compensation component i ″ _q Feedforward compensation to the input of a q-axis current PI controller; q-axis torque current setpoint

Is composed of

The load torque observer is based on the given value of the load torque

And load torque observed value

The feedback gain g is adjusted by the change of (c), the method is as follows:

step S1, a load torque observer carries out T on load torque _L Observing to obtain the observed value of the load torque

The PI speed controller performs control operation to obtain a given value of load torque

Step S2, calculating

Calculating out

S3, judging whether delta T is larger than epsilon ₂ (ii) a When Δ T is greater than ε ₂ Taking feedback gain g equal to g _min And withdrawing; when Δ T is equal to or less than ε ₂ If yes, the step S4 is carried out;

s4, judging whether delta T is smaller than epsilon ₁ (ii) a When Δ T is less than ε ₁ Taking feedback gain g equal to g _max And withdrawing; when DeltaT is greater than or equal to epsilon ₁ If yes, the step S5 is carried out;

step S5, the feedback gain g is according to

Calculating; wherein epsilon ₁ Comparing thresholds, e, for lower limits of torque variation ₂ Comparing threshold values for upper limits of torque variation, and 0 & ltepsilon ₁ ＜ε ₂ ；g _max For high value of feedback gain, g _min Is a low value of feedback gain, and g _min ＜g _max ＜0。

In the optimization method for the control parameters of the permanent magnet synchronous motor, the established objective function Q comprehensively evaluates various performance indexes of the PI speed controller and the load torque observer ₃ Is composed of

Wherein, t _z The method comprises the steps that the transition process time of the angular speed step response of a motor rotor is represented, and t =0 is the starting time of the step response of the motor; q ₃₁ Gamma in (5) _z1 (1-sgn(e(t)+ω _δ ) Term) is a rotor angular velocity overshoot penalty function, γ _z1 Is a sufficiently large positive number, ω _δ The rotor angular speed overshoot limit; q ₃₂ Gamma in (5) _z1 (1-sgn(e(t)+ω _Δ ) Term) is a steady state error penalty function, ω _Δ Is the rotor angular velocity steady state error limit; gamma ray _z Adjusting the coefficient and gamma for fitness balance _z ＞0；γ _z2 Not less than 6. The parameter vector to be optimized is mu ₁ ＝[K _p ，T _i ，G _max ，G _min ，ε ₁ ，ε ₂ α |, the number of parameters to be optimized is 7, i.e. wolfThe search space dimension N of the group algorithm is equal to 7.g _max And G _max In a relationship of

g _min And G _min In a relationship of

k _g In relation to alpha is

Wherein alpha is more than or equal to 1; further, the value of α is selected within the range of 1 to 5.

In the optimization method of the control parameters of the permanent magnet synchronous motor, the angular speed omega of the rotor is given ^* Is a step signal. At the time of starting the motor, the load torque T _L For high value T of load torque _Lmax (ii) a At t > t _z After the motor enters the stable state of the rotor angular speed, the load torque T _L From a high value T _Lmax Reduction of the mutation to a low value T _Lmin (ii) a Load torque T _L Maintained at a low value T _Lmin Run time

Then, from a low value T _Lmin Mutation increases to a high value of T _Lmax ；

Is 2 to 5t _z A random value in between. t is t _z The transition process time of the angular speed step response of the motor rotor. Further, the load torque is high value T _Lmax Not greater than rated load torque T of motor _N Low value of load torque T _Lmin Not less than rated load torque T of motor _N 10% of (d), high value of load torque T _Lmax With low value T of load torque _Lmin The difference between the motor load torque and the motor load torque is not less than the rated load torque T of the motor _N 50% of the total weight of the steel.

The wolf pack algorithm is as follows:

step 301, initializing a wolf group; the initial position of each wolf in the wolf group is

Step 302, hunting for competition; calculating the adaptive value of each wolf in the wolf group, wherein the smaller the adaptive value is, the better the position of the wolf is; selecting 1 wolf with optimal position as wolf head, and selecting R with optimal position except for wolf head ₁ The wolf is a competitive wolf; r ₁ The competitive wolves develop hunting searching behaviors, compete and replace wolfs;

step 303, summoning a raid; the head wolf and other wolfs except the competitive wolf develop the running search behavior and run towards the head wolf; calculating an adaptive value of the new position of the ith wolf, changing the position of the ith wolf when the new position searched by the ith wolf is superior to the current position of the ith wolf, and keeping the position unchanged if the new position searched by the ith wolf is not superior to the current position of the ith wolf; if the new position searched by the ith wolf is better than the position of the wolf, the ith wolf is converted into the wolf and the Chinese wolf calls the rushing again;

step 304, surrounding and attacking preys; under the summoning of the wolf head, other wolfs attack the prey; calculating an adaptive value of a new position of the ith wolf, changing the position of the ith wolf when the new position searched in the attacking process of the ith wolf is superior to the current position, and keeping the position unchanged if the new position is not superior to the current position; if the new position searched by the ith wolf attack is superior to the wolf position, the ith wolf is converted into the wolf;

step 305, judging termination conditions; if the number of loop iterations is reached, terminating the optimization process, and taking the wolf head position parameter as an optimal parameter; otherwise let n = n +1, go to step 306;

step 306, competition updating; random generation of R ₂ Replacement of R in wolf group by wolf ₂ The wolf with the worst fitness value is returned to step 302.

The permanent magnet synchronous motor control parameter optimization method detects the rotor position theta and the three-phase current i of the permanent magnet synchronous motor _a 、i _b And i _c (ii) a According to three-phase current i _a 、i _b And i _c Clark conversion is carried out on the permanent magnet synchronous motor to obtain current i under an alpha-beta axis coordinate system _α Current i _β According to the current i _α Current i _β Carrying out Park conversion on the rotor position theta to obtain a current i under a d-q axis coordinate system _d Current i _q 。

The optimization method of the control parameters of the permanent magnet synchronous motor is realized by a permanent magnet synchronous motor drive control system comprising a PI speed controller, a load torque observer, a q-axis current controller, a d-axis current controller, a Clarke conversion module, a position and speed detection module, a Park conversion module, a Park inverse conversion module, an SVPWM module and a three-phase inverter.

The periodic control process of the permanent magnet synchronous motor drive control system specifically comprises the following steps:

step one, detecting the rotor position theta, the rotor angular speed omega and the three-phase current i of the permanent magnet synchronous motor _a 、i _b And i _c ；

Step two, according to three-phase current i _a 、i _b And i _c Clark conversion is carried out on the permanent magnet synchronous motor to obtain current i under an alpha-beta axis coordinate system _α Current i _β According to the current i _α Current i _β And carrying out Park conversion on the rotor position theta to obtain a current i under a d-q axis coordinate system _d Current i _q ；

Step three, feedback gain g is given value T according to load torque _L ^* And load torque observed value

Is adjusted;

step four, the load torque observer calculates the rotor angular speed omega and the current i _q Observing the load torque to obtain a load torque observed value

And a torque current compensation component i ″) _q ；

Step five, the PI speed controller gives a given angular speed omega according to the input rotor ^* And the angular speed omega of the rotor are controlled and calculated to obtain a given value of the load torque

And torque current given component i' _q ；

Step six, giving a component i 'according to the torque current' _q And a torque current compensation component i ″) _q Calculating to obtain a given value i of q-axis torque current _q ^* (ii) a d-axis current controller setting value i according to d-axis torque current _d ^* And the current i under the d-axis coordinate system _d The difference value between the two is subjected to PI control operation to obtain a control voltage U under a d-axis coordinate system _d (ii) a The q-axis current controller sets a value i according to the q-axis torque current _q ^* With current i in q-axis coordinate system _q The difference value between the two is subjected to PI control operation to obtain a control voltage U under a q-axis coordinate system _q (ii) a According to the control voltage U under a d-q axis coordinate system _d 、U _q Carrying out Park inverse transformation to obtain a control voltage U under an alpha-beta axis coordinate system _α 、U _β (ii) a d-axis torque current set value i _d ^* Equal to 0;

step seven, controlling the voltage U under the alpha-beta axis coordinate system _α 、U _β As input of the SVPWM module, the SVPWM module controls a three-phase inverter to generate a three-phase alternating current power supply U _a 、U _b 、U _c Thereby driving the permanent magnet synchronous motor to operate.

In the above steps, the sequence of the third step and the fourth and fifth steps can be interchanged, that is, the fourth and fifth steps can be performed first, and then the third step can be performed.

The invention has the advantages that the observed value of the load torque is feedforward compensated to the given value of the current regulator, under the condition that the given current part output by the PI speed controller does not need to be greatly adjusted, the relative influence caused by the disturbance of the load or the change of the system parameters can be counteracted, and the buffeting of the system is effectively weakened. The load torque observation adopts an algorithm that the feedback gain is automatically adjusted according to the variation of the set value of the load torque and the variation of the observed value of the load torque, thereby avoiding the problems that the torque observation fluctuation is large because a load torque observer selects a small fixed feedback gain and the convergence time is long because a large fixed feedback gain is selected, rapidly reducing the observation error of the load torque when the set value of the load torque is changed or/and the observed value of the load torque is changed because the control parameters, the model parameters and the like of a system are changed or the load is disturbed, and improving the rapidity and the accuracy of the observation effect and the motor speed control. The feedback gain g is automatically adjusted when the load torque set value changes, the load torque set value can be changed due to the change of the rotor angular speed set value or/and the change of the rotor angular speed actual value, or the load torque set value can be changed due to the change of the system model parameters, the load torque observed value is greatly fluctuated, the feedback gain g is adjusted in advance, when the load torque observed value really generates an observation error, the response speed of an observer is accelerated, the observation error of the load torque observed value is quickly reduced, and the rapidity and the accuracy of the motor speed control are further improved. Parameters of the PI speed controller and the load torque observer are optimized and set by a wolf colony algorithm, the size of an attenuation factor xi of the attack step is adjusted, and the relative attenuation speeds of the early stage and the later stage of the attack step can be adjusted; aiming at different optimized objects such as searching an accurate optimal solution and avoiding local optimal objects near the optimal solution, the maximum adaptation can be carried out by reasonably selecting the value of the attack step attenuation factor xi so as to achieve different optimization effects.

Drawings

FIG. 1 is a block diagram of an embodiment of an elevator PMSM drive control system;

FIG. 2 is a flowchart of an embodiment of a method for automatically adjusting feedback gain;

FIG. 3 is a diagram showing the effect of adjusting the tapping step attenuation factor xi on the relative attenuation speed;

fig. 4 shows a given rotor angular velocity signal and load torque signal.

Detailed Description

The present invention will be described in further detail below with reference to the accompanying drawings and examples.

FIG. 1 is an elevator permanent magnetBlock diagram of an embodiment of a synchronous motor drive control system. In fig. 1, a Clarke conversion module inputs a three-phase current i of a permanent magnet synchronous motor (i.e., PMSM) _a 、i _b And i _c And outputs the current i under the two-phase static alpha-beta axis coordinate system _α 、i _β (ii) a A position sensor in the position and speed detection module detects the position theta of the rotor of the permanent magnet synchronous motor and converts the position theta into the angular speed omega of the rotor for output; park conversion module input current i _α 、i _β And rotor position theta, and outputs current i under a rotating d-q axis coordinate system _d 、i _q (ii) a PI speed controller inputs rotor to give angular speed omega ^* And rotor angular velocity omega, output load torque set value T _L ^* And torque current given component i' _q (ii) a Input load torque set value T of load torque observer _L ^* Rotor angular velocity ω and current i _q The output torque current compensation component i ″) _q (ii) a Torque current given component i' _q And a torque current compensation component i ″) _q After addition, the sum is used as a given value i of q-axis torque current ^* _q (ii) a q-axis current PI controller inputs q-axis torque current given value i ^* _q And current i _d And outputting a control voltage U under a q-axis coordinate system _q (ii) a A q-axis torque current given value i is input into a d-axis current PI controller ^* _d And current i _d And outputting control voltage U under d-axis coordinate system _d D-axis torque current setpoint i ^* _d Equal to 0; the Park inverse transformation module inputs a control voltage U under a d-q axis coordinate system _d 、U _q And outputs the control voltage U under the alpha-beta axis coordinate system _α 、U _β (ii) a The SVPWM module (space vector pulse width modulation module) inputs a control voltage U _α 、U _β Outputting pulse signals to a three-phase inverter, which converts the DC voltage U _dc Converting into three-phase AC power supply U _a 、U _b 、U _c Thereby driving the permanent magnet synchronous motor to operate.

Neglecting the influence of core eddy current and hysteresis loss, etc., adopting i _d The directional control of the PMSM rotor magnetic field of =0 establishes a mathematical model of the PMSM under a d-q axis rotating coordinate systemType, the voltage equation is:

for adopting i _d The salient pole type PMSM vector control system with the control mode of =0 has the electromagnetic torque equation as follows:

T _e ＝1.5pψ _f i _q (2)

the PMSM equation of motion is:

in the formulae (1), (2) and (3), u _d 、u _q Voltages of d-q axes, respectively; i.e. i _d 、i _q Currents of d-q axes, respectively; l is a radical of an alcohol _d 、L _q Inductances of d-q axes, respectively; t is a unit of _e Is the electromagnetic torque; t is _L Is the load torque; r is the resistance of the stator; p is the number of pole pairs of the motor; omega _e Is the rotor electrical angular velocity, i.e. angular frequency; ω is the rotor angular velocity, i.e. the mechanical angular velocity of the rotor of the electrical machine; psi _f Is a permanent magnet flux linkage; j is the moment of inertia; b is the coefficient of friction; t is time.

As can be seen from the mathematical models of the permanent magnet synchronous motors of the formulas (1), (2) and (3) under d-q coordinates, i is adopted _d And (5) controlling the torque output of the motor by using a control strategy of =0 according to the formula (2), and controlling the operation of the motor by combining a speed and current double closed loop. Let the rotor angular speed error e = ω of the motor ^* - ω, ω is a given rotor angular speed of the electrical machine. The PI speed controller regulates and controls the rotor angular speed error e and outputs a given torque current component i' _q And directly controlling the torque of the motor. Equation (4) is the transfer function of the PI speed controller.

In formula (4), K _p Proportional coefficient for PI speed controller，T _i Is the integration time constant of the PI speed controller. Given value T of load torque output by PI speed controller _L ^* And torque current given component i' _q Comprises the following steps:

wherein the given value of the load torque T _L ^* And (e) is sent to a load torque observer, and e (t) is a rotor angular speed error instantaneous value.

The parameters of the speed loop controller can be manually adjusted according to a conventional PID parameter adjusting method; empirically, the proportionality coefficient K _p Is greater than 0 and less than 10I _N ，I _N Rated current of the permanent magnet synchronous motor; integral time constant T _i The regulation range of (3) is 0.001 to 0.5s.

According to the PMSM electromagnetic torque and the motion equation, the constant value can be regarded as a constant value in a change period for constant step load, namely

The angular speed and the load torque of the motor rotor are used as state variables to form a PMSM state equation as follows:

based on the formula (6), the load torque and the angular speed of the motor rotor are taken as observation objects, and the embodiment 1 of the load torque observer is established as follows:

in the formula (7), the reaction mixture is,

is an observed value of the load torque,

is an estimate of the rotor angular velocity, g is the feedback gain of the load torque observer,

k _g is the sliding mode gain of the load torque observer embodiment 1, and the load torque observer embodiment 1 is a sliding mode observer. Motor friction is smaller in specific weight than load torque, let B =0, and neglecting the influence of friction, load torque observer embodiment 1 of equation (7) becomes:

from (6) and equation (8) when B =0, the error equation of load torque observer embodiment 1 is obtained as:

in the formula (9), the reaction mixture is,

for the estimation error of the angular velocity of the rotor,

for the observation error of the load torque, and defining the sliding mode surface of the observer as

According to the accessibility condition of the sliding mode, the system stability condition of the observer with the formula (8) is k _g ≤-|e ₂ And g is less than 0.

Based on the equation (6), the load torque and the angular speed of the motor rotor are taken as observation objects, and an embodiment 2 of the load torque observer can be established as follows:

when the motor friction is smaller in specific weight than the load torque, B =0, and the influence of the friction is ignored, load torque observer embodiment 2 of equation (10) becomes:

in the formulae (10) and (11),

is an observed value of the load torque,

is an estimate of the angular velocity of the rotor, g is the feedback gain of the load torque observer,

k _W is the proportional gain of load torque observer embodiment 2, load torque observer embodiment 2 being a state observer. According to the formula (6) and the formula (11) when B =0, the error equation of the load torque observer embodiment 2 is obtained as follows:

in the formula (12), the reaction mixture is,

for the estimation error of the angular velocity of the rotor,

is the load torque observation error. The state observer of equation (11) is an autonomous linear system, at k _W < 0, and g < 0, the observer is asymptotically stable. Both the formula (7) of the load torque observer embodiment 1 and the formula (10) of the load torque observer embodiment 2 take friction factors of the motor into consideration, and the addition of small friction damping adversely affects the rapidity of the system response, but may cause the rapidity of the system responseSo that the stability is increased on the basis of the formula (8) and the formula (11), respectively.

In observer embodiment 1 where expressions (7) and (8) are selected, sliding mode gain k _g Is according to

Selection is performed. In the formula (13), alpha is more than or equal to 1; typically, the value of α is selected in the range of 1 to 5, for example, α is selected to be equal to 1.5. Load torque observer embodiment 1 in observing load torque, k _g Is selected to be too small when | e ₂ When | is larger, the observer cannot enter a sliding mode state; k is a radical of _g The absolute value of the observer is selected to be large enough to ensure that the observer enters a sliding mode state, but the steady-state observation fluctuation of the load torque is increased; k is a radical of formula _g The value of (c) is changed along with the change of the load torque observation error, and the observer stability can be improved and the steady state observation fluctuation of the load torque can be reduced simultaneously.

When observer example 2 of expressions (10) and (11) is selected, proportional gain k _W Is set according to

Selection is performed. In formula (14), T _N Is the rated torque of the motor, beta is more than 0; in general, the β value is selected in the range of 1 to 20, for example, β =10. When the selection of beta is increased, the steady state fluctuation observed by the load torque is increased, but the tracking overshoot of the torque observation is reduced; when the beta selection is decreased, the steady state fluctuation of the load torque observation becomes small, but the torque observation overshoot amount becomes large.

In the observers represented by equations (7) and (8) or equations (10) and (11), the magnitude of the feedback gain g greatly affects the load torque observation result. The larger the feedback gain g is, the smaller the fluctuation of the observed torque is, but the slower the identification speed of the observed torque is; the smaller the feedback gain g, the faster the observed torque speed, but the greater the observed torque ripple. In consideration of this problem, in the conventional load torque observer, the observation speed and the fluctuation of the load torque are considered together, and the feedback gain g is taken as a median, but this abandons the advantages of small fluctuation when the feedback gain is large and fast observation speed when the feedback gain is small.

When the motor adopts a PI controller to control the speed, the influence of parameter change and external load disturbance on a system is mainly inhibited by increasing a proportionality coefficient in the controller, but the stability of the system is reduced due to the overlarge proportionality coefficient. In order to solve the contradiction between the rapidness and the stability of response and anti-interference of the PI speed controller, the observer is used for observing the disturbance change of the load in real time, and the observed value of the load torque is fed forward and compensated to the current regulator, so that the anti-interference performance of the system is not reduced on the premise of reducing the proportional coefficient of the PI controller. In order to fully utilize the advantages of the feedback gain g in high and low values, according to the load torque observation values at two adjacent moments and the magnitude of the load torque set value variation, when the load torque set value variation is small and the load torque observation value variation is small, a larger value is given to the feedback gain g, so that the observation result has small fluctuation and stronger stability; when the change of the set value of the load torque is large or the change of the observed value of the load torque is large, a smaller value of the feedback gain g is given to accelerate the observation speed, and finally, the comprehensive result of high observation speed, small fluctuation and stronger stability is obtained by adjusting the feedback gain g.

Fig. 2 is a flowchart of an embodiment of a feedback gain automatic adjustment method, and when the embodiment 1 of the load torque observer or the embodiment 2 of the load torque observer is used in the embodiment of the elevator permanent magnet synchronous motor drive control system in fig. 1, the feedback gain automatic adjustment is performed. In FIG. 2,. Epsilon ₁ Comparing thresholds, e, for lower limits of torque variation ₂ Comparing a threshold value for a torque variation upper limit; sum of variation of given value of load torque and variation of observed value of load torque in last 2 times

Wherein, delta T _L ^* For the difference between the load torque set points for the last 2 times,

the difference between the last 2 load torque observations. In the periodic control process of the primary permanent magnet synchronous motor drive control system, the adjustment of the feedback gain g shown in (b) of fig. 2 is later than the load torque observation and the output calculation of the PI speed controller, and there are:

step S1, a load torque observer performs T on load torque _L Observing to obtain the observed value of the load torque

The PI speed controller carries out control operation to obtain a given load torque value

At this time

Is composed of

Is composed of

Until the next adjustment of the feedback gain g, that time

Become into

Become into

Step S2, calculating

Computing

S3, judging whether delta T is larger than epsilon ₂ (ii) a When Δ T is greater than ε ₂ Taking feedback gain g equal to g _min And withdrawing; when DeltaT is less than or equal to epsilon ₂ If yes, the step S4 is carried out;

s4, judging whether delta T is smaller than epsilon ₁ (ii) a When Δ T is less than ε ₁ Taking feedback gain g equal to g _max And withdrawing; when Δ T is equal to or greater than ε ₁ If yes, the step S5 is carried out;

step S5, feedback gain g is according to

And (4) performing calculation.

Wherein epsilon ₁ Comparing thresholds, e, for lower limits of torque variation ₂ Comparing threshold values for upper limits of torque variation, and 0 & ltepsilon ₁ ＜ε ₂ ；g _max For high value of feedback gain, g _min Is a low value of feedback gain, and g _min ＜g _max ＜0。

In the periodic control process of the primary motor speed, the adjustment of the feedback gain g shown in (a) of fig. 2 precedes the load torque observation and the output calculation of the PI speed controller, the feedback gain g adjustment method changes the above step S1 to step S5, the steps S2 to S5 to steps S1 to S4, the exit in each step is changed to step S5, and

when Δ T is greater than ε ₂ Watch, clockThe observed value of the apparent load torque has large fluctuation, or the observed value of the load torque has large fluctuation due to the change of system model parameters, the change of the set value of the rotor angular speed and the change of the actual value of the rotor angular speed, and the feedback gain g is selected to be equal to g _min Carrying out rapid identification and observation on the load torque; when Δ T is less than ε ₁ When the feedback gain g is equal to g, the change of the given value of the load torque is small, the fluctuation of the observed value of the state load torque is small, and the feedback gain g is selected to be equal to g _max Carrying out load torque identification and observation mainly based on stability; when DeltaT is greater than or equal to epsilon ₁ And is less than or equal to epsilon ₂ And then, calculating the feedback gain g according to the formula (15), so that the feedback gain g is reduced along with the increase of the delta T in the interval, and the adverse effect on the working stability of the torque observer, which is caused by the fact that the feedback gain g is changed violently due to the small change of the delta T, is avoided. In FIG. 2, the given torque variation comparison threshold 0 < ε ₁ ＜ε ₂ ，ε ₁ 、ε ₂ Is related to the sampling control period (cycle time) of the PI speed controller, the permanent magnet synchronous motor and the load condition thereof, and epsilon ₂ Typically in the range of less than 5% of the rated torque, e.g. 22N m for rated torque, e ₁ ＝0.1N·m，ε ₂ =0.6N · m. The value of the feedback gain g satisfies g _min ＜g _max < 0, in general, g _min ≥-5000。g _min When the value is suddenly changed, the torque observation tracking overshoot of the load torque observer output observation value is within the torque observation tracking overshoot limit value; g _max The value should be that when the load torque is unchanged and the load torque observer and the PI speed controller are both in a steady state, the sum Delta T of the variation of the load torque given value and the variation of the load torque observed value for the last 2 times is less than epsilon ₁ (ii) a For example, the feedback gain g is selected _max ＝-0.5，g _min And (4) = -10. Selecting g _min 、g _max 、ε ₁ 、ε ₂ The specific method of the values is to start with the feedback gain g from a larger value, for example, gradually decrease the feedback gain g from-0.01, when the load torque is constant and both the load torque observer and the PI speed controller are in a steady state,the steady-state error observed by the load torque is gradually increased, and when the steady-state error observed by the load torque reaches the load torque observation steady-state error limit value, the feedback gain g value at the moment is determined to be g _max (ii) a Keeping the load torque constant and making the feedback gain g equal to g _max While continuously carrying out F ₁ Measurement of the sub- Δ T value, and F will be at this time ₁ Maximum F in sub- Δ T measurements ₂ The average value of the measured values of delta T is used as a lower limit comparison threshold epsilon of the torque variation ₁ (ii) a Then, when the load torque observer and the PI speed controller are both in a steady state, the load torque is suddenly changed, and g is adjusted and determined according to the condition that the tracking and adjusting time of the output observed value of the load torque observer is as short as possible on the premise that the torque observation tracking overshoot of the output observed value of the load torque observer is within the torque observation tracking overshoot limit value _min A value; then, the load torque is kept unchanged and the feedback gain g is made equal to g _min While continuously carrying out F ₁ Measuring the value of sub- Δ T, and comparing F ₁ Maximum F in sub- Δ T measurements ₂ The average value of the measured values of delta T is used as a torque change upper limit comparison threshold epsilon ₂ 。

When designing the PI speed controller and the load torque observer of the elevator permanent magnet synchronous motor drive control system embodiment, the PI speed controller parameters and the load torque observer can also be adjusted by adopting optimization algorithms such as a particle swarm algorithm, a wolf colony algorithm, a genetic algorithm and the like. The PI speed controller parameters are set by adopting a particle swarm algorithm, and a target function for comprehensively evaluating various performance indexes of the PI speed controller is established as

In formula (16), Q ₁₁ T in (1) _m The method comprises the steps that the transition process time of the angular speed step response of a motor rotor is obtained, and t =0 is the starting time of the step response of the motor; q ₁₁ Gamma in (1) _m1 (1-sgn(e(t)+ω _δ ) Term) is an angular velocity overshoot penalty function, where γ _m1 One is taken to be large enough (t) _m 5 times and above the rational value), omega) of a positive number _δ The value is the rotor angular speed overshoot limit (namely the maximum value of the rotor angular speed overshoot allowed by the system); when the overshoot of the angular speed step response of the motor rotor does not exceed the rotor angular speed overshoot limit value omega _δ The term overshoot penalty function is equal to 0 when, and is equal to γ otherwise _m1 ；Q ₁₂ For the steady state error penalty function, ω _Δ Is the rotor angular velocity steady state error limit; when the steady-state error of the angular speed step response of the motor rotor does not exceed the rotor angular speed steady-state error limit value omega _Δ The steady state error penalty function term is equal to 0 when, and is equal to γ otherwise _m1 ；Q ₁ The value is an objective function value, namely a fitness value for parameter optimization of the PI speed controller by the particle swarm optimization; the smaller the fitness value of the particle, the better the corresponding position. Gamma ray _m1 When taking value, firstly, t is estimated _m Reasonable value of (upper limit); for example, the rated rotation speed of the motor is 1500r/min (corresponding to the rated rotor angular speed of 157 rad/s), the rated load starting time is about 0.2s, t _m Is not more than 0.5s, then gamma is _m1 Is sufficiently large, 5 times or more, relative to 0.5, for example, γ _m1 ＝2.5。γ _m2 The value is generally more than or equal to 2, the size of the value determines how long the rotor angular speed steady-state error is measured in a time interval, and whether the rotor angular speed steady-state error exceeds the rotor angular speed steady-state error limit value omega or not is judged _Δ (ii) a E.g. gamma _m2 When the value is equal to 6, the time t of the transition process is 5 times _m The steady state error of the rotor angular velocity is measured. PI speed controller parameter optimization may establish other objective functions than (16) if other index factors need to be considered, such as whether overshoot is sufficiently small, steady state error is sufficiently small, and so forth.

When parameters in the embodiment 1 or the embodiment 2 of the load torque observer are set by adopting a particle swarm optimization, a target function for comprehensively evaluating various performance indexes of the load torque observer is established as

In the formula (17), the reaction mixture is,

for load torque observation errors, e ₂ (t) is a load torque observation error instantaneous value; q ₂₁ T in (1) _p Tracking and adjusting time of the motor load torque observation step response, wherein t =0 is the load sudden change time of the load torque observation step response; q ₂₁ Gamma in (5) _p1 (1-sgn(e ₂ (t)+T _δ ) Term) is a torque observation tracking overshoot penalty function, where γ _p1 One is taken to be large enough (t) _p +γ _p2 ·max(|e ₂ (T) |) 5 times and more the rational value), T _δ Tracking overshoot limit for torque observation, tracking overshoot limit when torque observation tracking overshoot does not exceed torque observation tracking overshoot limit T _δ The torque observation tracking overshoot penalty function term is equal to 0 when, and is equal to gamma otherwise _p1 。Q ₂₂ Max (| e) in the first term ₂ (t) |) is the absolute value of the steady-state error of the maximum torque observation, gamma _p2 Taking a constant larger than 0 for the fitness balance weight coefficient; q ₂₂ Gamma in (5) _p1 (1-sgn(e ₂ (t)+T _Δ ) Term) is a torque observation steady state error penalty function, T _Δ Observing a steady state error limit for the load torque; when the observed torque steady state error does not exceed the observed load torque steady state error limit T _Δ The torque observed steady state error penalty function term is equal to 0 when, and is equal to γ otherwise _p1 。Q ₂ The function value is a target function value, namely a fitness value for setting the parameters of the load torque observer by adopting a particle swarm algorithm; the smaller the fitness value of the particle, the better the corresponding position. Gamma ray _p1 When taking value, firstly, t is estimated _p +γ _p2 ·max(|e ₂ (t) |) reasonable value (upper limit); for example, assuming that the rated torque of the motor is 22N m, the maximum predicted torque is observed to track the regulation time t _p At about 0.1s, the load torque observes the steady state error limit T _Δ Is 1 N.m.gamma _p2 Taking 0.1 hour, the torque observation tracking adjustment time term and the maximum torque observation steady-state error absolute value term are relatively balanced, or 2 objective function values Q ₂ The functions are equivalent; at this time t _p +γ _p2 ·max(|e ₂ Reasonable value of (t) |) is not more than 0.2, gamma _p1 The value is equal to 1, or a constant greater than 1. Reduction of gamma _p2 Value, then objective function value Q ₂ The weight of the medium torque observation tracking adjustment time term is increased, and the rapidity of torque observation is more biased; increase gamma _p2 Value, then objective function value Q ₂ The weight of the steady-state error absolute value term of the medium and maximum torque observation becomes larger, and the steady-state performance of the torque observation is more biased. Gamma ray _p3 Typically a value of 2 or more, the magnitude of which determines how long the measurement of the steady state error of the load torque observation is made, e.g. gamma _p3 When the value is equal to 6, tracking and adjusting time (namely transition process time) t is 5 times _p The interval of (2) is measured for the load torque observation steady state error.

The particle swarm algorithm comprises the following specific steps:

step 101, initializing a particle swarm. Setting the initial position of the particles in the particle swarm to be

Wherein M is the number of particles in the particle group, generally selected from 20-150, and the initial position is required to obey random distribution.

(1) When the parameters of the PI speed controller are optimized, the parameter vector to be optimized is theta = [ K = _p ，T _i ]At the moment, the search space dimension N of the particle swarm algorithm is equal to 2, and in the final optimization result, the position value of the particle with the minimum fitness value is the optimal parameter of the PI speed controller. The position of the ith particle is shown as

Corresponding to the parameter vector θ to be optimized; the position value interval is [ m ] _imin m _imax ]The range interval can be given based on prior knowledge or experience, e.g., the parameter K _p Value range of [ m ] _1min m _1max ]Is [010I _N ]Parameter T _i Value range of [ m ] _2min m _2max ]Is [ 0.001.0.5 ]]。

(2) Observer for load torqueExample 1 when the parameters are optimized, the parameter vector to be optimized is theta ₁ ＝[G _max ，G _min ，ε ₁ ，ε ₂ ，α]At the moment, the search space dimension N of the particle swarm optimization is equal to 5, and g is used for optimizing the optimal position of the particle _max 、g _min According to the following

Sliding mode gain k _g Calculated according to the parameter α in accordance with equation (13). The initial position of the ith particle is expressed as

Corresponding to the parameter vector theta to be optimized ₁ (ii) a The position value interval is [ m ] _imin m _imax ]The range interval may be given based on prior knowledge or experience, e.g. the parameter G _max Value range of [ m ] _1min m _1max ]Is [ -4](ii) a Parameter G _min Value range of [ m ] _2min m _2max ]Is [ -4](ii) a Parameter epsilon ₁ Value range of [ m ] _3min m _3max ]And parameter epsilon ₂ Value range of [ m ] _4min m _4max ]Are all [ 0.05T _N ]，T _N Is the rated torque of the motor; value interval [ m ] of parameter alpha _5min m _5max ]Is [ 15 ]]。

(3) When parameters of the embodiment 2 of the load torque observer are optimized, a parameter vector to be optimized is theta ₂ ＝[G _max ，G _min ，ε ₁ ，ε ₂ ，β]At the moment, the search space dimension N of the particle swarm algorithm is equal to 5, and g is carried out after the optimal position of the particle is obtained through optimization _max 、g _min According to

Proportional gain k _W The parameters β are calculated according to equation (14). The initial position of the ith particle is expressed as

Corresponding to the parameter vector theta to be optimized ₂ (ii) a BitSetting the value interval as [ m ] _imin m _imax ]The range interval may be given based on prior knowledge or experience, e.g., θ ₂ The value interval of the middle and the front 4 parameters and theta ₁ The value intervals of the previous 4 parameters are the same; value interval [ m ] of parameter beta _5min m _5max ]Is [1 20 ]]。

In each optimized object in step 101, since the initial positions of the particles are required to be randomly distributed and the spatial search algorithm of the particle swarm is linear, the feedback gain is directly increased by a high value g _max And a low value of feedback gain g _min In the interval [ -5000 0]In search optimization, the absolute value of the feedback gain, which has a large influence on the observer operating state, is in a low range, for example, in the range of [ -100 [)]Meanwhile, the probability of particle entering is small, and the feedback gain high value g is difficult to obtain through optimization _max And a low value g of feedback gain _min The optimal position of (a). The feedback gain is not directly increased by a high value g in the optimization process _max And a low value of feedback gain g _min Search optimization is performed, but optimization is performed in a gain-like manner, with the parameter interval [ -100 []The search interval is expanded, and a high value g of the feedback gain is easily obtained _max And a low value g of feedback gain _min The optimal position of (a); at this time, the feedback gain is high value g _max And a low value g of feedback gain _min The parameter intervals of (A) are [ -10000-0.0001 [ -10000 [ -0.0001 [ ]](ii) a High value g of feedback gain _max Under normal conditions, it will not be in the range [ -0.0001 0]Selecting within the range, otherwise, causing the observer to respond too slowly; in addition, the upper limit of the interval is-0.0001, and the high value g of the feedback gain is also avoided _max The observer caused by taking a value of 0 does not work properly.

Step 102, setting the initial position m of each particle ⁽⁰⁾ As the initial optimum value m of each particle _b ⁽⁰⁾ Calculating a fitness function value (namely a particle fitness value) of each particle and storing the fitness function value as a particle optimal fitness value of each particle; the fitness values of all the particles are compared to obtain the optimal solution m of the initial particle swarm _g ⁽⁰⁾ And storing the optimal fitness value of the particle swarm. Let the initial velocity of the particles be

Also following a random distribution, the initial velocity of the ith particle is then expressed as

Extreme value of speed variation [ v ] of parameter _imin v _imax ]Generally setting the range of the parameter value interval to be 5-20 percent; for example, when the optimized parameter vector is θ, the parameter T _i Value range of [ m ] _2min m _2max ]Is [ 0.001.0.5 ]]And the interval range is 0.499, then the 2 nd dimension variable (parameter T) of each particle _i ) Speed change extreme value [ v ] _2min v _2max ]The value of 5% is [ -0.02495.02495 [ -0.02495%]The value is [ -0.0998.0998% according to 20%](ii) a The optimized parameter vector is theta ₁ Or theta ₂ Time, parameter G _max Value range of [ m ] _1min m _1max ]Is [ -4]And the interval range is 8, the 1 st dimension variable (parameter G) of each particle _max ) Speed change extreme value of [ v ] _1min v _1max ]The value of 5% is [ -0.4.0.4 ]]The value is [ -1.6.1.6 ] according to 20%]。

And step 103, updating the position. According to the formula

Updating the speed and position of each particle; the speed change of each dimension variable cannot exceed the corresponding speed change extreme value of each dimension variable, and the updating position of each dimension variable cannot exceed the corresponding value interval of each dimension variable. In the formula (18), n is the current iteration number, v ⁿ And m ⁿ Is the velocity vector and position of the particle; c. C ₀ The value range is 0-1.4 for inertial weight, the search range and the search speed can be changed by adjusting the value of the inertial weight, and further, the adaptive reduction c is realized along with the increase of the iteration times ₀ The value is favorable for achieving balance between searching capability and convergence speed; c. C ₁ 、c ₂ As a learning factorTaking values between 1 and 2, and suggesting that the values are all equal to 2;

is a random number with the value range of 0-1;

for the optimal solution (optimal position) found so far for the particle itself,

indicates the optimal solution (optimal position) of the particle group for the whole population up to now.

Step 104, updating the fitness value; the fitness value of each particle is calculated.

And 105, updating the optimal particle adaptability value and the optimal particle swarm adaptability value. To pair

And the corresponding optimal fitness value of the particle are updated to

And updating the corresponding particle swarm optimal fitness value.

Step 106, judging whether a cycle termination condition is met, if so, ending the particle swarm optimization, and finally solving the particle swarm optimal solution as the optimal parameter of the optimized parameter vector, namely the optimal parameter of a PI speed controller or a load torque observer; otherwise, return to step 103.

The loop termination condition is generally that the maximum iteration step number limit is reached or the optimal particle adaptation value is smaller than a certain threshold value, a maximum iteration step number limit mode is adopted as the loop termination condition, and the maximum iteration step number is usually selected from 100 to 2000. Parameter K is adjusted by particle swarm algorithm _p 、T _i Optimizing and setting are carried out, when the threshold condition of the particle swarm optimal fitness value is set, the starting time requirement of the motor is set to be within 0.2s, then the threshold of the optimal particle fitness value can be set to be 0.2, and when the requirement is improved to ensure a certain margin, the optimal particleThe threshold value of the sub adaptation value may be smaller than 0.2, for example, set to 0.15. Setting parameters of the load torque observer by adopting a particle swarm algorithm, and referring to expected torque observation, tracking and adjusting time t when setting a threshold condition of the optimal fitness value of the particle swarm _p Load torque observation steady state error limit T _Δ And the adaptability balance side weight coefficient gamma _p2 Etc. to determine the threshold size; let T _Δ Is 1 N.m.gamma _p2 Equal to 1.5, the desired torque observation tracks the adjustment time t _p Less than 0.04s, gamma _p2 Equal to 0.05, the threshold condition for the particle swarm optimal fitness value may be set at 0.06.

Parameter K is adjusted by particle swarm algorithm _p 、T _i Setting, when calculating the particle adaptability value of each particle according to the formula (16), sequentially using each particle as a corresponding controller parameter to control the motor to start (or start in a simulation system) to obtain e (t) of the angular speed step response of the motor rotor required in the formula (16), and determining the transition process time t according to the e (t) _m Calculating to obtain a particle fitness value Q ₁ 。

Setting parameters of a load torque observer by adopting a particle swarm algorithm, wherein the parameters of a PI speed controller in an embodiment of an elevator permanent magnet synchronous motor drive control system are already set, and the setting is carried out under the condition of realizing load torque compensation control; when the particle adaptability value of each particle is calculated according to the formula (17), the position of each particle is required to be sequentially converted into a corresponding load torque observer parameter, when the given speed of the motor is unchanged and the PI speed controller is in a steady state, the load torque is suddenly changed, the motor is controlled to operate (or operate in a motor simulation system), and the motor load torque observation step response e required in the formula (17) is obtained ₂ (t) according to e ₂ (t) determining a transient time t _p And observing the steady state error by the load torque, and calculating to obtain a particle fitness value Q ₂ 。

In the parameters of the load torque observer to be optimized, g _max 、g _min With a constraint g in between _min ＜g _max Corresponding to the constraint G _min ＞G _max . At the beginningTo initialize or update the particle position, first, the particle m _i1 According to the value-taking interval [ m _1min m _1max ]Position initialization or position update is performed, and then, the particle m _i2 According to the value-taking interval [ m _i1 m _2max ]Performing position initialization or position updating to make each particle m of each iteration _i All satisfy the constraint condition G _min ＞G _max I.e. satisfying the constraint g _min ＜g _max 。ε ₁ 、ε ₂ With a constraint condition epsilon between ₁ ＜ε ₂ When initializing the particle position or updating the particle position, first, the particle m _i Parameter m in _i3 (i.e.. Epsilon.) ₁ ) According to the value-taking interval [ m _3min m _3max ]Randomly generating positions or performing position updates, and then the particles m _i Parameter m of _i4 (i.e.. Epsilon.) ₂ ) According to the value-taking interval [ m _i3 m _4max ]Randomly generating positions or performing position updates to make the particles m _i Satisfies the constraint condition epsilon ₁ ＜ε ₂ 。

Observing to obtain a load torque observed value

Then, the observed value of the load torque is measured

Converted into a torque current compensation component i ″) _q Feed-forward compensating the input to a q-axis current PI controller, giving a component i 'to the torque current output from the PI speed controller' _q Compensation is performed. q-axis torque current given value i of q-axis current PI controller ^* _q Comprises the following steps:

in formula (19), k _q ＝1/(1.5pψ _f ) The compensation factor is observed for torque. Comparing the equations (5) and (19) can obtain the result when the load is disturbed or isWhen the system parameters are changed, load torque compensation is not added in the formula (5), and a larger K needs to be selected _p The value is used for providing enough large given current variation to counteract the disturbance of the load or the related influence of the variation of the system parameters so as to ensure that the rotating speed of the motor can be quickly constant; equation (19) feed-forward compensates the load torque observations into the current regulator without requiring a large K _p Under the condition of the value, when the load is disturbed or the system parameter is changed, a given current change quantity which is large enough is provided to offset the relevant influence of the disturbance of the load or the change of the system parameter, and the output pressure of the PI speed controller is reduced.

When the feedback gain value is fixed, the smaller the feedback gain g is, the larger the oscillation amplitude observed by the load torque is, and the stronger the fluctuation is; the larger the feedback gain g is, the smaller the oscillation amplitude observed by the load torque is, and the higher the observation accuracy is. The automatic gain adjustment algorithm solves the problems that small feedback gains in the load torque observer cause large torque observation fluctuation and large feedback gains have long convergence time, the convergence time and fluctuation amplitude indexes are superior to those of a compromise gain algorithm, the load torque change value can be quickly tracked, the observation error caused by given change or parameter change can be quickly reduced, the oscillation amplitude is small, the observation precision is high, and a good observation effect is achieved.

When a given rotation speed is changed at a rated load torque, although the actual load torque is not changed, as can be seen from the load torque observer constructed by equations (7), (8) or equations (10), (11), when the rotor angular velocity ω is changed, the observed torque observed value changes even if the load torque is not changed, resulting in an observation error. When the given rotating speed is changed under the rated load torque, the control and regulation process of the permanent magnet synchronous motor control system is that firstly, a PI speed controller changes according to the given speed to ensure that the output load torque given value T is changed _L ^* Is changed so that the given value i of the torque current ^* _q Changes so as to make the electromagnetic torque T of the permanent magnet synchronous motor _e The change drives the motor to change the angular speed omega of the rotor; if the feedback gain g is only dependent on the change of the load torque observationQuantity of

The automatic adjustment is carried out, and only when the angular speed omega of the rotor changes, the observed value of the load torque is enabled to be

After the change, the feedback gain g is adjusted; feedback gain g variation Δ T according to given value of load torque _L ^* And amount of change in observed value of load torque

Is automatically adjusted, when the given rotation speed is changed, the given value T of the load torque is caused to be changed _L ^* Change, load torque observed value

If no change has occurred, the feedback gain g is adjusted in advance, and the observed value of the load torque is adjusted

When the observation error is really generated, the response speed of the observer can be accelerated, and the observed value of the load torque can be eliminated (reduced) as soon as possible

The observation error of the motor is further improved, and the rapidity and the accuracy of the speed control of the motor are further improved. Similarly, when the system model parameter changes, the given value T of the load torque is caused to change _L ^* Prior to load torque observation

When changed, feedback gain _g While the variation amount DeltaT according to the given value of the load torque _L ^* And amount of change in observed value of load torque

Performing automatic adjustment to adjust the feedback gain g in advance, addFast observer response speed, eliminating (reducing) load torque observed value as soon as possible

Further improve the rapidity and accuracy of the motor speed control. Of course, the observed value is caused if the load is disturbed

When the change is made to the optical disk,

when a large change occurs, as can be seen from fig. 2, the feedback gain g can also be automatically adjusted to quickly cancel (reduce) the load torque observed value

To make the load torque observed value

Follow the load torque T as soon as possible _L A change in (c).

Further, in the embodiment of the elevator permanent magnet synchronous motor drive control system, after the parameters of the PI speed controller and the parameters of the load torque observer are sequentially set manually or in an optimization mode, the parameters of the PI speed controller can be manually fine-tuned under the condition of realizing load torque compensation control, or the parameters of the PI speed controller are re-optimized by adopting a particle swarm optimization according to the steps 101 to 106.

G is selected from the above _min 、g _max In the specific method of the value and the comparison threshold, the parameters in the PI speed controller are set and are realized under the condition of carrying out load torque compensation control; when the parameter value is determined manually, suggestion F is made ₁ Is an integer of 20 or more, F ₂ Is not less than 5 and not more than 0.5F ₁ Is an integer of (1).

In the periodic control process of the speed of the permanent magnet synchronous motor in the drive control system, the current k time (or k times)Kth) calculating the specified value T of the load torque _L ^* Is marked as T _L ^* (k) Observed value of load torque

Is marked as

The moment k-1 is the previous periodic control process moment of the moment k, and the given value T of the load torque _L ^* Is marked as T _L ^* (k-1), load torque observed value

Is marked as

The moment k-2 is the previous periodic control process moment of the moment k-1, and the given value T of the load torque _L ^* Is marked as T _L ^* (k-2), load torque observed value

Is marked as

The method for controlling the speed of the permanent magnet synchronous motor in the elevator permanent magnet synchronous motor drive control system comprises the following steps:

Thirdly, the load torque observer depends on the rotor angular speed omega and the current i _q To the load torqueObserving to obtain the observed value of the load torque

And a torque current compensation component i ″ _q ；

Step four, the PI speed controller gives the angular speed omega according to the input rotor ^* And the rotor angular speed omega is subjected to control calculation to obtain a load torque set value

And torque current given component i' _q ；

Step five, feedback gain g is given value T according to load torque _L ^* And load torque observed value

Is adjusted;

step six, giving component i 'according to torque current' _q And a torque current compensation component i ″) _q Calculating to obtain a given value i of q-axis torque current _q ^* (ii) a d-axis current controller according to d-axis torque current set value i _d ^* With current i in d-axis coordinate system _d PI control operation is carried out on the difference value between the two to obtain a control voltage U under a d-axis coordinate system _d (ii) a The q-axis current controller sets a value i according to the q-axis torque current _q ^* And the current i under a q-axis coordinate system _q PI control operation is carried out on the difference value between the two to obtain a control voltage U under a q-axis coordinate system _q (ii) a According to the control voltage U under a d-q axis coordinate system _d 、U _q Carrying out Park inverse transformation to obtain a control voltage U under an alpha-beta axis coordinate system _α 、U _β (ii) a d-axis torque current set value i _d ^* Equal to 0;

The steps are as followsIn the step, the sequence of the third step, the fourth step and the fifth step can be interchanged, that is, the fifth step can be performed first, and then the third step and the fourth step can be performed. In the step (b) of fig. 2, the load torque observation and the speed control are performed first according to the above steps three, four and five, and then the feedback gain automatic adjustment is performed,

ΔT _L ^* ＝T _L ^* (k)-T _L ^* (k-1). In FIG. 2, (b) the feedback gain is automatically adjusted first, and then the load torque observation and speed control are performed,

ΔT _L ^* ＝T _L ^* (k-1)-T _L ^* (k-2); in this case, the fifth step is performed first, and the third and fourth steps are performed later.

Parameters of the PI speed controller and the load torque observer can be optimized uniformly by adopting optimization algorithms such as a particle swarm algorithm, a wolf colony algorithm, a genetic algorithm and the like, and the optimization is carried out by adopting the wolf colony algorithm as an example, at the moment, the angular speed omega of the rotor given by the system motor is ^* The step signal is shown in (a) of fig. 4, and the load torque T is changed in accordance with (b) of fig. 4 _L . Given the angular speed ω of the rotor ^* The signal is a step signal and the angular speed of the rotor is set

Not more than the rated angular speed of the motor and not less than 80 percent of the rated angular speed of the motor. In fig. 4 (b), when the motor is started (T = 0), the load torque is the load torque high value T _Lmax (ii) a When the motor enters a stable rotor angular speed state (t > t) _z ) After that, the load torque is changed from a high value T _Lmax Reduction of the mutation to a low value T _Lmin (ii) a The load torque is maintained at a low value T _Lmin Run time

Then, from a low value T _Lmin Mutation increases to a high value of T _Lmax (ii) a Wherein the load torque is high value T _Lmax Not greater than rated load torque of motor, and low value T of load torque _Lmin Not less than 10% of rated load torque of motor, and high value T of load torque _Lmax With low value T of load torque _Lmin The difference between the two is not less than 50% of the rated load torque of the motor;

is 2 to 5t _z A random value in between. The step signal is used as the angular speed signal of the given rotor of the motor, the load torque sudden change is controlled when the angular speed of the rotor of the motor runs in a steady state, the parameters of a PI speed controller and a load torque observer are optimized simultaneously by constructing the comprehensive performance indexes of the starting stage and the steady state running stage of the motor, the influence of the good performance of the load torque observer is unified to the angular speed performance indexes of the rotor, the parameter optimization process is simplified, and meanwhile, the angular speed performance indexes of the rotor can be improved to the maximum extent.

Considering that the load torque observer mainly has the effect of improving the load interference resistance of the PI speed controller, and establishing a target function for comprehensively evaluating various performance indexes of the PI speed controller and the load torque observer as

In the formula (20), Q ₃₁ The integral term in (1) is the IAE criterion of the motor rotor angular speed step response starting stage, t _z The method comprises the steps that the transition process time of the angular speed step response of a motor rotor is represented, and t =0 is the starting time of the step response of the motor; q ₃₁ The second term γ in (1) _z1 (1-sgn(e(t)+ω _δ ) Is an angular velocity overshoot penalty function, where γ _z1 One is large enough (

5 times and above the rational value), omega) of a positive number _δ The value is the rotor angular speed overshoot limit (namely the maximum value of the rotor angular speed overshoot allowed by the system); when the overshoot of the angular speed step response of the motor rotor does not exceed the rotor angular speed overshoot limit value omega _δ The overshoot penalty function term is equal to 0 when, and is equal to y otherwise _z1 ；Q ₃₂ The integral term in the method is an IAE criterion of the motor rotor in the steady-state working stage of the angular speed, and the steady-state error and the problem anti-interference performance are comprehensively considered; q ₃₂ The second term γ in (1) _z1 (1-sgn(e(t)+ω _Δ ) ) is a steady state error penalty function, ω _Δ Is the rotor angular velocity steady state error limit; when the steady-state error of the angular speed step response of the motor rotor does not exceed the rotor angular speed steady-state error limit value omega _Δ The steady state error penalty function term is equal to 0 when, and is equal to y otherwise _z1 ；Q ₃ The function value is an adaptive value for optimizing parameters of a PI speed controller and a load torque observer by a wolf pack algorithm; the smaller the fitness function value of the individual wolf is, the better the corresponding position is. Gamma ray _z2 Typically 6 or more, the magnitude of which determines how long a steady-state error of the rotor angular velocity is measured, e.g. gamma _z2 When the value is equal to 10, the time t of the transition process is 9 times _z Measuring the steady-state error of the angular speed of the rotor in the interval; t is equal to gamma _z2 t _z Should be later than the moment at which the load torque changes from the low value T in fig. 4 _Lmin Mutation increasing to a high value T _Lmax Time of day (c). Gamma ray _z A constant larger than 0 is taken for a fitness balance adjustment coefficient and is used for balancing the starting performance and the steady-state performance (including steady-state error and anti-interference capability) of the motor; reduction of gamma _z Value, then objective function value Q ₃ The weight of the middle starting performance item is increased, and the system performance is more biased to the rapidity of motor starting; increase of gamma _z Value, then objective function value Q ₃ The weight of the middle steady-state performance item is increased, and the system performance is more biased to the steady-state performance and the anti-interference capability of the speed control. Gamma ray _z1 When taking value, firstly, the value is estimated

Reasonable value of (upper limit); for example, the rated rotation speed of the motor is 1500r/min (corresponding to the rated rotor angular speed of 157 rad/s), the starting time is about 0.2s, and Beebel

The item number does not exceed 40; let gamma _z2 Value equal to 10, gamma _z Equal to 2 and rotor angular velocity steady state error limit ω _Δ Equal to 2rad/s, in this case

Has a reasonable value of not more than 60, gamma _z1 A constant equal to or greater than 300 may be used. PI speed controller parameter optimization may establish other objective functions than (20) if needed to take into account other index factors, such as whether the transient time is short enough, the steady state error is small enough, and so on.

The method for optimizing parameters of a PI speed controller and a load torque observer in an elevator permanent magnet synchronous motor drive control system embodiment by adopting a wolf pack algorithm comprises the following specific steps:

in step 301, a wolf pack is initialized. The initial position of each body wolf in the wolf group is set as

Where M is an individual number, generally selected between 20 and 150, and the initial position is required to be subject to a random distribution. For different optimized objects, there are:

(1) For the PI speed controller and load torque observer embodiment 1, the parameter vector to be optimized is μ 1= [ K _p ，T _i ，G _max ，G _min ，ε ₁ ，ε ₂ ，α]At the moment, the searching space dimension N of the wolf cluster algorithm is equal to 7, and g is obtained after the final wolf head position is obtained through optimization _max 、g _min According to the following

Sliding mode gain k _g According to the parameter alpha, according to the formula (13)Respectively calculating to obtain. The initial position of the ith wolf is shown as

Corresponding to the parameter vector mu to be optimized ₁ (ii) a The position value interval is [ z ] _imin z _imax ]The range interval can be given based on prior knowledge or experience, e.g., the parameter K _p Value range of [ z ] _1min z _1max ]Is [010I ] _N ]Parameter T _i Value range of [ z ] _2min z _2max ]Is [0.0010.5 ]]Parameter G _max Value range of [ z ] _3min z _3max ]Is [ -4](ii) a Parameter G _min Value range of [ z ] _4min z _4max ]Is [ -4](ii) a Parameter epsilon ₁ Value range of [ z ] _5min z _5max ]And parameter epsilon ₂ Value range of [ z ] _6min z _6max ]Are all [ 0.05T _N ]，T _N Rated torque of the motor; value range [ z ] of parameter alpha _7min z _7max ]Is [ 15 ]]。

(2) For the PI speed controller and load torque observer embodiment 2, the parameter vector to be optimized is μ ₂ ＝[K _p ，T _i ，G _max ，G _min ，ε ₁ ，ε ₂ ，β]At the moment, the searching space dimension N of the wolf cluster algorithm is equal to 7, and g is used for optimizing the final wolf head position _max 、g _min According to

Proportional gain k _w The parameters β are calculated according to equation (14). The initial position of the ith wolf is shown as

Corresponding to the parameter vector mu to be optimized ₂ (ii) a The position value interval is [ z ] _imin z _imax ]The range interval may be given based on prior knowledge or experience, e.g. the vector μ ₂ Middle and first 6 parameter value intervals and vector mu ₁ The first 6 parameters are the same, and the value interval [ z ] of the parameter beta _7min z _7max ]Is [1 20 ]]。

In step 302, hunting competition. Calculating the adaptive value of each wolf in the wolf group according to the formula (20), wherein the smaller the adaptive value is, the better the position of the wolf is; selecting 1 wolf with the best position as the wolf, and selecting R with the best position except for the wolf ₁ The wolf is the competitive wolf. R ₁ The wolves for competition are used for developing hunting searching behaviors according to the formula (21), and meanwhile, the wolves for competition are used for the wolves for competition according to the size of the adaptive value, and the method specifically comprises the following steps:

step 3021, selecting h randomly for the wolf race ₁ A direction, which is further advanced and then retreated according to the formula (21) along each direction search parameter; calculating the adaptive value after the forward movement according to the formula (20), selecting the minimum adaptive value in all directions, and replacing the home position of the wolve race with the position of the minimum adaptive value if the minimum adaptive value is smaller than the adaptive value of the home position of the wolve race; when the adaptive value of the wolves is smaller than that of the wolf head, the wolves is taken as the wolf head and the hunting competition is quitted, otherwise, the step 3022 is entered;

step 3022, repeating h for each wolf race ₂ The next step 3021;

step 3023, all R ₁ After the wolves for hunting completes step 3022, the hunting competition is exited.

In the formula (21), i =1,2, \8230;, R ₁ (ii) a j =1,2, \ 8230;, N; rand (-1, 1) is uniformly distributed in [ -1.1 ]]A random number within; l =1,2, \ 8230;, h ₁ (ii) a Stepa is the hunting step length, and the value range of the suggested Stepa is [ 0.1.0.9 ]]；z _i ＝[z _i1 z _i2 … z _iN ]Is the location of the ith winning wolf. R ₁ Suggested in the interval [0.1M 0.25M]Taking a fixed value or a random value; number of directions h ₁ Suggested in the interval [3 8]Value, repetition number h ₂ Suggested in the interval [3 10]And (4) taking a value.

Step 303, call a flush. The head wolf and other wolfs except the competitive wolf develop the running search behavior according to the formula (22) and run towards the head wolf. Calculating an adaptive value of the new position according to the formula (20), and changing the position of the new position searched by the ith wolf when the new position is superior to the current position of the ith wolf, or keeping the position unchanged; if the new position searched by the ith wolf is better than the wolf position, the ith wolf is converted into the wolf and the call is initiated again.

z′ _ij ＝z _ij +rand(-1，1)·stepb·(z _bj -z _ij ) (22)

In the formula (22), i =1,2, \8230;, M-R ₁ -1；j＝1，2，…，N；z′ _i ＝[z′ _i1 z′ _i2 …z′ _i8 ]Indicating the location of the ith wolf search update; z is a radical of _i ＝|z _i1 z _i2 … z _iN ]Represents the current position of the ith wolf; z is a radical of _b ＝[z _b1 z _b2 … z _bN ]Indicating the current wolf location; stepb is the running step length, and the value range of the suggested Stepb is [ 1.3.2.5 ]]。

And step 304, the prey is attacked. Under the calling of the head wolf, other wolfs push type (23) can carry out the attack on the prey. Calculating an adaptive value of a new position according to the formula (20), and changing the position of the wolf when the new position searched in the ith wolf attacking process is superior to the current position, or keeping the position unchanged; if the new position searched by the ith wolf attack is better than the wolf position, the ith wolf is converted into the wolf.

In formula (23), i =1,2, \8230;, M-1; j =1,2, \8230, N;

representing the current position of the ith wolf (i.e. the position over n iterations),

a new position searched for the ith wolf attack is attacked; z is a radical of formula _b ＝[z _b1 z _b2 … z _bN ]Indicating the current wolf location; delta isThe value range of the suggested delta is [ 0.1.0.4 ] according to the preset threshold value]；z _jmax And z _jmin Respectively the maximum value and the minimum value of the j-dimension parameter value interval; stepc is the attack step size and is calculated according to equation (24).

In the formula (24), n is the current iteration number, and n _max Is the set maximum iteration number; stepc _max 、stepc _min The maximum tapping step length and the minimum tapping step length are set respectively, and xi is a tapping step length attenuation factor. Suggested stepc _min Is in the range of [ 0.3.1.3]，stepc _max Taking the value as stepc _min 5 to 100 times higher. n increases from 1 to n _max When, stepc follows stepc exponentially _max Decay to stepc _min Adjusting the size of the attack step attenuation factor xi, and adjusting the relative attenuation speeds of the early stage and the later stage of the attack step; the larger the xi value is, the faster the attenuation speed of the early stage of the stepc relative to the later stage is, and the longer time of the later stage is approximately equal to the step _min (ii) a The smaller the xi value is, the slower the attenuation speed of the early stage of the stepc is relative to the later stage, and the later stage still shows the attenuation state and approaches the stepc _min (ii) a Xi is in the value range of 1.5 10]. FIG. 3 is a diagram showing the effect of the attack step attenuation factor xi adjusting the attack step stepc relative attenuation speed; in FIG. 3, the horizontal axis represents the number of iterations n, n _max Equal to 1000; the longitudinal axis is the attack step size stepc _max Equal to 10,stepc _min Equal to 1; curve (1) is the attenuation curve for stepc when ξ equals 2, and curve (2) is the attenuation curve for stepc when ξ equals 8.

When the xi is large, the proportion of the later small-step accurate search process is increased, which is more beneficial to finding out an accurate optimal solution; xi takes a small value, so that the diversity in the later searching stage is enhanced, and local optimality near the optimal solution is more favorably avoided; aiming at different optimized objects such as searching an accurate optimal solution and avoiding local optimal objects near the optimal solution, the maximum adaptation can be carried out by reasonably selecting the value of the attack step attenuation factor xi so as to achieve different optimization effects.

Step 305, the condition determination is terminated. If the loop iteration times reach or the head wolf adaptive value is smaller than a certain threshold value, the optimization process is terminated, and the head wolf position parameter is the optimal parameter of the optimized parameter vector. Otherwise let n = n +1, go to step 306.

Step 306, contend for updates. Randomly generating R according to the principle of elimination of advantages and disadvantages ₂ Wolf replacing original R ₂ The rejected wolf with the worst fitness value competes for updating wolf clusters, and the process goes to step 302.R ₂ Suggested in the interval [0.05M 0.15M]Take a fixed value or a random value.

In the above steps, a new position of the individual wolf is randomly generated, or when the individual wolf searches for the new position, the dimensional variable of the new position of each wolf cannot exceed the value range corresponding to the variable. Among the parameters to be optimized, g _max 、g _min With a constraint g in between _min ＜g _max Corresponding to the constraint G _min ＞G _max . When randomly generating a new location of an individual wolf or searching for an individual wolf to generate a new location, first, the individual wolf z _i Parameter z in _i3 According to the value range [ z _3min z _3max ]Randomly generating a location or making a location update, then the individual wolf z _i Parameter z of _i4 According to the value range [ z _i3 z _4max ]Randomly generating position or updating position to make individual wolf z _i Satisfies the constraint condition G _min ＞G _max I.e. satisfying the constraint g _min ＜g _max 。ε ₁ 、ε ₂ With a constraint condition epsilon therebetween ₁ ＜ε ₂ When randomly generating a new location of an individual wolf or searching for an individual wolf to generate a new location, first, the individual wolf z _i Parameter z in _i5 (i.e.. Epsilon.) ₁ ) According to the value range [ z _5min z _5max ]Randomly generating a location or making a location update, then the individual wolf z _i Parameter z of _i6 (i.e.. Epsilon.) ₂ ) According to the value interval [ z _i5 z _6max ]Randomly generating position or updating position to make individual wolf z _i Satisfies a constraint condition epsilon ₁ ＜ε ₂ 。

In step 305, the termination condition adopts a maximum iteration step number limiting mode, and the maximum iteration number n _max Suggesting a range of [20 500 ]]A fixed value is taken. Meanwhile, when the condition that the head wolf adaptive value is smaller than a certain threshold value is set, the threshold value termination condition needs to comprehensively consider the starting performance and the anti-interference performance of the motor speed control. For example, if the rated rotational speed of the motor is 1500r/min (corresponding to a rated rotor angular speed of 157 rad/s), the start-up time requirement is within 0.2s, and the anti-interference performance and the start-up performance are substantially balanced, the threshold of the end condition may be set to 30.

In each step, when calculating the adaptive value of the new position according to equation (20), it is required to sequentially convert the individual wolf position into the corresponding PI speed controller parameter and load torque observer parameter, control the operation of the motor (or operate in a simulation system), and set the angular speed ω of the rotor in the system motor ^* As step signal, load torque T _L Under the condition that the rotor angular speed is subjected to sudden change in a steady state, the speed response e (t) of the motor is obtained, and the transient process time t is determined according to the e (t) _z Meanwhile, the adaptive value Q of the wolf is obtained by calculating according to e (t) ₃ 。

In each of the above embodiments, the rotor angular speed steady-state error refers to a difference between an instantaneous value of the angular speed of the motor rotor and a steady-state value in a steady state, and the rotor angular speed steady-state error limit value is a maximum absolute value of the rotor angular speed steady-state error allowed by a system; the rotor angular velocity steady state error limit is generally the same as the maximum value of the rotor angular velocity steady state error allowed by the system. The torque observation tracking overshoot limit is typically 1% to 10% of the rated torque of the motor, specifically, the torque observation tracking overshoot limit is 2% of the rated torque, or 5% of the rated torque, or 10% of the rated torque, and so on. The tracking adjustment time refers to the process time from the moment when the load torque is suddenly changed from one fixed value to another fixed value and from the moment when the sudden change starts to the moment when the output observation value of the load torque observer stably enters the range of the load torque observation steady-state error limit value; the load torque observation steady state error refers to an error between an observation torque instantaneous value and a load torque when the load torque is unchanged and a load torque observer is in a steady state, and the error comprises an observation error caused by buffeting of the sliding mode observer (or steady state fluctuation of the state observer) and an observation error caused by interference reasons except load fluctuation; the load torque observation steady-state error limit value is the maximum absolute value of the load torque observation steady-state error allowed by the load torque observer; the load torque observed steady state error limit is generally the same as the maximum value of the load torque observed steady state error allowed by the system; the observed load torque steady state error limit is typically 1% to 5% of the rated torque of the motor, specifically, the observed load torque steady state error limit is 1% of the rated torque, or 2% of the rated torque, or 5% of the rated torque, and so on. The torque observation tracking overshoot refers to that the load torque is suddenly changed from one constant value to another constant value, and the observed value output by the load torque observer exceeds the maximum deviation value of the load torque after sudden change. When the observed steady state error of the load torque is within a range proximate to the observed steady state error limit of the load torque, for example, within a range of 95% to 105%, or within a range of 98% to 102%, the observed steady state error of the load torque is considered to increase to the observed steady state error limit of the load torque.

In the invention, the elevator permanent magnet synchronous motor driving control system is a permanent magnet synchronous motor speed control system. The speed control system of the permanent magnet synchronous motor and the speed control method of the permanent magnet synchronous motor including the control parameter optimization method of the permanent magnet synchronous motor provided by the invention can be used for other permanent magnet synchronous motor application occasions besides being used for a drive control system of an elevator permanent magnet synchronous motor.

In addition to the technical features described in the specification, other technical features related to the invention are the conventional technical skill which is mastered by a person skilled in the art. For example, the q-axis current controller and the d-axis current controller adopt PI controllers for control and selection of controller parameters, the PI speed controller for selection of control parameters, the position and speed detection module uses a rotary transformer or a photoelectric encoder for detection of the rotation angle and the rotation speed of the rotor of the permanent magnet synchronous motor, and the Clarke transformation module, the Park inverse transformation module, the SVPWM module, and the transformation method and the application method of the three-phase inverter, etc., all of which are conventional techniques grasped by those skilled in the art.

Claims

1. A permanent magnet synchronous motor control parameter optimization method, the permanent magnet synchronous motor speed is controlled by PI speed controller, the load torque observer observes the load torque, the output of the load torque observer is used for carrying on the load torque compensation to the output of PI speed controller, characterized by, the parameter of PI speed controller and load torque observer adopts the wolf crowd algorithm to optimize and set jointly;

in the wolf group algorithm, the wolf is to develop the attack on the prey according to the formula

Carrying out the following steps; wherein i =1,2, \8230, M-1; j =1,2, \ 8230;, N; m is the number of wolfs in the wolf pack, and N is the search space dimension of the wolf pack algorithm;

represents the current position of the ith wolf; z is a radical of _b ＝[p _b1 p _b2 …p _bN ]Indicating the current wolf location; delta is a preset threshold value, and the value range of delta is [ 0.1.0.4 ]]；z _jmax And z _jmin Respectively the maximum value and the minimum value of the j-dimension parameter value interval; stepc is the attack step size, according to formula

Calculating; wherein n is the current iteration number, n _max Is the set maximum iteration number; stepc _max 、stepc _min Respectively setting a maximum attack step length and a minimum attack step length; xi is a tapping step attenuation factor, and xi is more than or equal to 1.5 and less than or equal to 10.

2. The PMSM control parameter optimization method of claim 1, wherein the PI speed controller outputs a load torque set value

And torque current given component i' _q Is composed of

Wherein p is the number of pole pairs of the motor, psi _f Is a permanent magnet flux linkage; k _p Proportional coefficient, T, of PI speed controller _i Is the integral time constant of the PI speed controller; rotor angular velocity error e = ω of the electric machine ^* -ω，ω ^* For a given rotor angular velocity, ω is the rotor angular velocity, e (t) is the rotor angular velocity error instantaneous value;

the load torque observer is

Wherein J is the moment of inertia,

is an estimated value of the angular velocity of the rotor, g is a feedback gain of the load torque observer, and g is less than 0;

For load torque observation errors, T _L In order to be a load torque,

is a load torque observation.

3. The permanent magnet synchronous motor control parameter optimization method according to claim 2, wherein the output of the load torque observer performs load torque compensation on the output of the PI speed controller by using an observed value of the load torque

Converted into torque current compensation component i ″ _q Feedforward compensation is carried out to the input of a q-axis current PI controller; set value of q-axis torque current

Is composed of

4. The permanent magnet synchronous motor control parameter optimization method according to claim 3, wherein the load torque observer is used for setting the value according to the load torque

And load torque observed value

The feedback gain g is adjusted by the change of (2):

Step S2, calculating

Computing

step S5, feedback gain g is according to

Calculating;

wherein epsilon ₁ Comparing thresholds, e, for lower limits of torque variation ₂ Comparing threshold values for upper limits of torque variation, and 0 & ltepsilon ₁ ＜ε ₂ ；g _max For high value of feedback gain, g _min Is a feedback gain low value, and g _min ＜g _max ＜0。

5. The method of claim 4, wherein an objective function Q for comprehensively evaluating performance indexes of the PI speed controller and the load torque observer is established ₃ Is composed of

Wherein, t _z The transition process time of the angular speed step response of the motor rotor is shown, and t =0 is the step response of the motorThe starting time of (2); q ₃₁ Gamma in (5) _z1 (1-sgn(e(t)+ω _δ ) Term is a rotor angular velocity overshoot penalty function, γ) _z1 Is a sufficiently large positive number, ω _δ The rotor angular speed overshoot limit value is obtained; q ₃₂ Gamma in (5) _z1 (1-sgn(e(t)+ω _Δ ) Term) is a steady state error penalty function, ω _Δ Is the rotor angular velocity steady state error limit; gamma ray _z Adjusting the coefficient and gamma for fitness balance _z ＞0；γ _z2 ≥6；

The parameter vector to be optimized is mu ₁ ＝|K _p ，T _i ，G _max ，G _min ，ε ₁ ，ε ₂ ，α]The search space dimension N of the wolf pack algorithm is equal to 7.

6. Method for optimizing control parameters of a permanent magnet synchronous machine according to claim 5, characterized in that the rotor angular speed ω is given ^* Is a step signal; at the time of motor start, load torque T _L For high value T of load torque _Lmax (ii) a At t > t _z After the motor enters the stable state of the angular speed of the rotor, the load torque T _L From a high value T _Lmax Reduction of the mutation to a low value of T _Lmin (ii) a Load torque T _L Is maintained at a low value T _Lmin Run time

Is 2 to 5t _z A random value in between.

7. The PMSM control parameter optimization method of claim 6, wherein the load torque high value T _Lmax Not greater than rated load torque T of motor _N Low value of load torque T _Lmin Not less than rated load torque T of motor _N 10% of (d), high value of load torque T _Lmax With low value T of load torque _Lmin The difference between the motor load torque and the motor load torque is not less than the rated load torque T of the motor _N 50% of the total weight of the steel.

8. The permanent magnet synchronous motor control parameter optimization method according to any one of claims 5-7, characterized in that the wolf group algorithm is:

Step 302, hunting for competition; calculating the adaptive value of each wolf in the wolf group, wherein the smaller the adaptive value is, the better the position of the wolf is; selecting 1 wolf with optimal position as wolf head, and selecting R with optimal position except for wolf head ₁ The wolf is a competitive wolf; r ₁ The wolves are selected by the match to spread hunting searching behaviors, compete and replace the wolf;

step 304, surrounding and attacking preys; under the calling of the head wolf, other wolfs carry out the attack on the prey; calculating an adaptive value of the new position of the ith wolf, changing the position of the ith wolf when the new position searched in the attacking process of the ith wolf is superior to the current position, and keeping the position unchanged if not; if the new position searched by the ith wolf attack is superior to the wolf position, the ith wolf is converted into the wolf;

step 306, competition updating; random generation of R ₂ The wolf replaces R in wolf group ₂ The wolf with the worst adaptation value is matched, and the process goes to step 302.

9. The permanent magnet synchronous motor control parameter optimization method of claim 8, wherein g is _max And G _max In a relationship of

g _min And G _min In a relationship of

k _g In relation to alpha is

Wherein alpha is more than or equal to 1.

10. The permanent magnet synchronous motor control parameter optimization method according to claim 1, wherein a rotor position θ and a three-phase current i of the permanent magnet synchronous motor are detected _a 、i _d And i _c (ii) a According to three-phase current i _a 、i _d And i _c Clark transformation is carried out on the permanent magnet synchronous motor to obtain current i under an alpha-beta axis coordinate system _α Current i _β According to the current i _α Current i _β Carrying out Park conversion on the rotor position theta to obtain a current i under a d-q axis coordinate system _d Current i _q 。