A speed optimization control method for permanent magnet synchronous motor

Abstract

The invention discloses a speed optimization control method for a permanent magnet synchronous motor. A sliding mode speed controller adopts an integral sliding mode control method. A load torque observer observes the load torque according to the rotor angular velocity and the q-axis current to obtain a load torque observation value. The load torque observation value output by the load torque observer is sent to the sliding mode speed controller. The feedback gain of the load torque observer is automatically adjusted according to the change in the load torque given value. When the system speed changes, or the parameters change, the load is disturbed, and the load torque given value changes or / and the load torque observation value changes, the observation error of the load torque is quickly reduced and the load torque observation value is feed-forward compensated to the given value of the current regulator, which effectively weakens the jitter of the system, and has fast dynamic response speed, high robustness, and improves the control accuracy of the motor speed.

Description

[0001] This invention patent application is a divisional application. The original application number is 202010918643.X. The application date is September 4, 2020. The name of the invention is wind turbine electric variable pitch motor drive control system. Technical Field

[0002] The present invention relates to the technical field of permanent magnet synchronous motors, and more specifically, to a speed optimization control method for permanent magnet synchronous motors. Background Art

[0003] Permanent magnet synchronous motors have the advantages of high efficiency, high torque, and good speed performance, and are widely used in manufacturing, electric vehicles, industrial production, etc. Due to the randomness of wind speed and the influence of aerodynamic effects, the motor drive control system of wind turbine variable pitch is a multivariable strong nonlinear uncertain system with large load inertia, fast torque change, and different pitch angle speed regulation performance required at different wind speeds and wind directions; the parameters of the traditional wind turbine pitch angle PI controller are fixed, and the robustness is not as good as the sliding mode control method, but the sliding mode control method will cause obvious jitter in the motor speed when load disturbance or internal parameter perturbation occurs. Summary of the invention

[0004] The purpose of the present invention is to provide a method for optimizing the speed control of a permanent magnet synchronous motor by feedforwarding the observed load torque to the current regulator, improving the load torque observation response speed and reducing the torque observation volatility, in view of the characteristics of the wind turbine variable pitch system being a multivariable strongly nonlinear uncertain system with large load inertia, fast torque change, and different pitch angle speed regulation performances required under different wind speeds and wind directions. The sliding mode speed controller adopts an integral sliding mode control method, and the load torque observer is based on the rotor angular velocity ω and the q-axis current i q Observe the load torque and obtain the load torque observation value Load torque observation value output by the load torque observer is sent to the sliding mode speed controller; it is characterized in that the q-axis given current output by the sliding mode speed controller includes the load torque observation value The q-axis given current output by the speed sliding mode controller is directly used as the q-axis torque current given value of the q-axis current controller, which plays the role of load torque compensation. The parameters of the sliding mode speed controller and the load torque observer are uniformly optimized and adjusted using the wolf pack algorithm. The objective function is:

[0005] Q3=ω z +γ z τ.

[0006] Among them, ω z is the rotor angular velocity tracking error, τ is the tracking delay time, γ z is the fitness balance adjustment coefficient and γz > 0. The given rotor angular velocity ω* is a sine wave signal; the rotor angular velocity tracking error ω z is the vibration amplitude of the rotor angular velocity ω, and the tracking delay time τ is the difference between the rotor angular velocity ω and the given rotor angular velocity ω * The delay time between.

[0007] The method for obtaining the tracking delay time τ is: the tracking delay time τ is an average value of the negative crossing tracking delay time τ1 and the positive crossing tracking delay time τ2 of multiple cycles.

[0008] The method for obtaining the negative crossing tracking delay time τ1 is to take the center point of the previous sampling moment of the first negative crossing of the rotor angular velocity and the subsequent sampling moment of the last negative crossing of the rotor angular velocity as the rotor angular velocity negative crossing moment; the absolute value of the time difference between the given rotor angular velocity negative crossing moment and the rotor angular velocity negative crossing moment is the negative crossing tracking delay time τ1.

[0009] The method for obtaining the forward crossing tracking delay time τ2 is to take the center point between the previous sampling moment of the first forward crossing of the rotor angular velocity and the subsequent sampling moment of the last forward crossing of the rotor angular velocity as the rotor angular velocity forward crossing moment; the absolute value of the time difference between the given rotor angular velocity forward crossing moment and the rotor angular velocity forward crossing moment is the forward crossing tracking delay time τ2.

[0010] Get the rotor angular velocity tracking error ω z The method is: the rotor angular velocity tracking jitter difference ω z is the peak tracking error of the rotor angular velocity for multiple cycles ω z1 and the rotor angular velocity valley tracking jitter difference ω z2 The average value of .

[0011] Get the rotor angular velocity peak tracking jitter ω z1 The method is to take the average of the two maximum sampling values ​​of the rotor angular velocity in the peak area as the peak maximum value, and the minimum sampling value between the sampling moments of the two maximum sampling values ​​as the peak minimum value; the rotor angular velocity peak tracking jitter error ω z1 It is the absolute value of the difference between the maximum value and the minimum value of the peak.

[0012] Get the rotor angular velocity valley tracking jitter error ω z2 The method is as follows: the average of the two minimum sampling values ​​of the rotor angular velocity in the valley area is taken as the minimum value of the valley, and the maximum sampling value between the two minimum sampling values ​​is taken as the maximum value of the valley; the rotor angular velocity valley tracking jitter error ω z2 It is the absolute value of the difference between the minimum value and the maximum value of the valley.

[0013] The state variables of the sliding mode speed controller are

[0014]

[0015] Where ω is the rotor angular velocity, ω * is the given rotor angular velocity; the sliding surface of the sliding mode speed controller is s y =c y y1+y z , c y is the sliding surface parameter, and c y >0; Sliding mode speed controller outputs load torque given value and q-axis torque current given value for

[0016]

[0017] Where J is the moment of inertia, p is the number of motor pole pairs, ψ f is the permanent magnet flux, B is the friction coefficient, is the observed value of the load torque; coefficient μ1, coefficient μ2 and coefficient μ3 are the exponential approach rate coefficients of the speed sliding mode control, and μ1>0, μ2>0, μ3>0.

[0018] The load torque observer is

[0019]

[0020] in, is the estimated value of the rotor angular velocity, g is the feedback gain of the load torque observer and g<0; k g is the sliding mode gain of the load torque observer and k g ≤-|e2 / J|, is the load torque observation error, T L is the load torque.

[0021] The load torque observer is based on the load torque given value output by the sliding mode speed controller. The feedback gain g is adjusted by:

[0022] Step 1: Calculation

[0023] Step 2: Judgment Is it greater than the torque change comparison threshold ε? When it is greater than the torque change comparison threshold ε, the feedback gain g is equal to g min ;when When the torque change comparison threshold ε is less than or equal to, the feedback gain g is equal to g max ;

[0024] Step 3: Load torque observer measures load torque T L Observe and obtain the load torque observation value

[0025] Step 4: The sliding mode speed controller performs control calculation and outputs the load torque given value.

[0026] Among them, ε>0; g max is the high value of feedback gain, g min is the low value of feedback gain, and g min <g max <0.

[0027] The parameters of the sliding mode speed controller and the load torque observer are uniformly optimized using the wolf pack algorithm, the method is:

[0028] Step 301, initialize the wolf pack; the initial position of each wolf in the wolf pack is M is the number of wolves in the wolf pack; the parameter vector to be optimized is θ z1 =[c y , μ1, μ2, μ3, G max , G min , ε, α]; g max With G max The relationship is g min With G min The relationship is k g The relationship with α is

[0029]

[0030] wherein α≥1; further, the value of α is selected within the range of 1 to 5;

[0031] Step 302, hunting competition; calculate the fitness value of each wolf in the wolf pack, select the R1 wolf with the best position as the candidate wolf; the R1 candidate wolf starts hunting search behavior, and each candidate wolf competes for the leader according to the size of the fitness value;

[0032] Step 303, calling for a charge; the other wolves other than the candidate wolf start a charge search behavior and charge towards the leader wolf; the fitness value of the new position of the i-th wolf is calculated, and when the new position searched by the i-th wolf is better than its current position, its position is changed, otherwise it remains unchanged; if the new position searched by the i-th wolf is better than the leader wolf's position, the i-th wolf is converted to the leader wolf and calls for a charge again;

[0033] Step 304, besiege the prey; under the call of the alpha wolf, the other wolves besiege the prey; calculate the fitness value of the new position of the i-th wolf, and when the new position searched by the i-th wolf during the siege is better than the current position, the position of the wolf is changed, otherwise it remains unchanged; if the new position searched by the i-th wolf during the siege is better than the alpha wolf's position, the i-th wolf is converted to the alpha wolf;

[0034] Step 305, judging the termination condition; if the number of loop iterations is reached, the optimization process is terminated and the position parameter of the leader wolf is the optimal parameter; otherwise, n=n+1 is set and the process goes to step 306; n is the current number of iterations;

[0035] Step 306, competition update; randomly generate R2 wolves to replace the wolf with the worst R2 fitness value in the wolf pack, and go to step 302.

[0036] The specific steps of safari competition are:

[0037] Step 3021, each candidate wolf randomly selects h1 directions according to the formula

[0038]

[0039] Search for parameters in each direction and then move forward one step and then back; calculate the fitness value after moving forward, select the minimum fitness value in all directions, if the minimum fitness value is less than the fitness value of the original position of the candidate wolf, then replace the original position of the candidate wolf with the position of the minimum fitness value. Where i = 1, 2, ..., R1; j = 1, 2, ..., 8; rand (-1, 1) is a random number uniformly distributed in [-11]; l = 1, 2, ..., h1; stepa is the hunting step length; z i =[z i1 z i2 … z i8 ] is the position of the i-th candidate wolf;

[0040] Step 3022, each candidate wolf repeats step 3021 h2 times;

[0041] Step 3023: After all R1 candidate wolves complete step 3022, the candidate wolf with the best position is selected as the leader.

[0042] Wolves start their raids according to the following pattern

[0043] z′ ij =z ij +rand(-1,1)·stepb·(z bj -z ij )

[0044] Carry out; wherein, i=1,2,…,M-R1; j=1,2,…,8; z′i =[z′ i1 z′ i2 … z′ i8 ] indicates the position of the i-th wolf’s search update; z i =[z i1 z i2 … z i8 ] represents the current position of the i-th wolf; z b =[z b1 z b2 … z b8 ] indicates the current position of the leader wolf; stepb is the running step length.

[0045] Wolves attack their prey in this way

[0046]

[0047] Carry out; wherein, i=1, 2, ..., M-1; j=1, 2, ..., 8; δ is a pre-established threshold, 0<δ<1; represents the current position of the i-th wolf, represents the siege update position of the i-th wolf; z b =[z b1 z b2 … z b8 ] indicates the current position of the leader wolf; stepc is the siege step length, according to the formula

[0048]

[0049] Calculate; where n max is the maximum number of iterations set; stepc max 、stepc min are the maximum siege step length and the minimum siege step length respectively; z jmax and z jmin are the maximum and minimum values ​​of the j-th dimension parameter value interval respectively.

[0050] The permanent magnet synchronous motor speed control method is implemented by a motor drive control system including a sliding mode speed controller, a load torque observer, a q-axis current controller, a d-axis current controller, a Clarke transformation module, a position and speed detection module, a Park transformation module, a Park inverse transformation module, an SVPWM module and a three-phase inverter.

[0051] The beneficial effect of the present invention is that the load torque observation value is feed-forward compensated to the given value of the current regulator, and the relevant influence caused by the load disturbance or the change of the system parameters can be offset without making a large adjustment to the given current part of the sliding mode speed controller output, and the jitter of the system is effectively weakened. The load torque observation adopts an algorithm that automatically adjusts the feedback gain according to the change of the load torque given value, avoiding the problem that the load torque observer selects a fixed small feedback gain to cause large torque observation fluctuations, and selects a fixed large feedback gain to cause a long convergence time. When the control parameters, model parameters, etc. of the system change or the load is disturbed, resulting in a change in the given sub-item part of the load torque given value or / and a change in the load torque observation value part, the observation error of the load torque can be quickly reduced, and the observation effect and the rapidity and accuracy of the motor speed control are improved. The feedback gain g is automatically adjusted when the load torque given value changes. When the load torque observation value has not changed significantly, but the given sub-item part of the load torque given value changes due to the change of the rotor angular velocity given value and / or the change of the rotor angular velocity actual value, or the given sub-item part of the load torque given value changes due to the change of the system model parameters, which will cause the load torque observation value to fluctuate greatly, the feedback gain g is adjusted in advance. When the load torque observation value actually produces an observation error, the response speed of the observer is accelerated, the observation error of the load torque observation value is quickly reduced, and the speed and accuracy of the motor speed control are further improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 This is a block diagram of Embodiment 1 of a wind turbine electric variable pitch motor drive control system;

[0053] Figure 2 This is a flow chart of Embodiment 1 of the feedback gain automatic adjustment method;

[0054] Figure 3 This is a flow chart of Embodiment 2 of the feedback gain automatic adjustment method;

[0055] Figure 4 This is a block diagram of Embodiment 2 of a wind turbine electric variable pitch motor drive control system;

[0056] Figure 5 Flow chart of Embodiment 3 of the feedback gain automatic adjustment method;

[0057] Figure 6 The given rotor angular velocity is a sinusoidal signal and load torque signal;

[0058] Figure 7 Schematic diagram of rotor angular velocity signal and rotor angular velocity response for one sine wave cycle;

[0059] Figure 8Schematic diagram of negative crossing of a given rotor angular velocity signal and a rotor angular velocity response signal. DETAILED DESCRIPTION

[0060] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0061] Figure 1 This is a block diagram of Example 1 of a wind turbine electric variable pitch motor drive control system. Figure 1 In the Clarke transformation module, the three-phase current i of the permanent magnet synchronous motor (PMSM) is input a 、i b and i c , output the current i in the two-phase stationary α-β axis coordinate system α 、i β ; The position sensor in the position and speed detection module detects the rotor position θ of the permanent magnet synchronous motor and converts it into the rotor angular velocity ω output; the Park conversion module inputs the current i α 、i β and the rotor position θ, the output current i in the rotating dq axis coordinate system d 、i q ;Sliding mode speed controller SMC input rotor given angular velocity ω * and rotor angular velocity ω, output load torque given value T L * and torque current given component i′ q ; Load torque observer inputs load torque given value T L * , rotor angular velocity ω and current i q , output torque current compensation component i″ q ; Torque current given component i′ q and torque current compensation component i ″ q After adding, it is used as the q-axis torque current given value i * q ; q-axis current PI controller input q-axis torque current given value i * q and current i d , output control voltage U in q-axis coordinate system q ; d-axis current PI controller input q-axis torque current given value i * d and current i d , output control voltage U in d-axis coordinate system d , d-axis torque current given value i * d =0; the control voltage U in the dq axis coordinate system is input to the Park inverse transformation module d , U q, output the control voltage U in the α-β axis coordinate system α , U β SVPWM module (i.e. space vector pulse width modulation module) input control voltage U α , U β , output pulse signal to the three-phase inverter, the three-phase inverter converts the DC voltage U dc Convert to three-phase AC power supply U a , U b , U c , thereby driving the permanent magnet synchronous motor to operate.

[0062] Ignoring the influence of core eddy current and hysteresis loss, the i d =0, the PMSM rotor magnetic field oriented control is established, and the mathematical model of PMSM in the dq axis rotating coordinate system is established. The voltage equation is:

[0063]

[0064] For the use of i d =0 control mode of salient pole PMSM vector control system, the electromagnetic torque equation is:

[0065]

[0066] The PMSM motion equation is:

[0067]

[0068] In formula (1), (2), and (3), u d 、u q are the voltages of the dq axes respectively; i d 、i q are the currents of d and q axes respectively; L d , L q are the inductance of d and q axes respectively; T e is the electromagnetic torque; T L is the load torque; R is the stator resistance; p is the number of motor poles; ω e is the rotor electrical angular velocity, i.e. angular frequency; ω is the rotor angular velocity, i.e. the motor rotor mechanical angular velocity; ψ f is the permanent magnet flux; J is the moment of inertia; B is the friction coefficient; t is time.

[0069] Let the motor's rotor angular velocity error e = ω * -ω,ω * is the given rotor angular velocity of the motor. The state variables of the embodiment 1 of the wind turbine electric variable pitch motor drive control system are defined as:

[0070]

[0071] From equations (2), (3) and (4), we can get:

[0072]

[0073] Simplify equation (5) and let D = 1.5pψ f / J, The state space equation of the system in Example 1 can be obtained as follows:

[0074]

[0075] Select the sliding surface function as:

[0076] s=cx1+x2 (7)

[0077] In formula (7), s is the sliding surface, c is the sliding surface parameter, and c>0. In formula (7), c is the coefficient of the rotor angular velocity error term. Its influence on the control effect is similar to the proportional coefficient in PID control. The value of c also takes into account the balance of the rotor angular velocity error and the rotor angular velocity error change rate. Usually, it is selected in the range of greater than 0 and less than 1000. For example, c=60. Derivative of formula (7) yields:

[0078]

[0079] The expression of the traditional exponential reaching law is:

[0080]

[0081] In formula (9), sgn() is a sign function, -k1sgn(s) is a constant speed approach term, -k2s is an exponential approach term, and the two coefficients k1 and k2 respectively determine the chattering and the motion quality of the approach process of the sliding surface, and k1 and k2 are both greater than 0. In order to improve the response speed of the system, the constant speed approach term is changed to a variable speed approach term based on the traditional exponential approach rate, and the improved approach law is:

[0082]

[0083] Where k1>0, k2>0, 1<k3<2, k4>0. When the motor's rotor angular velocity error |x1| is large, The variable speed approaching term has a larger approaching speed, which can accelerate the sliding mode approaching motion speed; when |x1| is small, The speed approaching term has a low approaching speed, which can reduce jitter. The value of k4 can refer to the steady-state jitter difference limit of the rotor angular velocity of the permanent magnet synchronous motor during stable operation. It is recommended to take the value in the range of 80% to 400% of the allowable steady-state jitter difference limit; for example, assuming that the allowable steady-state jitter difference limit of the permanent magnet synchronous motor rotor angular velocity is 5rad / s (radians / second), then k4 can take the value in the range of 4 to 20. The larger the k3, the greater the speed change, and k3 is generally taken in the range of 1.05 to 1.3. Generally, the values ​​of coefficients k1 and k2 are both less than 2000; the larger the coefficient k2, the faster the system state can approach the sliding mode; the coefficient k1 determines the speed to reach the switching surface, and the smaller the k1, the smaller the distance and jitter across the switching surface. k1 and k2 are the speed approaching term coefficient and the exponential approaching term coefficient, respectively. The value of changes around 1, therefore, the speed approach term coefficient k1 and the exponential approach term coefficient k2 in formula (10) can be adjusted according to the method of adjusting the medium speed approach term coefficient and the exponential approach term coefficient in the traditional exponential approach rate. k3 is the speed coefficient, and its size changes the speed of speed change; k4 is the migration coefficient, and its size changes the critical point of speed change.

[0084] Combining equations (8) and (10), the calculated q-axis given current is used as the torque current given component i′ q , we can get the load torque given value T output by the sliding mode speed controller L * and torque current given component i′ q for:

[0085]

[0086] Example 1 of wind turbine electric variable pitch motor drive control system The output of the sliding mode speed controller contains an integral term. Filtering the control quantity can weaken the system chattering and reduce the steady-state error of the system. The Lyapunov function is defined as:

[0087]

[0088] From formula (10) and formula (12), we can get:

[0089]

[0090] In formula (13), k1>0, k2>0, s·sgn(s)≥0, Therefore It shows that the system tracking error can converge to zero in a finite time and the system can operate stably.

[0091] Design of wind turbine electric variable pitch motor drive control system Example 1 The manual method of setting parameters c, k1, k2, k3, k4 when sliding mode speed controller is as follows: first determine the values ​​of k3 and k4; let the q-axis torque current given value i * q Only includes the input torque current given component i' q (that is, no load torque compensation control is performed), and then the sliding mode surface parameter c and the speed approach term coefficient k1 are adjusted from small to large in the sliding mode of the system until obvious jittering occurs in the system. On this basis, taking into account both the suppression of jittering and the system state convergence speed, the values ​​of the sliding mode surface parameter c and the speed approach term coefficient k1 are appropriately reduced; finally, while taking into account the suppression of sliding mode jittering, the value of the exponential approach term coefficient k2 is adjusted mainly based on the rapidity of the system arrival segment (for example, the motor start-up stage of the step response), and other parameter values ​​of the sliding mode speed controller are appropriately fine-tuned.

[0092] When designing the sliding mode speed controller of Example 1 of the wind turbine electric variable pitch motor drive control system, the controller parameters can also be adjusted using optimization algorithms such as particle swarm algorithm, wolf pack algorithm, genetic algorithm, etc. The specific method of using particle swarm algorithm to adjust the parameters c, k1, k2, k3, k4 is:

[0093] Establish a comprehensive evaluation of the wind turbine electric variable pitch motor drive control system Example 1 The objective function of the sliding mode speed controller for each performance index is:

[0094]

[0095] In formula (14), Q 11 The integral term in is the IAE criterion (error integration criterion) of the motor rotor angular velocity step response, e(t) is the instantaneous value of the rotor angular velocity error, t m is the transition time of the motor rotor angular velocity step response, t=0 is the starting time of the motor step response; Q 11 The second term γ m1 (1-sgn(e(t)+ω δ )) is the angular velocity overshoot penalty function, where γ m1 Take a sufficiently large ( 5 times or more of the reasonable value), ω δ is the rotor angular velocity overshoot limit (i.e. the maximum rotor angular velocity overshoot allowed by the system); when the overshoot of the motor rotor angular velocity step response does not exceed the rotor angular velocity overshoot limit ω δ When , the overshoot penalty function term is equal to 0, otherwise it is equal to γ m1 ;Q 12 is the steady-state jitter penalty function, ω Δis the rotor angular velocity steady-state jitter error limit; when the steady-state jitter error of the motor rotor angular velocity step response does not exceed the rotor angular velocity steady-state jitter error limit ω Δ When the steady-state jitter penalty function term is equal to 0, otherwise it is equal to γ m1 ; Q1 is the objective function value, that is, the fitness value of the particle swarm algorithm for parameter optimization of the sliding mode speed controller; the smaller the fitness value of the particle, the better the corresponding position. γ m1 When taking values, first estimate For example, if the rated speed of the motor is 1500r / min (corresponding to the rated rotor angular velocity of 157rad / s) and the starting time is about 0.2s, then The reasonable value of γ is no more than 40. m1 Take 5 times or more of 40, for example, take γ m1 =200. m2 Generally, the value is greater than or equal to 2. Its value determines the time interval for measuring the steady-state jitter error of the rotor angular velocity. For example, γ m2 When the value is equal to 6, then at 5 times the transition time t m The rotor angular velocity steady-state jitter error is measured in the interval. If other index factors need to be considered in the speed controller parameter optimization, for example, whether the transition process time is short enough, whether the steady-state error is small enough, etc., other objective functions other than equation (14) can be established.

[0096] The parameter vector to be optimized for the sliding mode speed controller is θ = [c, k1, k2, k3, k4], the search space dimension N of the particle swarm algorithm is 5, and the optimal position value of the constructed particle is the optimal parameter of the sliding mode speed controller. The specific steps of the particle swarm algorithm are:

[0097] Step 101, initialize the particle swarm. Assume that the initial position of the particle is Where M is the number of particles, which is usually selected between 20 and 150. The initial position is required to obey random distribution. The position of the i-th particle is expressed as The parameter vector to be optimized is θ = [c, k1, k2, k3, k4]; the position value interval is [m imin m imax ], the range interval can be given based on existing knowledge or experience, for example, the value interval of parameter c [m 1min m 1max ] is [0 1000], and the value range of parameter k1 is [m 2min m 2max ] is [0 2000], and the value range of parameter k2 is [m 3min m 3max ] is [0 2000], and the value range of parameter k3 is [m4min m 4max ] is [1.031.3], and the value range of parameter k4 is [m 5min m 5max ] is

[420] . Set the initial position m of each particle (0) As the initial optimal value m of each particle b (0) , calculate the fitness value of each particle according to formula (14) and save it as the optimal particle fitness value of each particle; compare the fitness values ​​of each particle to obtain the optimal solution m of the initial particle swarm g (0) And the optimal fitness value of the particle swarm is saved. Assume that the initial velocity of the particle is Also obeying the random distribution, the initial velocity of the i-th particle is expressed as The speed change extreme value of the parameter [v imin v imax ] is generally set to 5% to 20% of the parameter value range; for example, the value range of parameter k3 [m 4min m 4max ] is [1.03 1.3], and the interval range is 0.27, then the velocity change extreme value [v 4min v 4max ]According to 5%, the value is [-0.013 0.013], and according to 20%, the value is [-0.054 0.054].

[0098] Step 102, according to formula

[0099]

[0100] Update the speed and position of each particle; the speed change of each dimensional variable cannot exceed the corresponding speed change extreme value of each dimensional variable, and the updated position of each dimensional variable cannot exceed the corresponding value interval of each dimensional variable. In formula (15), n is the current number of iterations, v n and m n is the velocity vector and position of the particle; c0 is the inertia weight, ranging from 0 to 1.4. Adjusting its value can change the search range and search speed. Furthermore, adaptively reducing the c0 value as the number of iterations increases is conducive to achieving a balance between search capability and convergence speed; c1 and c2 are learning factors, ranging from 1 to 2, and it is recommended that both be equal to 2; is a random number ranging from 0 to 1; is the optimal solution (optimal position) found by the particle itself so far, It represents the optimal solution (optimal position) of the particle swarm of the entire population so far.

[0101] Step 103, calculate the fitness value of each particle according to formula (14).

[0102] Step 104, And the corresponding optimal particle fitness value is updated. And the corresponding particle swarm optimal fitness value is updated.

[0103] Step 105, determining whether the loop termination condition is satisfied, if so, the particle swarm algorithm is terminated, and the final particle swarm optimal solution is the optimal parameter of the sliding mode speed controller; otherwise, returning to step 102.

[0104] The loop termination condition is generally to reach the maximum iteration step limit or the optimal particle fitness value is less than a certain threshold. When the particle swarm algorithm is used to adjust the parameters c, k1, k2, k3, and k4, the maximum iteration step limit is used as the loop termination condition, and the maximum iteration step is usually selected between 100 and 2000. When setting the threshold condition of the particle swarm optimal fitness value at the same time, assuming that the rated speed of the motor is 1500r / min (corresponding to the rated rotor angular velocity of 157rad / s), and the startup time is required to be within 0.2s, the threshold of the particle swarm optimal fitness value can be set to 15.

[0105] According to formula (14), the particle fitness value of each particle is calculated. It is required to use each particle as the corresponding controller parameter in turn to control the motor start (or start in the simulation system) to obtain the motor rotor angular velocity step response e(t) required in formula (14). According to e(t), the transition process time t is determined. m , calculate the particle fitness value Q1.

[0106] According to the PMSM electromagnetic torque and motion equation, for a constant step load, it can be considered as a constant value within the change cycle, that is, Taking the rotor angular velocity and load torque as state variables, the PMSM state equation is:

[0107]

[0108] Based on equation (16), with load torque and rotor angular velocity as observation objects, load torque observer embodiment 1 is established as:

[0109]

[0110] In formula (17), is the observed value of the load torque, is the estimated value of the rotor angular velocity, g is the feedback gain of the load torque observer, k gis the sliding mode gain of the load torque observer embodiment 1, and the load torque observer embodiment 1 is a sliding mode observer. Compared with the load torque, the motor friction accounts for a small proportion, so let B = 0, ignoring the influence of friction, then the load torque observer embodiment 1 of formula (17) becomes:

[0111]

[0112] According to (16) and (18) when B=0, the error equation of the load torque observer embodiment 1 is obtained as follows:

[0113]

[0114] In formula (19), is the rotor angular velocity estimation error, is the load torque observation error, and the observer sliding surface is defined as According to the sliding mode reachability condition, the stability condition of the observer system in equation (18) is k g ≤-|e2 / J|, and g<0.

[0115] Based on formula (16), with the load torque and the motor rotor angular velocity as the observation objects, the load torque observer embodiment 2 can also be established as follows:

[0116]

[0117] Compared with the load torque, the motor friction accounts for a small proportion. Let B = 0 and ignore the influence of friction. Then the load torque observer embodiment 2 of equation (20) becomes:

[0118]

[0119] In formula (20) and (21), is the observed value of the load torque, is the estimated value of the rotor angular velocity, g is the feedback gain of the load torque observer, k W is the proportional gain of the load torque observer embodiment 2, and the load torque observer embodiment 2 is a state observer. According to equation (16) and equation (21) when B=0, the error equation of the load torque observer embodiment 2 is obtained as follows:

[0120]

[0121] In formula (22), is the rotor angular velocity estimation error, is the load torque observation error. The state observer of equation (21) is an autonomous linear system. W<0, and g<0, the observer is asymptotically stable. Formula (17) of the load torque observer embodiment 1 and formula (20) of the load torque observer embodiment 2 both take into account the friction factor of the motor. The addition of small friction damping will have an adverse effect on the rapidity of the system response, but can increase the stability based on formula (18) and formula (21), respectively.

[0122] When the observer embodiment 1 of equations (17) and (18) is selected, the sliding mode gain k g The setting method is to follow

[0123]

[0124] In formula (23), α≥1; generally, 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 the process of observing the load torque, k g The absolute value of |e2| is too small. When |e2| is large, the observer cannot enter the sliding mode state. g The absolute value of is large enough to ensure that the observer enters the sliding mode state, but the steady-state observation fluctuation of the load torque becomes larger; k g The value of changes with the load torque observation error, which can simultaneously increase the stability of the observer and reduce the steady-state observation fluctuation of the load torque.

[0125] When the observer embodiment 2 of equations (20) and (21) is selected, the proportional gain k W The setting method is to follow

[0126]

[0127] In formula (24), T N is the rated torque of the motor, β>0; generally, the β value is selected in the range of 1 to 20, for example, β=10. When β is selected to increase, the steady-state fluctuation of the load torque observation becomes larger, but the torque observation tracking overshoot becomes smaller; when β is selected to decrease, the steady-state fluctuation of the load torque observation becomes smaller, but the torque observation tracking overshoot becomes larger.

[0128] In the observers represented by equations (17), (18) or equations (20), (21), the value of the feedback gain g has a great influence on the load torque observation result. The larger the feedback gain g, the smaller the observed torque fluctuation, but the slower the observed torque identification speed; the smaller the feedback gain g, the faster the observed torque speed, but the greater the observed torque fluctuation. In consideration of this problem, in the traditional load torque observer, the observation speed and fluctuation of the load torque are comprehensively considered, and the feedback gain g is taken as a compromise value, but this will abandon the advantages of small fluctuation when the feedback gain is large and fast observation speed when the feedback gain is small.

[0129] The motor sliding mode speed control mainly suppresses the influence of parameter changes and external load disturbances on the system by increasing the amplitude of the discontinuous term in the controller, but the increase in amplitude will cause the inherent chattering of the sliding mode. In order to solve the contradiction between the chattering and anti-disturbance of the sliding mode control system, the observer is used to observe the load disturbance changes in real time, and the load torque observation value is feed-forward compensated to the current regulator to reduce the amplitude of the discontinuous term in the sliding mode control, weaken the given torque change caused by parameter changes, or the system chattering caused by load disturbances. In order to make full use of the advantages of the feedback gain g at high and low values, according to the load torque observation value and the load torque given value change at two adjacent moments, when the load torque given value changes little and the load torque observation value changes little, a larger feedback gain g is given to make the observation result less volatile and more stable; when the load torque given value changes greatly or the load torque observation value changes greatly, a smaller feedback gain g is given to speed up the observation speed. Finally, by adjusting the feedback gain g, a comprehensive result of fast observation speed, small fluctuation and stronger stability is obtained.

[0130] Load torque observer embodiment 1, or load torque observer embodiment 2 is used for Figure 1 In the embodiment 1 of the wind turbine electric pitch motor drive control system, the load torque observer is based on the load torque given value and load torque observation The feedback gain g is adjusted according to the change of the rotor angular velocity ω and the current i q Observe the load torque and obtain a new load torque observation value

[0131] Figure 2 The flow chart of the feedback gain automatic adjustment method embodiment 1 is used in the load torque observer embodiment 1 or the load torque observer embodiment 2. Figure 1 In Example 1 of the wind turbine electric variable pitch motor drive control system, the feedback gain is automatically adjusted. Figure 2 In the equation, ε1 is the given torque change comparison threshold, ε2 is the observed torque change comparison threshold, ΔT L * is the difference between the two most recent load torque given values, is the difference between the two most recent load torque observations. In a periodic control process of a motor drive control system, Figure 2 The feedback gain g shown in (b) is adjusted later than the load torque observation and the output calculation of the sliding mode speed controller, and is:

[0132] Step 1: The load torque observer calculates the load torque T according to the existing feedback gain g value. L Observe and obtain the load torque observation value The sliding mode speed controller performs control calculation to obtain the load torque given value At this time for for When the feedback gain g is adjusted next time during the periodic control process, becomes becomes

[0133] Step 2: Calculation

[0134] Step 3: Judgement Is it greater than the given torque change comparison threshold ε1? When it is greater than the given torque change comparison threshold ε1, the feedback gain g is equal to g min and exit; when When it is less than or equal to the given torque change comparison threshold ε1, go to step 4;

[0135] Step 4: Judgement Is it greater than the observed torque change comparison threshold ε2? When it is greater than the observed torque change comparison threshold ε2, the feedback gain g is equal to g min and exit; when When the observed torque change comparison threshold ε2 is less than or equal to, the feedback gain g is equal to g max and exit.

[0136] In the periodic control process of the motor speed, Figure 2 The feedback gain g shown in (a) is adjusted before the load torque observation and the output calculation of the sliding mode speed controller. The feedback gain g adjustment method changes the above step 1 to step 4, steps 2-4 to steps 1-3, and the exit in each step is changed to enter step 4, and ΔTL*=TL*k-1-TL*k-2.

[0137] When |ΔT L * |When it is greater than ε1, it indicates that the load torque given value T L * Due to the changes in system model parameters, rotor angular velocity set values, and actual rotor angular velocity values, the load torque observation value is in a state of large change. The load torque observation value either has a large fluctuation or will have a large fluctuation. The feedback gain g is selected to be equal to g min Rapid identification and observation of load torque; when |ΔT L * | is less than or equal to ε1, and When it is greater than ε2, it indicates that the load torque observation value fluctuates greatly, and the feedback gain g is selected to be equal to g min Rapid identification and observation of load torque; when |ΔT L * | is less than or equal to ε1, and When it is less than or equal to ε2, it indicates that the load torque given value changes little and the state load torque observation value fluctuates little, and the feedback gain g is selected to be equal to g max Perform torque identification and observation. Figure 2 In the equation, ε1>0, ε2>0. The specific values ​​of ε1 and ε2 are related to the sampling control period (cycle time) of the sliding mode speed controller, the permanent magnet synchronous motor and its load conditions. ε1 and ε2 are both greater than 0 and generally less than 5% of the rated torque. ε1 and ε2 can take the same value or different values. For example, if the rated torque is 22N·m, ε1=ε2=0.2N·m can be taken, or ε1=0.2N·m, ε2=0.25N·m can be taken. The value of the feedback gain g satisfies g min <g max <0, generally, g min ≥-5000. g min The value should be selected so that when the load torque changes suddenly, the torque observation tracking overshoot of the load torque observer output observation value is within the torque observation tracking overshoot limit; g max The value should be the change of the last two load torque observation values ​​when the load torque is constant and the load torque observer and sliding mode speed controller are both in steady state. Less than ε2; ​​for example, select the feedback gain g max =-0.5, g min =-10. Select g min and g max The specific method of calculating the value is, first, when the load torque is constant and the load torque observer and the sliding mode speed controller are both in steady state, let the feedback gain g start from a larger value. For example, let the feedback gain g gradually decrease from -0.01, the steady-state jitter difference of the load torque observation will gradually increase. When the steady-state jitter difference of the load torque observation reaches the steady-state jitter difference limit of the load torque observation, the feedback gain g value at this time is determined to be g max , keep the load torque unchanged and set the feedback gain g equal to g max , and perform F1 times continuously The value is measured and F1 is Maximum F2 in measurement The average value of the measured values ​​is used as the observed torque change comparison threshold ε2, and the given torque change comparison threshold ε1 is taken in the range of 0.5 to 1.5 times of the observed torque change comparison threshold ε2; then, when the load torque observer and the sliding mode speed controller are both in a steady state, the load torque is suddenly changed, and under the premise of ensuring that the torque observation tracking overshoot of the load torque observer output observation value is within the torque observation tracking overshoot limit, the tracking adjustment time of the load torque observer output observation value is as short as possible to adjust and determine g min value.

[0138] Figure 3 The flow chart of the feedback gain automatic adjustment method embodiment 2 is shown in the load torque observer embodiment 1 or the load torque observer embodiment 2. Figure 1 In Example 1 of the wind turbine electric variable pitch motor drive control system, the feedback gain is automatically adjusted. Figure 3 In the figure, ε is the torque change comparison threshold, ΔT L * is the difference between the two most recent load torque given values, is the difference between the two most recent load torque observations. In the periodic control process of the motor in a drive control system, Figure 3 The feedback gain g shown in (b) is adjusted later than the load torque observation and the output calculation of the sliding mode speed controller, and is:

[0139] Step I: The load torque observer calculates the load torque T according to the existing feedback gain g value. L Observe and obtain the load torque observation value The sliding mode speed controller performs control calculation to obtain At this time for for Until the next feedback gain g adjustment, the becomes becomes

[0140] Step II: Calculation

[0141] Step III: Judgment Is it greater than ε? When it is greater than ε, the feedback gain g is equal to g min ;when When it is less than or equal to ε, the feedback gain g is equal to g max ;

[0142] In the periodic control process of the motor speed, Figure 3The feedback gain g shown in (b) is adjusted prior to the load torque observation and the output calculation of the sliding mode speed controller. The feedback gain g adjustment method changes the above step I into step III, and steps II-III into steps I-II, and

[0143] When the sum of the changes in the load torque given value and the load torque observed value for the last two times When it is greater than ε, it indicates that the load torque observation value fluctuates greatly, or the load torque given value changes greatly due to changes in system model parameters, rotor angular velocity given value, and rotor angular velocity actual value, which will cause the load torque observation value to fluctuate greatly. The feedback gain g is selected to be equal to g min Rapid identification and observation of load torque; when When it is less than or equal to ε, it indicates that the load torque given value changes little and the state load torque observation value fluctuates little, and the feedback gain g is selected to be equal to g max Perform load torque identification and observation. Figure 3 In the equation, ε>0. The specific value of ε is related to the sampling control period (cycle time) of the sliding mode speed controller, the permanent magnet synchronous motor and its load conditions. ε is greater than 0 and generally less than 5% of the rated torque. For example, if the rated torque is 22N·m, ε can be taken as 0.2N·m or ε can be taken as 0.3N·m. The value of the feedback gain g satisfies g min <g max <0, generally, g min ≥-5000. g min The value should be selected so that when the load torque changes suddenly, the torque observation tracking overshoot of the load torque observer output observation value is within the torque observation tracking overshoot limit; g max The value should be the sum of the changes in the load torque given value and the load torque observed value for the last two times when the load torque remains unchanged and the load torque observer and the sliding mode speed controller are both in a steady state. Less than ε; for example, the feedback gain g is selected max =-0.5, g min =-10. Select g min and g max The specific method of calculating the value is, first, when the load torque is constant and the load torque observer and the sliding mode speed controller are both in steady state, let the feedback gain g start from a larger value. For example, let the feedback gain g gradually decrease from -0.01, the steady-state jitter difference of the load torque observation will gradually increase. When the steady-state jitter difference of the load torque observation reaches the steady-state jitter difference limit of the load torque observation, the feedback gain g value at this time is determined to be g max , keep the load torque unchanged and set the feedback gain g equal to g max , and continuously perform F1 times |ΔTL * |Value and The maximum F2 value among the F1 measurements is The average value of the sum is taken as the torque change comparison threshold ε; then, when the load torque observer and the sliding mode speed controller are both in steady state, the load torque is mutated. Under the premise of ensuring that the torque observation tracking overshoot of the load torque observer output observation value is within the torque observation tracking overshoot limit, the tracking adjustment time of the load torque observer output observation value is as short as possible to adjust and determine g min value. Figure 2 and Figure 3 In, g max is the high value of feedback gain, g min is the low value of feedback gain.

[0144] The observer parameters can also be adjusted using optimization algorithms such as particle swarm algorithm, wolf pack algorithm, genetic algorithm, etc. The specific method of using particle swarm algorithm to adjust the parameters of load torque observer embodiment 1 or load torque observer embodiment 2 in embodiment 1 of the wind turbine electric variable pitch motor drive control system is:

[0145] The objective function for comprehensively evaluating the performance indicators of the load torque observer in Example 1 of the wind turbine electric pitch motor drive control system is established as follows:

[0146]

[0147] In formula (25), Q 21 The integral term in is the IAE criterion for observing the step response of the motor load torque. is the load torque observation error, e2(t) is the instantaneous value of the load torque observation error, t p is the tracking adjustment time of the motor load torque observed step response, t = 0 is the load mutation moment of the load torque observed step response; Q 21 The second term γ p1 (1-sgn(e2(t)+T δ )) is the torque observation tracking overshoot penalty function, where γ p1 Take a large enough A positive number (5 times or more of the reasonable value), T δ is the torque observation tracking overshoot limit. When the torque observation tracking overshoot does not exceed the torque observation tracking overshoot limit T δ When the torque observation tracking overshoot penalty function term is equal to 0, otherwise it is equal to γ p1 .Q 22 In the first term, max(|e2(t)|) is the absolute value of the maximum torque observed steady-state jitter error, γ p2 is the fitness balance emphasis coefficient, which is a constant greater than 0; Q22 The second term γ p1 (1-sgn(e2(t)+T Δ )) is the torque observation steady-state jitter penalty function, T Δ is the load torque observation steady-state jitter difference limit; when the torque observation steady-state jitter difference does not exceed the load torque observation steady-state jitter difference limit T Δ When the torque observation steady-state jitter penalty function term is equal to 0, otherwise it is equal to γ p1 Q2 is the objective function value, that is, the fitness value of the load torque observer parameters using the particle swarm algorithm; the smaller the fitness value of the particle, the better the corresponding position. p1 When taking values, first estimate The reasonable value (upper limit) of the motor; for example, if the rated torque of the motor is 22N·m, the maximum torque observation tracking adjustment time t p At around 0.1s, the integral term of the IAE criterion in formula (25) does not exceed 2; the fitness balance emphasis coefficient γ p2 There are two functions. One is to balance the IAE criterion integral term and the absolute value term of the maximum torque observation steady-state jitter difference. For example, suppose the load torque observation steady-state jitter difference limit value T Δ is 1N·m, then γ p2 When the value is 2, the IAE criterion integral term and the absolute value term of the maximum torque observation steady-state jitter difference are relatively balanced, or the two play an equivalent role in the objective function value Q2. The reasonable value of γ is no more than 4. p1 Take a constant equal to 20 or greater than 20. Reduce γ p2 value, the weight of the IAE criterion integral term in the objective function value Q2 becomes larger, and it is more inclined to the rapidity of torque observation; increasing γ p2 value, the weight of the absolute value of the maximum torque observation steady-state jitter difference in the objective function value Q2 becomes larger, and it is more inclined to the steady-state performance of torque observation. p3 Generally, the value is greater than or equal to 2. Its value determines the time interval for measuring the steady-state jitter difference of load torque observation. For example, γ p3 When the value is equal to 6, the tracking adjustment time (i.e. transition process time) t p The steady-state jitter difference of load torque observation is measured in the range.

[0148] The specific steps of optimizing the load torque observer parameters in Example 1 of the wind turbine electric variable pitch motor drive control system using the particle swarm algorithm are:

[0149] Step 201, initialize the particle swarm. Assume that the initial position of the particle is Where M is the number of particles, which is generally selected between 20 and 150, and the initial position is required to obey random distribution. For different optimization objects, there are:

[0150] (1) For the load torque observer embodiment 1 in the wind turbine electric pitch motor drive control system embodiment 1, when the feedback gain automatic adjustment method embodiment 1 is used to automatically adjust the feedback gain, the parameter vector to be optimized is θ1=[G max , G min , ε1, ε2, α], at this time the search space dimension N of the particle swarm algorithm is equal to 5.

[0151] (2) For the load torque observer embodiment 1 in the wind turbine electric pitch motor drive control system embodiment 1, when the feedback gain automatic adjustment method embodiment 2 is used to automatically adjust the feedback gain, the parameter vector to be optimized is θ2=[G max , G min , ε, α], at this time the search space dimension N of the particle swarm algorithm is equal to 4.

[0152] (3) For the load torque observer embodiment 2 in the wind turbine electric pitch motor drive control system embodiment 1, when the feedback gain automatic adjustment method embodiment 1 is used to automatically adjust the feedback gain, the parameter vector to be optimized is θ3=[G max , G min , ε1, ε2, β], at this time the search space dimension N of the particle swarm algorithm is equal to 5.

[0153] (4) For the load torque observer embodiment 2 in the wind turbine electric pitch motor drive control system embodiment 1, when the feedback gain automatic adjustment method embodiment 2 is used to automatically adjust the feedback gain, the parameter vector to be optimized is θ4=[G max , G min , ε, β], at this time the search space dimension N of the particle swarm algorithm is equal to 4.

[0154] In each embodiment of step 201, after the optimal position of the particle is constructed, g max according to g min according to Calculated; sliding mode gain k g According to the parameter α, the proportional gain k is calculated according to formula (23): W It is calculated according to formula (24) based on parameter β.

[0155] In each embodiment of step 201, the position value interval of each parameter vector is [p imin p imax ], the range interval can be given based on existing knowledge or experience; for example, parameter G max The value interval [p 1min p 1max ] is [-4 4]; parameter Gmin The value interval [p 2min p 2max ] is [-4 4]; the value range of parameter ε1 is [p 3min p 3max ] and the value interval of parameter ε2[p 4mi np 4max ] are [0 0.05T N ], T N is the rated torque of the motor; the value range of parameter ε is [p 3min p 3max ] is [0 0.05T N ]; the value interval of parameter α[p 5min p 5max ](or [p 4min p 4max ]) is [1 5]; the value interval of parameter β is [p 5min p 5max ](or [p 4min p 4max ]) is [1 20].

[0156] In each embodiment of step 201, since the initial position of the particle is required to obey the random distribution and the spatial search algorithm of the particle swarm is a linear method, the feedback gain high value g is directly max and feedback gain low value g min When searching and optimizing in the interval [-5000 0], the absolute value of the feedback gain with a low value has a great influence on the working state of the observer. For example, in the interval [-10 0], the probability of particles entering is small, and it is difficult to optimize the feedback gain with a high value g. max and feedback gain low value g min The optimal position of the feedback gain g is not directly adjusted during the optimization process. max and feedback gain low value g min Instead of searching and optimizing, it is optimized in a similar way to gain. The parameter interval [-10 0] is expanded in the search interval, making it easier to obtain a high value of feedback gain g. max and feedback gain low value g min The optimal position; at this time, the feedback gain is high value g max and feedback gain low value g min The parameter range is [-10000 -0.0001]; the feedback gain high value g max Under normal circumstances, the interval [-0.0001 0] will not be selected, otherwise it will cause the observer to respond too slowly; in addition, the upper limit of the interval is -0.0001, which can also avoid high feedback gain values ​​g max The observer cannot work properly if the value is 0.

[0157] Step 202: Initialize the particle velocity and particle swarm optimal solution. Set the initial position p of each particle (0) As the initial optimal value p of each particle b (0) , calculate the fitness function value of each particle (i.e., the fitness value of the particle) according to formula (25) and save it as the optimal particle fitness value of each particle; compare the fitness values ​​of each particle to obtain the optimal solution p of the initial particle swarm g (0) And the optimal fitness value of the particle swarm is saved. Assume that the initial velocity of the particle is Also obeying the random distribution, the initial velocity of the i-th particle is expressed as The speed change extreme value of the parameter [u imin u imax ] is generally set to 5% to 20% of the parameter value range; for example, parameter G max The value interval [p 1min p 1max ] is [-4 4], the interval range is 8, then the first dimension variable of each particle (parameter G max )'s speed change extreme value [u 1min u 1max ]According to 5%, the value is [-0.4 0.4], and according to 20%, the value is [-1.6 1.6].

[0158] Step 203, according to formula

[0159]

[0160] Update the speed and position of each particle; the speed change of each dimensional variable cannot exceed the corresponding speed change extreme value of each dimensional variable, and the updated position of each dimensional variable cannot exceed the corresponding value interval of each dimensional variable. In formula (26), n is the current number of iterations, u n and p n is the velocity vector and position of the particle; c0 is the inertia weight, ranging from 0 to 1.4. Adjusting its value can change the search range and search speed. Furthermore, adaptively reducing the c0 value as the number of iterations increases is conducive to achieving a balance between search capability and convergence speed; c1 and c2 are learning factors, ranging from 1 to 2, and it is recommended that both be equal to 2; is a random number ranging from 0 to 1; is the optimal solution (optimal position) found by the particle itself so far, It represents the optimal solution (optimal position) of the particle swarm of the entire population so far.

[0161] Step 204, calculate the particle fitness value of each particle according to formula (25).

[0162] Step 205, And the corresponding optimal particle fitness value is updated. And the corresponding particle swarm optimal fitness value is updated.

[0163] Step 206 , judging whether the loop termination condition is satisfied, if yes, then the particle swarm algorithm is terminated, and the final particle swarm optimal solution is the optimal parameter of the load torque observer; otherwise, returning to step 203 .

[0164] The loop termination condition is generally when the maximum iteration step limit is reached or the optimal particle fitness value is less than a certain threshold. When the particle swarm algorithm is used to adjust the load torque observer parameters, the maximum iteration step limit is used as the loop termination condition, and the maximum iteration step is usually selected between 100 and 2000. When setting the threshold condition of the particle swarm optimal fitness value, it is necessary to refer to the motor rated torque and the expected torque observation tracking adjustment time t at the same time. p , Torque observation tracking overshoot limit T δ , load torque observation steady-state jitter limit T Δ , fitness balance emphasis coefficient γ p2 etc. to determine the threshold value; assuming the rated torque of the motor is 22N·m, T δ 2N·m, T Δ is 1N·m, γ p2 = 1.5, the desired torque observation tracking adjustment time t p If it is less than 0.04s, the threshold of the optimal fitness value of the particle swarm can be set at 1.8.

[0165] When the particle fitness value of each particle is calculated according to formula (25), the parameters of the sliding mode speed controller of Example 1 of the wind turbine electric variable pitch motor drive control system have been adjusted, and the load torque compensation control is implemented. It is required to convert each particle position into the corresponding load torque observer parameter in turn, and when the motor given angular velocity remains unchanged and the sliding mode speed controller is in a steady state, the load torque is suddenly changed to control the motor operation (or to run in the motor simulation system), and the motor load torque observation step response e2(t) required in formula (25) is obtained, and the transition process time t is determined based on e2(t) p , calculate the particle fitness value Q2.

[0166] Among the load torque observer parameters to be optimized, g max , g min There is a constraint g between min <g max , corresponding to the constraint G min >G max When initializing the particle position, or updating the particle position according to equation (26), first, the particle According to the value interval [p 1min p 1max ] to initialize or update the position, then the particle Based on the value range Initialize or update the position so that each particle in each iteration satisfies the constraint G. min >G max , that is, satisfying the constraint g min <g max .

[0167] In the periodic control process of the permanent magnet synchronous motor speed in the embodiment 1 of the wind turbine electric variable pitch motor drive control system, the load torque given value T calculated at the kth time (or the kth step) is L * T L * (k), load torque observation value Recorded as The k-1 moment is the moment of the periodic control process before the k moment, and the load torque given value T L * T L * (k-1), load torque observation value Recorded as The k-2 moment is the moment of the periodic control process before the k-1 moment, and the load torque given value T L * T L * (k-2), load torque observation value Recorded as The steps of controlling the speed of the permanent magnet synchronous motor in Embodiment 1 of the wind turbine electric variable pitch motor drive control system include:

[0168] Step 1: Detect the rotor position θ, rotor angular velocity ω and three-phase current i of the permanent magnet synchronous motor a 、i b and i c ;

[0169] Step 2: Based on the three-phase current i a 、i b and i c Clark transformation is performed on the permanent magnet synchronous motor to obtain the current i in the α-β axis coordinate system: α 、Current i β , according to the current i α 、Current i βPerform Park transformation on the rotor position θ to obtain the current i in the dq axis coordinate system d 、Current i q ;

[0170] Step 3: Feedback gain g is based on the load torque given value T L * and load torque observation to adjust for changes in

[0171] Step 4: Load torque observer is based on rotor angular velocity ω and current i q Observe the load torque and obtain a new load torque observation value and torque current compensation component i″ q ;

[0172] Step 5: The sliding mode speed controller is based on the input rotor given angular velocity ω * And the rotor angular velocity ω is used for control calculation to obtain the load torque given value and torque current given component i′ q ;

[0173] Step 6: Given component i' based on torque current q and torque current compensation component i″ q Calculate the q-axis torque current given value i q * ; The d-axis current controller is based on the d-axis torque current given value i d * and the current i in the d-axis coordinate system d The difference between them is used for PI control operation to obtain the control voltage U in the d-axis coordinate system d ; The q-axis current controller is based on the q-axis torque current given value i q * and the current i in the q-axis coordinate system q The difference between them is used for PI control operation to obtain the control voltage U in the q-axis coordinate system q ; Based on the control voltage U in the dq axis coordinate system d , U q Perform Park inverse transformation to obtain the control voltage U in the α-β axis coordinate system α , U β ; d-axis torque current given value i d * is equal to 0;

[0174] Step 7: Set the control voltage U in the α-β axis coordinate system α , U β As the input of the SVPWM module, the SVPWM module controls the three-phase inverter to generate a three-phase AC power supply Ua , U b , U c , thereby driving the permanent magnet synchronous motor to operate.

[0175] In the above steps, the order of step 3 and steps 4 and 5 can be interchanged, that is, steps 4 and 5 can be performed first, and then step 3. Figure 2 (a) and Figure 3 (a) in the above steps 3, 4, and 5 are followed in order to first automatically adjust the feedback gain, and then perform load torque observation and speed control. ΔT L * =T L * (k-1)-T L * (k-2). Figure 2 (b) and Figure 3 In (b), load torque observation and speed control are performed first, and then feedback gain is automatically adjusted. ΔT L * =T L * (k)-T L * (k-1); In the above steps, steps four and five are performed first, and then step three is performed.

[0176] Observe the load torque observation value Then, the observed value of the load torque Converted into torque current compensation component i″ q Feedforward compensation to the input of the q-axis current PI controller, the torque current given component i′ output by the sliding mode speed controller q The q-axis torque current given value i of the q-axis current PI controller is * q for:

[0177]

[0178] In formula (27), k q =1 / (1.5pψ f) is the torque observation compensation coefficient. Comparing equation (11) with equation (27), it can be obtained that when the load is disturbed or the system parameters change, the load torque compensation is not added in equation (11), and it is necessary to select larger k1 and k2 values ​​to provide a sufficiently large given current change to offset the related effects of the load disturbance or the change of system parameters, so as to ensure that the motor speed can be quickly constant; while equation (27) feeds forward the load torque observation value to the current regulator, and can provide a sufficiently large given current change to offset the related effects of the load disturbance or the change of system parameters when the load is disturbed or the system parameters change without the need for larger k1 and k2 values, thereby reducing the output pressure of the sliding mode speed controller and the amplitude of the discontinuous term, and effectively weakening the system jitter.

[0179] When the feedback gain value is fixed, the smaller the feedback gain g, the larger the oscillation amplitude of the load torque observation and the stronger the volatility; the larger the feedback gain g, the smaller the oscillation amplitude of the load torque observation and the higher the observation accuracy. The automatic gain adjustment algorithm solves the problem of large torque observation fluctuation caused by small feedback gain in the load torque observer and the problem of long convergence time of large feedback gain. The convergence time and fluctuation amplitude indicators are better than the compromise gain algorithm. It can quickly track the change value of the load torque and quickly reduce the observation error caused by the given change or parameter change. It has a small oscillation amplitude and high observation accuracy, achieving a good observation effect.

[0180] When the given speed is changed under the rated load torque, although the actual load torque does not change, it can be seen from the load torque observer constructed by equations (17), (18) or (20), (21) that when the rotor angular velocity ω changes, even if the load torque does not change, the observed torque observation value will change, resulting in observation error. When the given speed is changed under the rated load torque, the control and adjustment process of the sliding mode control system of the permanent magnet synchronous motor is that the sliding mode speed controller first changes the output load torque given value T according to the given speed. L * Change the torque current given value i * q changes, thus making the electromagnetic torque T of the permanent magnet synchronous motor e The feedback gain g is only based on the change of the load torque observation value. Automatic adjustment is performed. At this time, only when the rotor angular velocity ω changes, the load torque observation value After the change occurs, the feedback gain g is adjusted; the feedback gain g is also adjusted according to the change ΔT of the load torque given value. L * and the change in the observed value of load torque Automatic adjustment is performed. When the given speed changes, the load torque given value T L * Change, load torque observation value If the load torque has not changed, adjust the feedback gain g in advance. When an observation error actually occurs, the observer's response speed can be accelerated to eliminate (reduce) the load torque observation value as quickly as possible. The observation error is reduced, thereby improving the rapidity and accuracy of motor speed control. Similarly, when the system model parameters change, the load torque given value T L * Prior to load torque observation When the load torque is changed, the feedback gain g is also based on the change in the load torque given value ΔT L * and the change in the observed value of load torque Automatic adjustment can be performed to adjust the feedback gain g in advance, speed up the response speed of the observer, and eliminate (reduce) the load torque observation value as soon as possible The observation error can be reduced and the speed control of the motor can be further improved. Of course, if the load is disturbed and the observation value is When changes occur, When a major change occurs, Figure 2 , Figure 3 It can be seen that the feedback gain g can also be automatically adjusted to eliminate (reduce) the load torque observation value as quickly as possible. The observation error makes the load torque observation value Keep up with the load torque T as soon as possible L changes.

[0181] Furthermore, in Example 1 of the wind turbine electric variable pitch motor drive control system, after the parameters of the sliding mode speed controller and the load torque observer are adjusted manually or by optimization, the parameters of the sliding mode speed controller can be manually fine-tuned while realizing load torque compensation control, or the parameters of the sliding mode speed controller can be re-optimized using a particle swarm algorithm in accordance with steps 101-105.

[0182] Figure 4 A block diagram of Example 2 of a wind turbine electric variable pitch motor drive control system for realizing a permanent magnet synchronous motor sliding mode control method based on a load torque observer. Figure 4 Example 2 and Figure 1 The difference of Example 1 is that the speed sliding mode controller adopts the integral sliding mode control method, and the observation value of the load torque observer Sent to the speed sliding mode controller, the q-axis given current (torque current given component) output by the sliding mode speed controller already includes the load torque observation value Therefore, the q-axis given current (torque current given component) output by the speed sliding mode controller in Example 2 is directly used as the q-axis torque current given value, which can also play the role of load torque compensation; the load torque given value T output by the speed sliding mode controller L Δ The load torque observation value is also included in The load torque observer directly calculates the load torque given value T L Δ The feedback gain is automatically adjusted according to the change in the load torque given value and the change in the load torque observed value for the last two times. The same is done for automatic feedback gain adjustment.

[0183] The state variables of Embodiment 2 of the wind turbine electric variable pitch motor drive control system are defined as:

[0184]

[0185] Select the sliding surface function as:

[0186] s y =c y y1+y2 (29)

[0187] In formula (29), c y is the sliding surface parameter, and c y >0. In formula (29), c y is the coefficient of the integral term of the rotor angular velocity error. Its influence on the control effect is similar to the proportional coefficient in PID control. y The value of also takes into account the balance of the rotor angular velocity error integral term and the rotor angular velocity error term. Usually, c y Select in the range greater than 0 and less than 100. Derivative of formula (29) yields:

[0188]

[0189] On the basis of the traditional exponential reaching law, a new reaching law is adopted:

[0190]

[0191] μ1, μ2, and μ3 are the exponential approach rate coefficients of the speed sliding mode control, where μ1>0, μ2>0, and μ3>0. When the motor's rotor angular velocity error |y2| is large, the calculation term The variable speed approaching term has a larger approaching speed, which can accelerate the sliding mode approaching motion speed; when |y2| is smaller, The speed approaching term has a low approaching speed, which can reduce the vibration. The value of μ3 can refer to the steady-state jitter difference limit of the rotor angular velocity when the permanent magnet synchronous motor is running stably. It is recommended that the value be no greater than the reciprocal value of the square of the allowable steady-state jitter difference limit. Further, the value is within the range of 25% to 100% of the reciprocal value of the square of the allowable steady-state jitter difference limit; for example, assuming that the allowable steady-state jitter difference limit of the permanent magnet synchronous motor rotor angular velocity is 5 rad / s (radians / second), its reciprocal square value is equal to 0.04, and μ3 can be within the range of 0.01 to 0.04. μ3 is the speed coefficient, and its size changes the speed of the speed change. The e in formula (31) is the natural exponent, that is, the base of the natural logarithm.

[0192] Generally, the values ​​of coefficient μ1 and coefficient μ2 are both less than 5000. μ1 and μ2 are the speed approach term coefficient and the exponential approach term coefficient respectively. The value of varies around 1, therefore, the variable speed approach term coefficient μ1 and the exponential approach term coefficient μ2 in formula (31) can be adjusted according to the method of adjusting the medium speed approach term coefficient and the exponential approach term coefficient in the traditional exponential approach rate.

[0193] Combining equations (2), (3) and (31), we get:

[0194]

[0195] Combining equations (31) and (32), the calculated q-axis given current is directly used as the q-axis torque current given value i Δ q , the q-axis torque current given value i output by the controller can be obtained Δ q and load torque given value T L Δ for:

[0196]

[0197] In formula (33), the load torque value T L Use the output value of the load torque observer Instead, define the Lyapunov function as:

[0198]

[0199] From equation (30) and equation (31), we can get:

[0200]

[0201] In formula (35), μ1>0, μ2>0, s y ·sgn(s y )≥0, so It shows that the tracking error of the observer can converge to zero in a finite time and the system can operate stably.

[0202] When designing a sliding mode speed controller, the tuning parameter c y The artificial method of determining μ1, μ2, and μ3 is to first determine the value of μ3; let the output value of the load torque observer in equation (33) be (i.e., no load torque compensation control is performed), and then the sliding surface parameter c is adjusted from small to large in the sliding mode of the system. y and the value of the speed approach term coefficient μ1 until the system shows obvious chattering. On this basis, the sliding surface parameter c is appropriately reduced while taking into account both the suppression of chattering and the convergence speed of the system state. y and the value of the speed approach term coefficient μ1; finally, while taking into account the suppression of sliding mode chattering, the value of the exponential approach term coefficient μ2 is adjusted mainly according to the rapidity of the system arrival segment (for example, the motor startup phase of the step response), and other parameter values ​​of the sliding mode speed controller are appropriately fine-tuned.

[0203] Figure 4 The load torque observer in the wind turbine electric pitch motor drive control system embodiment 2 still adopts the aforementioned load torque observer embodiment 1, or adopts the aforementioned load torque observer embodiment 2; at this time, the load torque observer outputs a load torque given value according to the sliding mode speed controller The feedback gain g is adjusted according to the change of the rotor angular velocity ω and the current i q Load torque T L Observe and obtain the load torque observation value

[0204] Figure 5 The flow chart of the feedback gain automatic adjustment method embodiment 3 is used in the load torque observer embodiment 1 or the load torque observer embodiment 2. Figure 4 In Example 2 of the wind turbine electric variable pitch motor drive control system, the feedback gain is automatically adjusted. Figure 5 In the equation, ε is the torque change comparison threshold, ε>0; g max is the high value of feedback gain, g min is the low value of feedback gain, and g min <g max <0;ΔT L Δ is the difference between the two most recent load torque given values. In the periodic control process of a motor speed, when the feedback gain g is adjusted before the calculation of the sliding mode speed controller output, Figure 5 The feedback gain g shown in (a) is based on The specific method for adjustment and load torque observation is:

[0205] Step 1: Calculation

[0206] Step 2: Judgment Is it greater than the torque change comparison threshold ε? When it is greater than the torque change comparison threshold ε, the feedback gain g is equal to g min ;when When the torque change comparison threshold ε is less than or equal to, the feedback gain g is equal to g max ;

[0207] Step 3: Load torque observer measures load torque T L Observe and obtain the load torque observation value

[0208] Step 4: The sliding mode speed controller performs control calculation and outputs the load torque given value. At this time for When the next motor speed periodic control process begins, the load torque setting value output this time becomes

[0209] Figure 5 The feedback gain g adjustment method shown in (b) in the above-mentioned embodiment changes the above-mentioned steps (iii) to (iv) into steps (i) to (ii), and steps (i) to (ii) into steps (iii) to (iv).

[0210] Because T L Δ The output items include the given sub-items that are in a changing state due to changes in system model parameters, rotor angular velocity given values, and rotor angular velocity actual values. Also includes the compensation sub-item load torque observation value item When the change in the last two load torque reference values ​​|ΔT L Δ When | is greater than ε, it indicates that the load torque observation value fluctuates greatly, or the system model parameters change, the rotor angular velocity set value change, and the rotor angular velocity actual value change, which makes T L Δ The given sub-item in the equation changes greatly and will cause the load torque observation value to fluctuate greatly. The feedback gain g is selected to be equal to g min Perform torque identification and observation; when |ΔT L Δ When | is less than or equal to ε, it indicates that the load torque observation value fluctuates little and the factors that will cause the load torque observation value to fluctuate greatly (i.e., T L Δ The given sub-item in the formula (g) changes little, and the feedback gain g is selected to be equal to g max Perform torque identification and observation. Figure 5The specific value of ε is related to the sampling control period (cycle time) of the sliding mode speed controller, the permanent magnet synchronous motor and its load conditions. ε is greater than 0 and generally less than 5% of the rated torque. For example, if the rated torque is 22N·m, ε can be taken as 0.2N·m or ε can be taken as 0.3N·m. The value of the feedback gain g satisfies g min <g max <0, generally, g min ≥-5000. g min The value should be selected so that when the load torque changes suddenly, the torque observation tracking overshoot of the load torque observer output observation value is within the torque observation tracking overshoot limit; g max The value should be the difference between the last two load torque given values ​​|ΔT when the load torque remains unchanged and the load torque observer and sliding mode speed controller are both in steady state. L Δ | is less than ε; for example, the feedback gain g is selected max =-0.5, g min =-10. Select g min and g max The specific method of calculating the value is, first, when the load torque is constant and the load torque observer and the sliding mode speed controller are both in steady state, let the feedback gain g start from a larger value. For example, let the feedback gain g gradually decrease from -0.01, the steady-state jitter difference of the load torque observation will gradually increase. When the steady-state jitter difference of the load torque observation increases to the steady-state jitter difference limit of the load torque observation, the feedback gain g value at this time is determined to be g max , keep the load torque unchanged and set the feedback gain g equal to g max , and continuously perform F1 times |ΔT L Δ | value, and take the maximum F2 |ΔT among the F1 measurements L Δ |The average value of the measured value is used as the torque change comparison threshold ε; then, when the load torque observer and the sliding mode speed controller are both in a steady state, the load torque is suddenly changed. Under the premise of ensuring that the torque observation tracking overshoot of the load torque observer output observation value is within the torque observation tracking overshoot limit, the tracking adjustment time of the load torque observer output observation value is as short as possible to adjust and determine g min value.

[0211] In each of the above, select g min , g max In the specific methods of determining the value and comparison threshold, the parameters in the sliding mode speed controller have been adjusted and are implemented under the condition of load torque compensation control; when the parameter value is determined by manual method, it is recommended that F1 is an integer greater than or equal to 20, and F2 is an integer greater than or equal to 5 and less than or equal to 0.5F1.

[0212] In the wind turbine electric variable pitch motor drive control system embodiment 2, the parameters of the sliding mode speed controller and the load torque observer can also be adjusted by using optimization algorithms such as particle swarm algorithm, wolf pack algorithm, genetic algorithm, etc., while realizing load torque compensation control. The specific method of using the wolf pack algorithm to adjust the parameters in the sliding mode speed controller and the load torque observer embodiment 1 (or the load torque observer embodiment 2) of the wind turbine electric variable pitch motor drive control system embodiment 2 is:

[0213] System motor given rotor angular velocity ω * is a sine wave signal, such as Figure 6 As shown in (a) in the figure. Given the rotor angular velocity ω * The period of the sine wave signal is T * , the maximum rotor angular velocity Not greater than the rated angular velocity of the motor, the minimum angular velocity of the rotor Not less than 10% of the rated angular velocity of the motor, the maximum angular velocity of the rotor Minimum rotor angular velocity The difference between them is not less than 50% of the rated angular velocity of the motor. Assume that when the wind turbine electric variable pitch motor drive control system embodiment 2 is started with rated load torque, the starting rise time to the rated speed is T r , then T * In 5~10T r The system motor is given a rotor angular velocity ω according to the sine wave. * When the signal is running, follow Figure 6 (b) Load torque T L , that is, the system motor is given a rotor angular velocity ω according to the sine wave * When the signal starts to run, the load torque is the load torque low value T Lmin ; After the motor enters the stable following state of the rotor angular velocity, the load torque changes from the low value T Lmin Mutation increases to high values ​​of T Lmax ; The load torque is maintained at a high value T Lmax Run time After that, from the high value T Lmax Mutation reduced to low value T Lmin ; Among them, the load torque high value T Lmax Not greater than the rated load torque T of the motor N , load torque low value T Lmin Not less than 10% of the rated load torque of the motor, the load torque high value T Lmax With low load torque T Lmin The difference between them shall not be less than 50% of the rated load torque of the motor; 2~5T *The system motor is given a rotor angular velocity ω according to the sine wave * The signal runs for at least 2 cycles T * Then the rotor angular velocity enters a stable following state.

[0214] Figure 7 In order to keep the rotor angular velocity of the motor stable, one sine wave period T * Schematic diagram of the given rotor angular velocity signal and rotor angular velocity response, where curve ① is the given rotor angular velocity ω * , curve ② is the rotor angular velocity response ω, and there is jitter. In order to clearly distinguish ω * and ω, Figure 7 Given the rotor angular velocity ω * The vertical axis coordinate ratio is different from that of the rotor angular velocity response ω. z is the jitter amplitude of the rotor angular velocity ω, and the tracking delay time τ is the delay time between the rotor angular velocity ω and the given rotor angular velocity ω*. Figure 7 In, ω o is the midline value of the sinusoidal signal of the given rotor angular velocity, ω z1 is the rotor angular velocity peak tracking jitter error when the rotor angular velocity response ω is at the maximum value state (peak state), τ1 is the rotor angular velocity negative crossing tracking delay time, ω z2 is the rotor angular velocity valley tracking jitter error when the rotor angular velocity response ω is in the minimum state (valley state), and τ2 is the rotor angular velocity positive crossing tracking delay time. Continuous measurement includes load torque from low value T Lmin Mutation increases to high values ​​of T Lmax To load torque from high value T Lmax Mutation reduced to low value T Lmin Multiple cycles (e.g., 10 or more T * The peak tracking error of the rotor angular velocity (period) is ω z1 、Rotor angular velocity valley tracking jitter error ω z2 , negative crossing tracking delay time τ1, positive crossing tracking delay time τ2; rotor angular velocity tracking jitter ω z For the multiple cycles ω z1 and ω z2 The tracking delay time τ is the average value of the multiple cycles τ1 and τ2. A sinusoidal signal is used as the motor's given rotor angular velocity signal. The load torque mutation is controlled when the motor is running. The performance index is constructed by the rotor angular velocity tracking jitter error and the rotor angular velocity tracking delay time to simultaneously optimize the parameters of the sliding mode speed controller and the load torque observer. The influence of the load torque observer's performance is unified to the rotor angular velocity performance index, which simplifies the parameter optimization process and can also improve the rotor angular velocity performance index to the greatest extent.

[0215] Get the rotor angular velocity peak tracking jitter ω z1 The method is: take the average of the two maximum sampling values ​​of the rotor angular velocity in the peak area as the peak maximum value, and the minimum sampling value between the two maximum sampling values ​​as the peak minimum value; the rotor angular velocity peak tracking jitter error ω z1 is the absolute value of the difference between the peak maximum value and the peak minimum value. Get the rotor angular velocity valley tracking jitter error ω z2 The method is as follows: the average of the two minimum sampling values ​​of the rotor angular velocity in the valley area is taken as the minimum value of the valley, and the maximum sampling value between the two minimum sampling values ​​is taken as the maximum value of the valley; the rotor angular velocity valley tracking jitter error ω z2 It is the absolute value of the difference between the minimum value and the maximum value of the valley.

[0216] The method for obtaining the negative crossing tracking delay time τ1 and the positive crossing tracking delay time τ2 is as follows: the center point of the sampling moment before the first negative crossing of the rotor angular velocity and the sampling moment after the last negative crossing of the rotor angular velocity is taken as the negative crossing moment of the rotor angular velocity; the absolute value of the time difference between the negative crossing moment of the rotor angular velocity and the negative crossing moment of the rotor angular velocity is given as the negative crossing tracking delay time τ1. The center point of the sampling moment before the first positive crossing of the rotor angular velocity and the sampling moment after the last positive crossing of the rotor angular velocity is taken as the positive crossing moment of the rotor angular velocity; the absolute value of the time difference between the positive crossing moment of the rotor angular velocity and the positive crossing moment of the rotor angular velocity is given as the positive crossing tracking delay time τ2.

[0217] Let’s take the calculation of negative crossing tracking delay time τ1 as an example to further illustrate: Figure 8 The negative crossing diagram of the given rotor angular velocity signal and the rotor angular velocity response signal is shown in FIG. The negative crossing refers to the given rotor angular velocity sinusoidal signal and the rotor angular velocity response signal crossing the midline value line of the given rotor angular velocity sinusoidal signal from large to small. Figure 8 In, ω o The horizontal line is the midline value line of the sinusoidal signal of the given rotor angular velocity; τ a is the negative crossing moment of the given rotor angular velocity. Due to the jitter, during one negative crossing of the rotor angular velocity, its actual sampling value forms multiple negative crossings; Figure 8 In the figure, points ① to ⑩ are the sampling points of the rotor angular velocity response, among which the sampling values ​​of points ①, ②, ③, ⑤, and ⑦ are greater than the midline value ω o , the sampling values ​​of points ④, ⑥, ⑧, ⑨, and ⑩ are less than the midline value ω o During the negative crossing of the rotor angular velocity, the sampling time of point ③ is the sampling time τ before the first negative crossing. b1 The sampling time of point ⑧ is the next sampling time τ after the last negative crossing b2 , τ b is τb1 With τ b2 A special case is that there is only one negative crossing in a certain rotor angular velocity negative crossing process, then this negative crossing is the first negative crossing and the last negative crossing. The given rotor angular velocity negative crossing moment and the given rotor angular velocity positive crossing moment can both be calculated by the given rotor angular velocity ω* sinusoidal signal. The meaning of the positive crossing tracking delay time is similar to that of the negative crossing tracking delay time.

[0218] The objective function for comprehensively evaluating the performance index of the sliding mode speed controller and the load torque observer of Example 2 of the wind turbine electric variable pitch motor drive control system is established as follows:

[0219] Q3=ω z +γ z τ (36)

[0220] In formula (36), Q3 is the objective function value, that is, the adaptive value of the sliding mode speed controller and the load torque observer of the embodiment 2 of the wind turbine electric pitch motor drive control system using the wolf pack algorithm for parameter optimization, which is composed of the rotor angular velocity tracking jitter error term and the tracking delay time term; γ z is the fitness balance adjustment coefficient, which is a constant greater than 0; let the system's rotor angular velocity steady-state jitter limit ω Δ is 1.5rad / s, the motor startup rise time T r 0.1s, because the tracking delay time τ is not greater than the start-up rise time T under normal working conditions r , so γ z When the value is 15, the tracking delay time term and the rotor angular velocity tracking jitter difference term are relatively balanced; or in other words, the tracking delay time term and the rotor angular velocity tracking jitter difference term play the same role; reducing γ z value, the weight of the rotor angular velocity tracking error term in the objective function value Q3 becomes larger, and the system performance is more inclined to the stability of speed control; increasing γ z value, the weight of the tracking delay time term in the objective function value Q3 becomes larger, and the system performance is more inclined to the rapidity of speed control.

[0221] The specific steps of optimizing the parameters of the sliding mode speed controller and the load torque observer in Example 2 of the wind turbine electric variable pitch motor drive control system by the wolf pack algorithm are:

[0222] Step 301, initialize the wolf pack. Assume that the initial position of each wolf in the wolf pack is Where M is the number of wolves in the wolf pack, which is generally selected between 20 and 150, and the initial position is required to obey random distribution. For different optimization objects, there are:

[0223] (1) For the sliding mode speed controller and load torque observer in Embodiment 1 of the wind turbine electric pitch motor drive control system Embodiment 2, when the feedback gain is automatically adjusted using the feedback gain automatic adjustment method Embodiment 3, the parameter vector to be optimized is θ z1 =[c y , μ1, μ2, μ3, G max , G min , ε, α], the algorithm's search space dimension N is equal to 8; the position of the ith individual wolf (the ith wolf) is expressed as Corresponding to the parameter vector θ to be optimized z1 .

[0224] (2) For the sliding mode speed controller and load torque observer in Embodiment 2 of the wind turbine electric pitch motor drive control system, when the feedback gain automatic adjustment method Embodiment 3 is used to automatically adjust the feedback gain, the parameter vector to be optimized is θ z2 =[c y , μ1, μ2, μ3, G max , G min , ε, β], the algorithm's search space dimension N is equal to 8; the position of the ith individual wolf (the ith wolf) is expressed as Corresponding to the parameter vector θ to be optimized z2 .

[0225] In each embodiment of step 301, the position of the wolf leader finally constructed is the optimal position, and its parameters are the optimal parameters, g max according to g min according to Calculated; sliding mode gain k g According to the parameter α, the proportional gain k is calculated according to formula (23): W It is calculated according to formula (24) based on parameter β.

[0226] In each embodiment of step 301, the position value interval is [z imin z imax ], the range interval can be given based on existing knowledge or experience, for example, the value interval of parameter cy [z 1min z 1max ] is [0 100]; the value range of parameter μ1 is [z 2min z 2max ] is [0 5000]; the value range of parameter μ2 is]z 3min z 3max ] is [0 5000]; the value range of parameter μ3 is [z 4min z 4max ] is [0.25 / ω Δ 21 / ω Δ 2 ],ω Δ is the rotor angular velocity steady-state jitter limit; parameter G max The value interval [z 5min z 5max ] is [-4 4]; parameter G min The value interval [z 6min z 6max ] is [-4 4]; the value range of parameter ε is [z 7min z 7max ] is [0 0.05T N ], T N is the rated torque of the motor; the value range of parameter α is]z 8min z 8max ] is [1 5], or the value interval of parameter β is [z 8min z 8max ] is [1 20].

[0227] Step 302, hunting competition. The fitness value of each wolf in the wolf pack is calculated according to formula (36). The smaller the fitness value, the better the position of the wolf. The R1 wolf with the best position is selected as the candidate wolf. The R1 candidate wolves start hunting search behavior according to formula (37). Each candidate wolf competes for the leader according to the size of the fitness value. Specifically,

[0228] Step 3021, each candidate wolf randomly selects h1 directions, searches for parameters along each direction according to formula (37), moves forward one step, and then moves back; calculates the fitness value after moving forward according to formula (36), selects the minimum fitness value in all directions, and if the minimum fitness value is smaller than the fitness value of the original position of the candidate wolf, replaces the original position of the candidate wolf with the position where the minimum fitness value is located;

[0229] Step 3022, each candidate wolf repeats step 3021 h2 times;

[0230] Step 3023: After all R1 candidate wolves complete step 3022, the candidate wolf with the best position is selected as the leader.

[0231]

[0232] In formula (37), i = 1, 2, ..., R1; j = 1, 2, ..., 8; rand (-1, 1) is a random number uniformly distributed in the range of [-1 1]; l = 1, 2, ..., h1; stepa is the hunting step length, and the recommended value range of stepa is [0.1 0.9]; z i =[z i1 z i2 … z i8] is the position of the ith candidate wolf. R1 is recommended to be a fixed value or a random value in the interval [0.1M 0.25M]; the number of directions h1 is recommended to be in the interval [3 8], and the number of repetitions h2 is recommended to be in the interval [3 10].

[0233] Step 303, call for a charge. The other wolves other than the candidate wolf start a charge search behavior according to formula (38), and charge towards the leader wolf. The i-th wolf calculates the fitness value of the new position according to formula (36). When the new position searched by the i-th wolf is better than its current position, its position is changed, otherwise it remains unchanged; if the new position searched by the i-th wolf is better than the leader wolf's position, the i-th wolf is converted to the leader wolf and re-initiates a charge.

[0234] z′ ij =z ij +rand(-1,1)·stepb·(z bj -z ij ) (38)

[0235] In formula (38), i = 1, 2, ..., M-R1; j = 1, 2, ..., 8; z′ i =[z′ i1 z′ i2 … z′ i8 ] indicates the position of the i-th wolf’s search update; z i =[z i1 z i2 … z i8 ] represents the current position of the i-th wolf; z b =[z b1 z b2 … z b8 ] indicates the current position of the leader wolf; stepb is the running step length, and the recommended value range of stepb is [1.3 2.5].

[0236] Step 304, siege the prey. At the call of the alpha wolf, the other wolves siege the prey according to formula (39). The i-th wolf calculates the fitness value of the new position according to formula (36). When the new position searched by the i-th wolf during the siege is better than the current position, the position of the wolf is changed, otherwise it remains unchanged; if the new position searched by the i-th wolf during the siege is better than the alpha wolf's position, the i-th wolf is converted to the alpha wolf.

[0237]

[0238] In formula (39), i = 1, 2, ..., M-1; j = 1, 2, ..., 8; represents the current position of the i-th wolf (i.e., the position after n iterations), represents the siege update position of the i-th wolf; zb =[z b1 z b2 …z b8 ] represents the current position of the leader wolf; δ is a pre-set threshold, and the recommended value range of δ is [0.1 0.4]; stepc is the siege step length, which is calculated according to formula (40).

[0239]

[0240] In formula (40), n is the current number of iterations, n max is the maximum number of iterations set; stepc max 、stepc min The maximum and minimum siege steps are set respectively. min The value range of stepc is [0.3 1.3]. max The value of stepc min 5 to 100 times of. jmax and z jmin are the maximum and minimum values ​​of the j-th dimension parameter value interval respectively. The e in formula (40) is the natural exponent, that is, the base of the natural logarithm.

[0241] Step 305, judging the termination condition. If the number of loop iterations reaches or the fitness value of the leader wolf is less than a certain threshold, the optimization process is terminated and the leader wolf position parameter is the optimal parameter; otherwise, n=n+1 is set and the process goes to step 306.

[0242] Step 306, competitive update. According to the principle of survival of the fittest, randomly generate R2 wolves to replace the wolf with the worst R2 fitness value in the wolf pack, and compete to update the wolf pack, and then go to step 302. R2 is recommended to take a fixed value or a random value in the interval [0.05M 0.15M].

[0243] In the above steps, when the new positions of individual wolves are randomly generated, or when individual wolves search for new positions, the variables of each dimension of the new position of each wolf cannot exceed the corresponding value range of the variable. max , g min There is a constraint g between min <g max , corresponding to the constraint G min >G max When a new position of an individual wolf is randomly generated, or when an individual wolf searches for a new position, first, the individual wolf z i The parameter z in i5 According to the value interval [z 5min z 5max ] Randomly generate a position or update the position, then the individual wolf z i The parameter zi6 According to the value interval [z i5 z 6max ] Randomly generate positions or update positions so that individual wolves i Satisfy the constraint G min >G max , that is, satisfying the constraint g min <g max .

[0244] In step 305, the termination condition adopts the maximum number of iterations limit method, and the maximum number of iterations n max It is recommended to take a fixed value in the interval [20 500]. When setting the condition that the head wolf adaptation value is less than a certain threshold, the threshold condition needs to comprehensively consider the rapidity and stability of speed control. For example, the rotor angular velocity steady-state jitter limit ω Δ is 1.5rad / s, the motor startup rise time T r is 0.1s, γ z When the value is 15, the threshold of the termination condition can be selected as 1.5.

[0245] In the above steps, when calculating the fitness value of the new position according to formula (36), it is required to convert the individual wolf positions into corresponding sliding mode speed controller parameters and load torque observer parameters in turn to control the motor operation (or operation in the simulation system). * is a sine wave signal, load torque T L When the rotor angular velocity is stable and follows the state mutation, the speed response of the motor is obtained, and the rotor angular velocity tracking jitter error ω is determined based on the speed response. z and tracking delay time τ, and then calculate the adaptation value according to formula (36).

[0246] In the periodic control process of the permanent magnet synchronous motor speed in the wind turbine electric pitch motor drive control system embodiment 2, the load torque given value calculated at the kth time (or the kth step) is Recorded as Load torque observation value Recorded as The k-1 moment is the moment of the periodic control process before the k moment, and the load torque is given by Recorded as The k-2 moment is the moment of the periodic control process before the k-1 moment, and the load torque given value Recorded as according to Figure 5 When the feedback gain g is adjusted in (a), the periodic control process of the permanent magnet synchronous motor speed includes the following steps:

[0247] Step 1: Detect the rotor position θ, rotor angular velocity ω and three-phase current i of the permanent magnet synchronous motor a 、i b and i c ;

[0248] Step 2: Based on the three-phase current i a 、i b and i c Clark transformation is performed on the permanent magnet synchronous motor to obtain the current i in the α-β axis coordinate system: α 、i β , according to the current i α 、i β Perform Park transformation on the rotor position θ to obtain the current i in the dq axis coordinate system d 、i q ;

[0249] Step 3: Feedback gain g is based on the given value of load torque to adjust for changes in

[0250] Step 4: The load torque observer observes the load torque and obtains the load torque observation value

[0251] Step 5: The sliding mode speed controller performs control calculation to obtain the load torque given value and q-axis torque current given value

[0252] Step 6: The d-axis current controller is based on the d-axis torque current given value i d * and the current i in the d-axis coordinate system d The difference between them is used for PI control operation to obtain the control voltage U in the d-axis coordinate system d ; The q-axis current controller is based on the q-axis torque current given value and the current i in the q-axis coordinate system q The difference between them is used for PI control operation to obtain the control voltage U in the q-axis coordinate system q ; Based on the control voltage U in the dq axis coordinate system d , U q Perform Park inverse transformation to obtain the control voltage U in the α-β axis coordinate system α , U β ;

[0253] Step 7: Set the control voltage U in the α-β axis coordinate system α , U β As the input of the SVPWM module, the SVPWM module controls the three-phase inverter to generate a three-phase AC power supply U a , Ub , U c , thereby driving the permanent magnet synchronous motor to operate.

[0254] according to Figure 5 When the feedback gain g is adjusted in (b), in the steps of the above control process, the contents of steps 4 and 5 are performed first, and the contents of step 3 are performed later.

[0255] The output term of the sliding mode speed controller in formula (33) includes the compensation sub-item load torque observation value This is equivalent to feeding the load torque observation value forward to the current regulator in equation (27). When the load is disturbed or the system parameters change, it can provide a sufficiently large given current change to offset the related effects of the load disturbance or the change in system parameters, effectively weakening the system jitter. The feedback gain g is based on the change in the load torque given value ΔT L Δ Automatic adjustment is performed. When the given speed changes, the load torque given value T L Δ Change, load torque observation value If the load torque has not changed, adjust the feedback gain g in advance. When an observation error actually occurs, the observer response speed can be accelerated to eliminate (reduce) the load torque observation value as quickly as possible. The observation error can improve the speed and accuracy of motor speed control. Similarly, when the system parameters change, the load torque given value T L Δ Prior to load torque observation When a change occurs, the feedback gain g is based on the change in the load torque given value ΔT L Δ Automatic adjustment can be performed to adjust the feedback gain g in advance, speed up the observer response speed, and eliminate (reduce) the load torque observation value as soon as possible The observation error can be reduced and the speed control of the motor can be further improved. When a change occurs, ΔT L Δ The feedback gain g will also change according to the change in the load torque given value ΔT L Δ Automatic adjustment can eliminate (reduce) the load torque observation value as quickly as possible The observation error makes the load torque observation value Keep up with the load torque T as soon as possible L changes.

[0256] The speed sliding mode controller adopts the integral sliding mode control method of the wind turbine electric variable pitch motor drive control system embodiment 2, and its feedback gain is based on the load torque given value T L Δ The algorithm for automatically adjusting the change in the load torque is used in the embodiment 1 of the wind turbine electric variable pitch motor drive control system. The feedback gain is based on the sum of the change in the load torque given value and the change in the load torque observation value for the last two times. The same algorithm is used for automatic adjustment, which avoids the problem that the load torque observer selects a fixed small feedback gain, which leads to large torque observation fluctuations, and selects a fixed large feedback gain, which leads to a long convergence time. It can be used when the control parameters, model parameters, etc. of the system change or the load is disturbed, resulting in the load torque given value T L Δ When the load torque changes (including the given item changes and / or the compensation item changes), the observation error of the load torque is quickly reduced, which improves the observation effect and the speed and accuracy of the motor speed control. The feedback gain g changes according to the load torque given value T L Δ Automatic adjustment can be performed at the load torque observation value If there is no significant change, but the given sub-item of the load torque given value changes due to the change of the rotor angular velocity given value or / and the actual value of the rotor angular velocity, or the given sub-item of the load torque given value changes due to the change of the system model parameters, which will cause the load torque observation value to fluctuate greatly, adjust the feedback gain g in advance. When the load torque observation value When an observation error actually occurs, speed up the observer's response speed and quickly reduce the load torque observation value. The observation error can be reduced and the speed and accuracy of motor speed control can be further improved.

[0257] In the above embodiments, the torque observation tracking overshoot limit is usually 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, etc. The load torque suddenly changes from one constant value to another constant value. The time from the start of the sudden change to the time when the load torque observer outputs the observed value stably entering the load torque observation steady-state jitter difference limit range is the torque observation transition process, and the tracking adjustment time refers to the transition process time. The load torque observation steady-state jitter error refers to the error between the instantaneous value of the observed torque and the load torque when the load torque is constant and the load torque observer is in a steady state. This error includes the observation error caused by the jitter of the sliding mode observer itself and the observation error caused by interference reasons other than load fluctuations, or the observation error caused by the rotor angular velocity jitter of the state observer and the observation error caused by interference reasons other than load fluctuations; the load torque observation steady-state jitter error limit is the maximum absolute value of the load torque observation steady-state jitter error allowed by the load torque observer; the load torque observation steady-state jitter error limit is usually the same as the maximum value of the load torque observation steady-state error allowed by the system; the load torque observation steady-state jitter error limit is usually 1% to 5% of the rated torque of the motor. Specifically, the load torque observation steady-state jitter error limit is 1% of the rated torque, or 2% of the rated torque, or 5% of the rated torque, etc. The torque observation tracking overshoot refers to the load torque suddenly changing from one fixed value to another fixed value, and the observed value output by the load torque observer exceeds the maximum deviation value of the load torque after the sudden change. When the steady-state jitter error of the load torque observation is within the vicinity of the steady-state jitter error limit of the load torque observation, for example, within the range of 95% to 105%, or within the range of 98% to 102%, it is considered that the steady-state jitter error of the load torque observation increases to the steady-state jitter error limit of the load torque observation. The sliding mode speed controller is in steady state, which means that the sliding mode speed controller is stably in the sliding mode; the rotor angular velocity steady-state jitter error refers to the difference between the instantaneous value and the steady-state value of the motor rotor angular velocity in steady state, and the rotor angular velocity steady-state jitter error limit is the maximum absolute value of the rotor angular velocity steady-state jitter error allowed by the system. In the load torque observer, the sliding mode observer of Example 1 is in steady state, which means that the sliding mode observer is stably in the sliding mode; the state observer of Example 2 is in steady state, which means the working state of the state observer after the torque observation transition process. The steady-state jitter error of the rotor angular velocity refers to the difference between the instantaneous value and the steady-state value of the motor rotor angular velocity in steady state. The steady-state jitter error limit of the rotor angular velocity is the maximum absolute value of the steady-state jitter error of the rotor angular velocity allowed by the system; the steady-state jitter error limit of the rotor angular velocity is usually the same as the maximum steady-state error of the rotor angular velocity allowed by the system.

[0258] In the present invention, the pitch motor of the wind turbine electric pitch motor drive control system is a permanent magnet synchronous motor, and the wind turbine electric pitch motor drive control system is a permanent magnet synchronous motor speed control system. The permanent magnet synchronous motor speed control system and the permanent magnet synchronous motor speed (optimization) control method provided by the present invention can be used for other permanent magnet synchronous motor application occasions in addition to being used for wind turbine electric pitch motor drive control.

[0259] In addition to the technical features described in the specification, other technologies involved in the present invention are conventional technologies mastered by those skilled in the art. For example, the q-axis current controller and the d-axis current controller use PI controllers for control and controller parameter selection, the sliding mode speed controller control parameter selection, the position and speed detection module uses a rotary transformer or a photoelectric encoder to detect the rotation angle and rotation speed of the permanent magnet synchronous motor rotor, and the Clarke transformation module, Park transformation module, Park inverse transformation module and SVPWM module, three-phase inverter transformation method and application method, etc., are all conventional technologies mastered by those skilled in the art.

Claims

1. A speed optimization control method for a permanent magnet synchronous motor. The sliding mode speed controller adopts an integral sliding mode control method. The load torque observer is based on the rotor angular velocity ω and the q-axis current i q Observe the load torque and obtain the load torque observation value Load torque observation value output by the load torque observer is sent to a sliding mode speed controller; it is characterized by: The q-axis given current output by the sliding mode speed controller includes the load torque observation value The q-axis given current output by the speed sliding mode controller is directly used as the q-axis torque current given value of the q-axis current PI controller, which plays the role of load torque compensation. The parameters of the sliding mode speed controller and the load torque observer are uniformly optimized using the wolf pack algorithm, and the objective function is: Q3=ω z +g z t; Among them, ω z is the rotor angular velocity tracking error, τ is the tracking delay time, γ z is the fitness balance adjustment coefficient; The given rotor angular velocity ω* is a sinusoidal signal; the rotor angular velocity tracking error ω z is the jitter amplitude of the rotor angular velocity ω, and the tracking delay time τ is the delay time between the rotor angular velocity ω and the given rotor angular velocity ω*; The method for obtaining the tracking delay time τ is: the tracking delay time τ is an average value of the negative crossing tracking delay time τ1 and the positive crossing tracking delay time τ2 of multiple cycles; The method for obtaining the negative crossing tracking delay time τ1 is to take the center point of the sampling moment before the first negative crossing of the rotor angular velocity and the sampling moment after the last negative crossing of the rotor angular velocity as the rotor angular velocity negative crossing moment; the absolute value of the time difference between the rotor angular velocity negative crossing moment and the rotor angular velocity negative crossing moment is given as the negative crossing tracking delay time τ1; The method for obtaining the forward crossing tracking delay time τ2 is to take the center point of the sampling moment before the first forward crossing of the rotor angular velocity and the sampling moment after the last forward crossing of the rotor angular velocity as the rotor angular velocity forward crossing moment; the absolute value of the time difference between the rotor angular velocity forward crossing moment and the rotor angular velocity forward crossing moment is given as the forward crossing tracking delay time τ2; Get the rotor angular velocity tracking error ω z The method is: the rotor angular velocity tracking jitter difference ω z is the peak tracking error of the rotor angular velocity for multiple cycles ω z1 and the rotor angular velocity valley tracking jitter difference ω z2 The average value of Get the rotor angular velocity peak tracking jitter ω z1 The method is to take the average of the two maximum sampling values ​​of the rotor angular velocity in the peak area as the peak maximum value, and the minimum sampling value between the sampling moments of the two maximum sampling values ​​as the peak minimum value; the rotor angular velocity peak tracking jitter error ω z1 is the absolute value of the difference between the maximum value and the minimum value of the peak; Get the rotor angular velocity valley tracking jitter error ω z2 The method is as follows: the average of the two minimum sampling values ​​of the rotor angular velocity in the valley area is taken as the minimum value of the valley, and the maximum sampling value between the two minimum sampling values ​​is taken as the maximum value of the valley; the rotor angular velocity valley tracking jitter error ω z2 It is the absolute value of the difference between the minimum value and the maximum value of the valley.

2. The method for optimizing the speed control of a permanent magnet synchronous motor according to claim 1, characterized in that: The state variables of the sliding mode speed controller are Where ω is the rotor angular velocity, ω * is the given rotor angular velocity; the sliding surface of the sliding mode speed controller is s y =c y y1+y2,c y is the sliding surface parameter, and c y >0; sliding mode speed controller outputs load torque given value and q-axis torque current given value for Where J is the moment of inertia, p is the number of motor pole pairs, ψ f is the permanent magnet flux, B is the friction coefficient, is the observed value of the load torque; coefficient μ1, coefficient μ2 and coefficient μ3 are the exponential approach rate coefficients of the speed sliding mode control, and μ1>0, μ2>0, μ3>0; The load torque observer is in, is the estimated value of the rotor angular velocity, g is the feedback gain of the load torque observer and g<0; k g is the sliding mode gain of the load torque observer and k g ≤-|e2 / J|, is the load torque observation error, T L is the load torque; The load torque observer is based on the load torque given value output by the sliding mode speed controller. The feedback gain g is adjusted according to the change of 3. The method for optimizing the speed control of a permanent magnet synchronous motor according to claim 2, characterized in that: The load torque observer is based on the load torque given value output by the sliding mode speed controller. The method to adjust the feedback gain g is: Step 1: Calculation Step 2: Judgement Is it greater than the torque change comparison threshold ε? When it is greater than the torque change comparison threshold ε, the feedback gain g is equal to g min ;when When the torque change comparison threshold ε is less than or equal to, the feedback gain g is equal to g max ; Step 3: Load torque observer measures load torque T L Observe and obtain the load torque observation value Step 4: The sliding mode speed controller performs control calculation and outputs the load torque given value. Among them, ε>0; g max is the high value of feedback gain, g min is the low value of feedback gain, and g min <g max <0.

4. The method for optimizing the speed control of a permanent magnet synchronous motor according to claim 3, characterized in that: When the parameters of the sliding mode speed controller and the load torque observer are optimized and tuned uniformly using the wolf pack algorithm, the parameter vector to be optimized is θ z1 =[c y , μ1, μ2, μ3, G max , G min , ε, α]; g max With G max The relationship is g min With G min The relationship is k g The relationship with α is Among them, α≥1.

5. The method for optimizing the speed control of a permanent magnet synchronous motor according to any one of claims 1 to 4, characterized in that: Detect the rotor position θ and three-phase current i of the permanent magnet synchronous motor a 、i b and i c ; Based on the three-phase current i a 、i b and i c Clark transformation is performed on the permanent magnet synchronous motor to obtain the current i in the α-β axis coordinate system: α 、Current i β , according to the current i α 、Current i β Perform Park transformation on the rotor position θ to obtain the current i in the dq axis coordinate system d 、Current i q .

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