PMSM voltage prediction control system and method based on composite disturbance compensation

Abstract

The invention belongs to the technical field of permanent magnet synchronous motor control, and particularly relates to a PMSM voltage prediction control system and method based on composite disturbance compensation. In the method, a linear expansion state observer LESO of a speed outer ring controller and a dq axis disturbance observer of a current outer ring controller are designed independently; the problem of current loop coupling under a traditional double-loop architecture can be avoided; a linear expansion state observer LESO is improved by using a variable exponential reaching law, buffeting in a sliding stage can be effectively reduced, the speed of a system moving towards a sliding mode surface is increased, and the buffeting problem is reduced when the system is closer to the sliding mode surface; selecting dq-axis current estimation errors sd and sq to construct a dq-axis disturbance observer which converges in finite time, estimating dq-axis given voltage deviation, designing a dq-axis disturbance correction controller to correct the estimated dq-axis given voltage deviation, and compensating the corrected dq-axis given voltage deviation to a model to obtain an optimal voltage vector of the motor. Therefore, the observation precision is ensured.

Description

Technical Field

[0001] The present invention belongs to the technical field of permanent magnet synchronous motor control, and particularly relates to a PMSM voltage prediction control system and method based on composite disturbance compensation. Background Technique

[0002] Permanent magnet synchronous motors (PMSMs) are widely used in electric vehicles, rail transit, ship propulsion, industrial servo and other fields due to their simple structure, small axial dimension, large torque and fast response speed. At present, the research on motor lightweight design and robust control strategies is a hot topic for PMSMs, and a large number of key technologies still need to be overcome. In terms of control strategies, traditional PMSM control methods adopt a cascade double closed-loop control architecture based on PI regulators. The speed outer loop provides current commands, and the current inner loop outputs the target voltage vector. Since a PMSM is a strongly coupled nonlinear system, traditional methods rely only on the static decoupling of PI regulators, and generally have problems such as poor dynamic decoupling ability of current feedforward and cumbersome parameter tuning of PI regulators, making it difficult to achieve precise control. Summary of the Invention

[0003] The purpose of the present invention is to address the above problems existing in the prior art, and provide a PMSM voltage prediction control system and method based on composite disturbance compensation, which has strong dynamic decoupling ability, good dynamic and steady-state performance, strong parameter robustness, and can achieve precise control of the system.

[0004] To achieve the above objectives, the technical solution of the present invention is as follows:

[0005] In the first aspect, the present invention provides a PMSM voltage prediction control system based on composite disturbance compensation. The PMSM voltage prediction control system includes a speed loop control module, a current loop control module, a voltage disturbance compensation module, and a permanent magnet synchronous motor control sampling module;

[0006] The permanent magnet synchronous motor control sampling module is used to collect the motor mechanical angular velocity ω m of the permanent magnet synchronous motor during rotation, the d-axis current i d and the q-axis current i q , the d-axis voltage deviation f d and the q-axis voltage deviation f d ;

[0007] The speed loop control module is used to calculate the q-axis current command value i * after composite disturbance compensation through a linear active disturbance rejection controller LADRC according to the motor mechanical angular velocity command value ωx m and the motor mechanical angular velocity ω q * ;

[0008] The current loop control module is used to calculate the estimated value of the d-axis voltage deviation d and the estimated value of the q-axis voltage deviation q d d q * q

[0009] q * q * q * d * q * d * q * LTD m *

[0010] d * q * LTD m *

[0011] The linear active disturbance rejection controller LADRC includes a linear tracking differentiator LTD, a linear extended state observer LESO, and a linear state error feedback controller LSEF;

[0012] The mathematical model of the linear tracking differentiator LTD is shown in Equation (5):

[0013]

[0014] In the above formula, e LTD is the tracking error; z1 is the tracking signal of ω m * m is the change rate of z1; ω m * is the rotor mechanical angular velocity command value; r is the speed adjustable factor;

[0015] The mathematical model of the linear extended state observer LESO is designed based on the variable exponential sliding mode reaching law, including Equations (13) to (17):

[0016]

[0017] In the above formula, the variable x1 = ω m ; x2 = f w ; u = i q * , are the estimated values of ω m and f w respectively; Take the variable y1 represents the controller output, are respectively the rate of change of e; Both β1 and β2 are adjustable gain parameters;

[0018]

[0019] In the above formula, f w is the composite disturbance, b0 is the standard value of the characteristic gain coefficient, J0, ψ f0 are the per-unit values of the moment of inertia and the rotor flux linkage respectively; i q * is the q-axis current command value; B0 is the standard value of the viscous friction coefficient; T L is the load torque; P n is the number of pole pairs; ψ f is the rotor flux linkage; J is the moment of inertia; ω m is the rotor mechanical angular velocity; e fw is the disturbance estimation error, e fw = x s1 - f w ; C(e) is the control function,

[0020] Take the linear sliding surface s = ce + ef w , where ce is the sliding surface function, and the variable exponent sliding mode reaching law is shown in Equation (15):

[0021]

[0022] In the above formula, ε, ρ, σ, and δ are all the gains of the variable exponent sliding mode reaching law; ε > 0, δ > 0, ρ > 0, σ > 0;

[0023] Design the control function c(e) as shown in Equation (16);

[0024]

[0025] In the above formula, F is the parameter in the control function c(e); h l and h mare respectively the upper and lower bounds; is f w to obtain the rate of change;

[0026]

[0027] The mathematical model of the linear state error feedback controller LSEF is shown in Equation (18):

[0028]

[0029] In the above formula, u0 is the intermediate variable of the linear state error feedback controller LSEF.

[0030] The mathematical model of the dq-axis disturbance observer is designed based on the reaching law of the terminal saturation function, including Equations (19) to (40):

[0031] Define the dq-axis voltage equations of the PMSM when there is an electrical parameter mismatch as shown in Equations (19) and (20):

[0032]

[0033] In the above formula, ω e is the rotor electrical angular velocity; f d , f d are respectively the d-axis and q-axis voltage deviations when there is an electrical parameter mismatch of the motor; F d , F q are respectively the rates of change of f d , f q , |F d | ≤ D, |F q | ≤ Q, D and Q are respectively the maximum values of F d , F q ; ΔL is the stator inductance perturbation; ΔR is the stator resistance perturbation; Δψ f is the stator flux linkage perturbation; i d is the d-axis current component; R is the stator resistance; L is the stator inductance; u d , u q are respectively the d-axis voltage and the q-axis voltage;

[0034] Define the dq-axis voltage observation equations as shown in (21) and Equation (22):

[0035]

[0036] In the above formula, are respectively the estimated values of the d-axis and q-axis currents; are respectively the estimated values of F d , F q ; I dsmo , Iqsmo are the d-axis and q-axis disturbance observer functions; G d and G q are the gains of the d-axis and q-axis disturbance observers; U dsmc and U qsmc are the d-axis and q-axis disturbance correction controller functions;

[0037] Define the d-axis and q-axis current estimation errors s d and s q as well as the d-axis and q-axis disturbance estimation errors e fd and e fq as shown in Equation (23):

[0038]

[0039] Combining Equations (19) - (23), the dq-axis sliding mode error equations are obtained as shown in Equations (24) - (25):

[0040]

[0041] Select s d and s q as the sliding mode surface functions, and construct an approach law based on the terminal saturation function as shown in Equation (26) to make the system approach the sliding mode surface in a finite time T:

[0042]

[0043] In the above formula, k, α, and ε are the gains of the approach law based on the terminal saturation function; k > α > 0, ε > 0;

[0044] Substitute the approach law based on the terminal saturation function into Equations (24) and (25) respectively to obtain Equation (31):

[0045]

[0046] Define the upper bounds of e fd and e fq as E fd and E fq respectively, that is, |e fd | ≤ E fd ; |e fq | ≤ E fq , and obtain the dq-axis disturbance observer functions as shown in Equation (32);

[0047]

[0048] After the system enters the sliding mode surface, rewrite Equations (24) and (25) as Equation (34):

[0049]

[0050] Introduce the sliding surface where c1 is the gain of the sliding surface s2, and the d-axis disturbance correction controller function shown in Equation (35) is designed as follows;

[0051] U dsmc = (G d - c1)e fd - Ks2 - Dsgn(s2) (35);

[0052] Introduce the sliding surface The q-axis disturbance correction controller function shown in Equation (37) is designed as follows;

[0053] U qsmc = (G q - c1)e fq - Ks3 - Qsgn(s3) (37);

[0054] Discretize Equations (19) and (20) to obtain Equation (38):

[0055]

[0056] In the above equation, T S is the system control period; i d (i), i q (i) are the stator currents of the d-axis and q-axis at time i respectively; i d (i + 1), i q (i + 1) are the predicted currents with a one-beat delay respectively; u d (i), u q (i) are the stator voltages of the d-axis and q-axis at time i respectively; are the estimated values of the voltage disturbances of the d-axis and q-axis at time i respectively; I dsom (i), I qsom (i) are the disturbance observers of the d-axis and q-axis at time i respectively;

[0057] To make the predicted currents i d (i + 2), i q (i + 2) reach the predicted values within the next control period T S , that is, i d (i + 2) = i d * , i q (i + 2) = i q * , perform a one-beat delay on Equation (38) to obtain Equation (39):

[0058]

[0059] Rewrite Equation (39) as Equation (40), and obtain the optimal u for the next control period through Equation (40). d * and u q * :

[0060]

[0061] The mathematical model of the permanent magnet synchronous motor control sampling module is shown in Equations (1)-(4):

[0062]

[0063] In the above formula, T e is the electromagnetic torque; P n is the number of pole pairs; ψ f is the rotor magnetic flux; i d and i q are the d-axis and q-axis components of the stator current respectively; R is the stator resistance; L is the stator inductance; ω m is the rotor mechanical angular velocity; u d and u q are the d-axis and q-axis components of the stator voltage respectively; T L is the load torque; J is the moment of inertia; B is the viscous friction coefficient.

[0064] Second, the present invention provides a PMSM voltage predictive control method based on composite disturbance compensation. The PMSM voltage predictive control method includes:

[0065] Collect the motor mechanical angular velocity ω m of the permanent magnet synchronous motor during rotation, the d-axis current i d and the q-axis current i q , the d-axis voltage deviation f d and the q-axis voltage deviation f d ;

[0066] According to the motor mechanical angular velocity command value ω m * and the motor mechanical angular velocity ω m , calculate the q-axis current command value i q * after composite disturbance compensation through the linear active disturbance rejection controller LADRC;

[0067] According to the d-axis current i d and the q-axis current i q , the d-axis voltage deviation f d and the q-axis voltage deviation f d , calculate the estimated value of the d-axis voltage deviation and the estimated value of the q-axis voltage deviation

[0068] According to the q-axis current command value i after composite disturbance compensation q * and the estimated value of the d-axis voltage deviation The estimated value of the q-axis voltage deviation Calculate the d-axis voltage command value u through the dq-axis disturbance observer d * and the q-axis voltage command value u q * and correct the d-axis voltage command value u through the dq-axis disturbance correction controller d * and the q-axis voltage command value u q * ;

[0069] According to the corrected d-axis voltage command value u d * and the q-axis voltage command value u q * Control the rotation of the permanent magnet synchronous motor

[0070] The linear active disturbance rejection controller LADRC includes a linear tracking differentiator LTD, a linear extended state observer LESO, and a linear state error feedback controller LSEF;

[0071] The mathematical model of the linear tracking differentiator LTD is shown in Equation (5); the mathematical model of the linear extended state observer LESO is designed based on the variable exponential sliding mode reaching law and includes Equations (13) to (17); the mathematical model of the linear state error feedback controller LSEF is shown in Equation (18). For Equation (5), Equations (13) to (17), and Equation (18), please refer to the PMSM voltage prediction control system based on composite disturbance compensation, which will not be elaborated here.

[0072] The mathematical model of the dq-axis disturbance observer is designed based on the reaching law of the terminal saturation function and includes Equations (19) to (40). For Equations (19) to (40), please refer to the PMSM voltage prediction control system based on composite disturbance compensation, which will not be elaborated here.

[0073] The control process of controlling the rotation of the permanent magnet synchronous motor according to the corrected d-axis voltage command value u d * and the q-axis voltage command value u q * is simplified to the mathematical model shown in Equations (1) to (4). For Equations (1) to (4), please refer to the PMSM voltage prediction control system based on composite disturbance compensation, which will not be elaborated here.

[0074] In a third aspect, the present invention provides a PMSM voltage predictive control device based on composite disturbance compensation. The PMSM voltage predictive control device includes a memory and a processor. The memory is used to store computer program code and transmit the computer program code to the processor. The processor is used to execute the foregoing PMSM voltage predictive control method according to the instructions in the computer program code.

[0075] In a fourth aspect, the present invention provides a computer-readable storage medium with a computer program stored thereon. When the computer program is executed by a processor, the foregoing PMSM voltage predictive control method is implemented.

[0076] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0077] 1. For the PMSM voltage predictive control method based on composite disturbance compensation of the present invention, the linear extended state observer LESO in the speed outer loop controller and the dq-axis disturbance observer in the current outer loop controller are designed independently of each other, which can avoid the current loop coupling problem under the traditional double-loop architecture, so that the steady-state and dynamic performance of the system are not affected by each other. Compared with the PI and MPC control methods, it has better dynamic and steady-state performance and stronger parameter robustness.

[0078] 2. For the PMSM voltage predictive control method based on composite disturbance compensation of the present invention, on the one hand, the linear extended state observer LESO is improved by using a variable exponent reaching law. Compared with the traditional exponential reaching law the -ε|s|ρsgn(s) term in the variable exponent reaching law effectively reduces the chattering in the sliding stage, and the -δ|s|σ s term not only speeds up the movement of the system towards the sliding surface, but also reduces the chattering problem of the traditional exponential reaching law when approaching the sliding surface. On the other hand, the dq-axis current estimation errors s d s q are selected to construct a dq-axis disturbance observer that can converge in a finite time to estimate the dq-axis given voltage deviation. A dq-axis disturbance correction controller is designed to correct the estimated dq-axis given voltage deviation, and the corrected dq-axis given voltage deviation is compensated to the model to obtain the optimal voltage vector of the motor, ensuring the observation accuracy. Description of the Drawings

[0079] Figure 1 It is a schematic structural diagram of the voltage predictive control system based on composite disturbance compensation of the present invention.

[0080] Figure 2 It is a schematic diagram of the principle of the linear active disturbance rejection controller LADRC of the present invention.

[0081] Figure 3 is the schematic diagram of the principle of the d-axis disturbance correction controller function U dsmc of the present invention.

[0082] Figure 4 are the simulation results of the output speed under no-load conditions by applying PI control and the control method of the present invention.

[0083] Figure 5 are the simulation results of the output torque under no-load conditions by applying PI control and the control method of the present invention.

[0084] Figure 6 are the simulation results of the d-axis current under no-load conditions by applying PI control and the control method of the present invention.

[0085] Figure 7 is the waveform diagram of the output speed when applying PI control and the control method of the present invention while introducing a step load and a non-linear load simultaneously.

[0086] Figure 8 is the waveform diagram of the output torque when applying PI control and the control method of the present invention while introducing a step load and a non-linear load simultaneously.

[0087] Figure 9 is the waveform diagram of the d-axis current when applying PI control and the control method of the present invention while introducing a step load and a non-linear load simultaneously.

[0088] Figure 10 is the schematic diagram of the structure of the voltage prediction control device based on composite disturbance compensation of the present invention. Detailed implementation manners

[0089] The present invention will be further described in detail below in conjunction with the detailed implementation manners and the drawings.

[0090] Embodiment 1:

[0091] Refer to Figure 1 , a PMSM voltage prediction control system based on composite disturbance compensation, including a speed loop control module, a current loop control module, a voltage disturbance compensation module, and a permanent magnet synchronous motor control sampling module; the permanent magnet synchronous motor control sampling module is used to collect the motor mechanical angular velocity ω m , d-axis current i d and q-axis current i q , d-axis voltage deviation f d and q-axis voltage deviation f d ; the speed loop control module is used to, according to the motor mechanical angular velocity command value ω m * and the motor mechanical angular velocity ω m, the q-axis current command value i after composite disturbance compensation is calculated by the linear active disturbance rejection controller LADRC q * ; The current loop control module is used to calculate according to the d-axis current i d and the q-axis current i q , the d-axis voltage deviation f d and the q-axis voltage deviation f d , the estimated value of the d-axis voltage deviation is calculated by the sliding mode observer SMO The estimated value of the q-axis voltage deviation The voltage disturbance compensation module is used to calculate the d-axis voltage command value u according to the q-axis current command value i after composite disturbance compensation q * and the estimated value of the d-axis voltage deviation The estimated value of the q-axis voltage deviation The d-axis voltage command value u is calculated by the dq-axis disturbance observer d * and the q-axis voltage command value u q * , and the d-axis voltage command value u is corrected by the dq-axis disturbance correction controller d * and the q-axis voltage command value u q * ; The permanent magnet synchronous motor control sampling module is also used to control the rotation of the permanent magnet synchronous motor according to the corrected d-axis voltage command value u d * and the q-axis voltage command value u q * ;

[0092] Specifically, the permanent magnet synchronous motor control sampling module can be simplified to the mathematical model shown in equations (1)-(4):

[0093]

[0094] In the above formula, T e is the electromagnetic torque; P n is the number of pole pairs; ψ f is the rotor magnetic flux; i d , i q are the d-axis and q-axis components of the stator current respectively; R is the stator resistance; L is the stator inductance; ω m is the rotor mechanical angular velocity; u d , u q are the d-axis and q-axis components of the stator voltage respectively; T L is the load torque; J is the moment of inertia; B is the viscous friction coefficient;

[0095] Specifically, see Figure 2, the linear active disturbance rejection controller LADRC includes a linear tracking differentiator LTD, a linear extended state observer LESO, and a linear state error feedback controller LSEF; the mathematical model of the linear tracking differentiator LTD is shown in Equation (5):

[0096]

[0097] In the above formula, e LTD is the tracking error; z1 is the tracking signal; is the change rate of z1; ω m * is the rotor mechanical angular velocity command value; r is the speed adjustable factor;

[0098] The mathematical model of the linear extended state observer LESO is designed based on the variable exponent sliding mode reaching law, and the mathematical model includes Equations (6)-(17):

[0099] Define the composite disturbance where b0 is the standard value of the characteristic gain coefficient, J0, ψ f0 are the per-unit values of the moment of inertia and the rotor magnetic flux respectively; i q * is the q-axis current command value; B0 is the standard value of the viscous friction coefficient; T L is the load torque; P n is the number of pole pairs; ψ f is the rotor magnetic flux; J is the moment of inertia; ω m is the rotor mechanical angular velocity;

[0100] Take the variables x1 = ω m ; x2 = f w ; u = i q * , and obtain Equations (6)-(7) according to the composite disturbance:

[0101]

[0102] In the above formula, are the change rates of x1 and x2 respectively; is the change rate of f w ;

[0103] Taking the Laplace transform of the traditional LESO observer shown in Equation (8) gives Equation (9), solving Equation (9) gives Equation (10), taking the Laplace transform of Equation (6) gives Equation (11), and according to Equation (11), the transfer function with the composite disturbance f w as the input and the estimated value of the composite disturbance as the output is shown in Equation (12):

[0104]

[0105] sω m (s) = b0i q * (s) + f w (s) (11)

[0106]

[0107] In the above formula, are the estimated values of ω m , f w respectively; y is the controller output; β1 and β2 are both adjustable gain parameters;

[0108] Take the variable Rewrite Equation (9) as Equation (13):

[0109]

[0110] In the above formula, are respectively the rate of change of e;

[0111] Define the disturbance estimation error e fw = x s1 - f w and the control function Get Equation (14):

[0112]

[0113] Take the linear sliding surface s = ce + e fw , and get the variable - exponent sliding - mode reaching law as shown in Equation (15):

[0114]

[0115] In the above formula, ε, ρ, σ, and δ are all the gains of the exponential sliding - mode reaching law; ε > 0, δ > 0, ρ > 0, σ > 0;

[0116] Design the control function c(e) as shown in Equation (16);

[0117]

[0118] In the above formula, F is the parameter in the control function c(e); h l , h m are respectively the upper and lower bounds; is the rate of change obtained for f w ;

[0119] Combining equations (13) - (16), the improved LESO observer is obtained as shown in equation (17):

[0120]

[0121] The mathematical model of the linear state error feedback controller LSEF is shown in equation (18):

[0122]

[0123] In the above equation, u0 is the intermediate variable of the linear state error feedback controller LSEF.

[0124] Specifically, the mathematical model of the dq - axis disturbance observer is designed based on the reaching law of the terminal saturation function, and the mathematical model includes equations (19) - (40):

[0125] Define the dq - axis voltage equations of PMSM when there is an electrical parameter mismatch as shown in equations (19) and (20):

[0126]

[0127] In the above equation, ω e is the rotor electrical angular velocity; f d , f q are the d - axis and q - axis voltage deviations respectively when there is a motor parameter mismatch; F d , F q are the change rates of f d , f d respectively, |F d | ≤ D, |F q | ≤ Q, D and Q are the maximum values of F d , F q respectively; ΔL is the stator inductance perturbation; ΔR is the stator resistance perturbation; Δψ f is the stator flux linkage perturbation; i d is the d - axis current component; R is the stator resistance; L is the stator inductance; u d , u q are the d - axis voltage and q - axis voltage respectively.

[0128] Define the dq - axis voltage observation equations as shown in equations (21) and (22):

[0129]

[0130] In the above equation, are the estimated values of the d - axis and q - axis currents respectively; are the estimated values of F d , F q respectively; I dsmo , I qsmoare the d-axis and q-axis disturbance observer functions; G d and G q are the gains of the d-axis and q-axis disturbance observers; U dsmc and U qsmc are the d-axis and q-axis disturbance correction controller functions;

[0131] Define the d-axis and q-axis current estimation errors s d and s q as well as the d-axis and q-axis disturbance estimation errors e fd and e fq as shown in Equation (23):

[0132]

[0133] Combining Equations (19) - (23), the dq-axis sliding mode error equations are obtained as shown in Equations (24) - (25):

[0134]

[0135] Select s d and s q as the sliding mode surface functions, and construct an approach law based on the terminal saturation function as shown in Equation (26) to make the system approach the sliding mode surface in a finite time T:

[0136]

[0137] In the above equation, k, α, and ε are all gains of the approach law based on the terminal saturation function; k > α > 0, ε > 0;

[0138] Substitute the approach law based on the terminal saturation function into Equations (24) and (25) respectively to obtain Equation (31):

[0139]

[0140] Define the upper bounds of e fd and e fq as E fd and E fq respectively, that is, |e fd | ≤ E fd ; |e fq | ≤ E fq to obtain the dq-axis disturbance observer functions as shown in Equation (32);

[0141]

[0142] After the system enters the sliding mode surface, rewrite Equations (24) and (25) as Equation (34):

[0143]

[0144] Introduce the sliding mode surface where c1 is the gain of the sliding mode surface s2, and the d-axis disturbance correction controller function shown in Equation (35) is designed;

[0145] U dsmc =(G d -c1)e fd -Ks2-Dsgn(s2) (35);

[0146] Introduce the sliding mode surface Design the q-axis disturbance correction controller function shown in Equation (37);

[0147] U qsmc =(G q -c1)e fq -Ks3-Qsgn(s3) (37);

[0148] Discretize Equations (19) and (20) to obtain Equation (38):

[0149]

[0150] In the above formula, T S is the system control period; i d (i), i q (i) are the d-axis and q-axis stator currents at time i respectively; i d (i + 1), i q (i + 1) are the predicted currents with a one-beat delay respectively; u d (i), u q (i) are the d-axis and q-axis stator voltages at time i respectively; are the estimated values of the d-axis and q-axis voltage disturbances at time i respectively; I dsmo (I), I qsmo (i) are the d-axis and q-axis disturbance observers at time i respectively; The structural schematic diagram of the d-axis disturbance observer is as Figure 3 shown. Since the structural of the q-axis disturbance observer is the same as that of the d-axis disturbance observer, the structural schematic diagram of the q-axis disturbance observer is not given again;

[0151] To make the predicted currents i d (i + 2), i q (i + 2) reach the predicted values within the next control period T S , that is, i d (i + 2)=i d * , i q (i + 1)=i q * , perform a one-beat delay on Equation (38) to obtain Equation (39):

[0152]

[0153] Rewrite Equation (39) as Equation (40), and obtain the optimal u for the next control period through Equation (40). d * and u q * :

[0154]

[0155] Example 2:

[0156] A PMSM voltage predictive control method based on composite disturbance compensation is carried out in the following steps in sequence:

[0157] First step, build a mathematical model of the permanent magnet synchronous motor. Based on this mathematical model, according to the d-axis voltage command value u d * and the q-axis voltage command value u q * control the rotation of the permanent magnet synchronous motor.

[0158] The mathematical model of the permanent magnet synchronous motor is derived based on the following premises: Premise 1, the stator windings are sinusoidally distributed in the stator slots; Premise 2, ignore the flux distortion caused by switching harmonics; Premise 3, ignore the magnetic saturation of the iron core and the iron loss caused by hysteresis and eddy currents. The mathematical model of the permanent magnet synchronous motor is shown in Equations (1)-(4):

[0159]

[0160] In the above formula, T e is the electromagnetic torque; P n is the number of pole pairs; ψ f is the rotor magnetic flux; i d and i q are the d-axis and q-axis components of the stator current respectively; R is the stator resistance; L is the stator inductance; ω m is the rotor mechanical angular velocity; u d and u q are the d-axis and q-axis components of the stator voltage respectively; T L is the load torque; J is the moment of inertia; B is the viscous friction coefficient.

[0161] Second step, combine the terms related to the load torque and the rotor mechanical angular velocity into a composite disturbance, and define the composite disturbance where b0 is the standard value of the characteristic gain coefficient, J0 and ψ f0 are the per-unit values of the moment of inertia and the rotor magnetic flux respectively; i q* is the q-axis current command value; B0 is the standard value of the viscous friction coefficient; T L is the load torque; P n is the number of pole pairs; ψ f is the rotor flux linkage; J is the moment of inertia; ω m is the rotor mechanical angular velocity;

[0162] Let the variable x1 = ω m ; x2 = f w ; u = i q * , according to the composite disturbance, rewrite equations (3)-(4) as equations (6)-(7):

[0163]

[0164] In the above formula, are the change rates of x1 and x2 respectively; is the change rate of f w ;

[0165] Step 3: Design a linear active disturbance rejection controller LADRC; according to the motor mechanical angular velocity command value ω m * and the collected motor mechanical angular velocity ω m , calculate the q-axis current command value i after composite disturbance compensation through the linear active disturbance rejection controller LADRC q * ;

[0166] The LADRC controller includes a linear tracking differentiator LTD, a linear extended state observer LESO, and a linear state error feedback controller LSEF. The mathematical model of the linear tracking differentiator LTD is shown in equation (5):

[0167]

[0168] In the above formula, e LTD is the tracking error; z1 is the tracking signal; is the change rate of z1; ω m * is the rotor mechanical angular velocity command value; r is the speed adjustable factor;

[0169] The linear extended state observer LESO is used to effectively estimate and compensate the influence of load disturbance and mechanical parameter perturbation on i q * ; the construction steps of the mathematical model of the linear extended state observer LESO are as follows:

[0170] 1.1 The traditional LESO observer is shown in equation (8):

[0171]

[0172] In the above formula, are the estimated values of ω m and f w respectively; y is the output of the controller; β1 and β2 are both adjustable gain parameters;

[0173] To prove the stability of the observer, taking the Laplace transform of Equation (8) gives Equation (9), solving Equation (9) yields Equation (10), taking the Laplace transform of Equation (6) gives Equation (11), and further obtaining the transfer function with the composite disturbance f w as the input and the estimated value of the composite disturbance as the output as shown in Equation (12). Making the characteristic roots of Equation (12) on the left part of the sliding surface s can ensure the stability of the observer:

[0174]

[0175] sω m (s) = b0i q * (s) + f w (s) (11)

[0176]

[0177] 1.2 It can be seen from Equation (12) that the estimation error of the traditional LESO observer is related to the upper bound of f w and the values of β1 and β2. To enhance the dynamic response speed of the LESO observer and reduce the estimation error, a variable exponential sliding mode reaching law is introduced to improve the LESO observer, specifically as follows:

[0178] Taking the variable rewrite Equation (9) as Equation (13):

[0179]

[0180] In the above formula, are respectively the change rate of e;

[0181] 1.3 Define the disturbance estimation error e fw = x sl - f w and the control function to obtain Equation (14):

[0182]

[0183] 1.4 Take the linear sliding surface s = ce + e fw, the variable exponent sliding mode reaching law is obtained as shown in Equation (15):

[0184]

[0185] In the above formula, ε, ρ, σ, and δ are the gains of the variable exponent sliding mode reaching law; ε > 0, δ > 0, ρ > 0, σ > 0;

[0186] Compared with the traditional exponential reaching law The variable exponent sliding mode reaching law on the one hand effectively reduces the chattering in the sliding stage through the -ε|s| ρ sgn(s) term, and on the other hand, through the δ|s| σ term not only speeds up the movement speed towards the sliding surface, but also reduces the chattering problem of the traditional exponential reaching law when it is close to the sliding surface; by introducing the combination of the variable exponent sliding mode reaching law and the LESO controller, not only can the advantages of simple parameter tuning and high reliability of the LESO controller be exerted, but also the observation error can be reduced, and the steady-state and dynamic performance of the system under parameter mismatch can be improved;

[0187] 1.5 Design the control function C(e) as shown in Equation (16) to ensure that when t → ∞, e → 0, e fw → 0 and converges exponentially:

[0188]

[0189] In the above formula, h l and h m are respectively the upper and lower bounds; is the change rate of f w obtained;

[0190] 1.6 Combining Equations (13) - (16), the improved LESO observer is obtained as shown in Equation (17):

[0191]

[0192] The mathematical model of the linear state error feedback controller LSEF is shown in Equation (18):

[0193]

[0194] In the above formula, u0 is the intermediate variable of the linear state error feedback controller LSEF.

[0195] Fourth step, according to the d-axis current i d and the q-axis current i q , the d-axis voltage deviation f d and the q-axis voltage deviation f d , the estimated value of the d-axis voltage deviation is calculated through the sliding mode controller SMO Estimated value of q - axis voltage deviation

[0196] Step 5: Design dq - axis disturbance observers based on the reaching law of the terminal saturation function; according to the q - axis current command value i after composite disturbance compensation q * and the estimated value of d - axis voltage deviation Estimated value of q - axis voltage deviation Calculate the d - axis voltage command value u through the dq - axis disturbance observer d * and the q - axis voltage command value u q * , and correct the d - axis voltage command value u through the dq - axis disturbance correction controller d * and the q - axis voltage command value u q * ;

[0197] The construction steps of the dq - axis disturbance observer are as follows:

[0198] 2.1 Construct the dq - axis voltage equations of PMSM when there is electrical parameter mismatch as shown in (19) and (20):

[0199]

[0200] In the above formula, ω e is the rotor electrical angular velocity; f d and f q are the d - axis and q - axis voltage disturbances respectively when there is motor parameter mismatch; F d and F q are the change rates of f d and f q respectively, |F d | ≤ D, |F q | ≤ Q, D and Q are respectively; ΔL is the stator inductance perturbation; ΔR is the stator resistance perturbation; Δψ f is the stator flux linkage perturbation;

[0201] 2.2 Construct the dq - axis voltage observation equations as shown in (21) and (22):

[0202]

[0203] In the above formula, are the estimated values of d - axis and q - axis currents respectively; are the estimated values of F d and f q respectively; I dsmo and I qsmo are the d - axis and q - axis disturbance observer functions respectively; Gd , G q are the gains of the d-axis and q-axis observers respectively; U dsmc , U qsmc are the d-axis and q-axis disturbance correction controllers respectively;

[0204] 2.3 Define the d-axis and q-axis current estimation errors s d , s q and the d-axis and q-axis disturbance estimation errors e fd , e fq as shown in Equation (23):

[0205]

[0206] 2.4 Combine Equations (19) - (23) to obtain the dq-axis sliding mode error equations as shown in Equations (24) - (25):

[0207]

[0208] 2.5 By selecting s d , s q as the sliding mode surface function and constructing the reaching law based on the terminal saturation function as shown in Equation (26), it can be ensured that the system approaches the sliding mode surface in a finite time T:

[0209]

[0210] In the above formula, k, α, and ε are all the gains of the reaching law based on the terminal saturation function; k > α > 0, ε > 0;

[0211] To prove that the reaching law based on the terminal saturation function can make the system approach the sliding mode surface in a finite time T, define the energy function Substitute it into Equation (26) to obtain Equation (27), Equation (27) can be rewritten as Equation (28), take the integral of Equation (28) to obtain Equation (29), and solve the inequality of Equation (29) to obtain Equation (30); According to the reaching law criterion, it can be verified that the system will converge to the sliding mode surface within a finite time T; Equations (27) - (30) are as follows:

[0212]

[0213] 2.6 Substitute the reaching law based on the terminal saturation function into Equations (24) and (25) respectively to obtain Equation (31):

[0214]

[0215] 2.7 Define the upper bounds of e fd , e fq as E fd , E fq , that is, |efd |≤E fd ; |e fq |≤E fq , the dq-axis disturbance observer function shown in Equation (32) is obtained, and the schematic diagram of the principle of the d-axis disturbance observer I dsmo is as shown in Figure 3 . Since the design methods of the d- and q-axis disturbance observers are the same, the present invention does not give the schematic diagram of the q-axis disturbance observer I qsmo : To ensure the sliding mode stability the parameter values need to satisfy Equation (33):

[0216]

[0217] 2.8 After the system enters the sliding mode surface, rewrite Equations (24) and (25) as Equation (34):

[0218]

[0219] 2.9 Design U dsmc and U qsmc through first-order sliding mode control, specifically:[[]]

[0220] Introduce the sliding mode surface where c1 is, and the designed U dsmc ;

[0221] U dsmc =(G d -c1)e fd -Ks2-Dsgn(s2) (35);

[0222] Introduce the sliding mode surface and the designed U qsmc is obtained as shown in Equation (37);

[0223] U qsmc =(G q -c1)e fq -Ks3-Qsgn(s3) (37);

[0224] Considering that the design process of U dsmc is exactly the same as that of U qsmc , only the convergence proof of U dsmc is given below: Define the energy function Substitute it into Equation (35) to obtain Equation (36):

[0225] It can be seen that after the system reaches the sliding mode surface s2 = 0, and e fdConverge to 0 exponentially respectively, and the convergence rate depends on the value of variable K;

[0226] Step 6: Calculate u in the next control period d * and u q * to control the rotation of the permanent magnet synchronous motor; the specific calculation steps are as follows:

[0227] 3.1 First, discretize Equation (19) and Equation (20) to obtain Equation (38):

[0228]

[0229] In the above formula, T S is the system control period; i d (i), i q (i) are the stator currents on the d-axis and q-axis at time i respectively; i d (i + 1), i q (i + 1) are the predicted currents with one-beat delay respectively; u d (i), u q (i) are the stator voltages on the d-axis and q-axis at time i respectively; are the estimated values of voltage disturbances on the d-axis and q-axis at time i respectively; I dsmo (i), I qsmo (i) are the disturbance observers on the d-axis and q-axis at time i respectively;

[0230] 3.2 To make the predicted currents i d (i + 2), i q (i + 2) reach the predicted values within the next control period T S , that is, i d (i + 2) = i d * , i q (i + 2) = i q * , perform one-beat delay on Equation (38) to obtain Equation (39):

[0231]

[0232] 3.3 Rewrite Equation (39) as Equation (40), and obtain the optimal u d * and u q * in the next control period through Equation (40):

[0233]

[0234] The improved sliding mode control method for PMSM of the present invention is to achieve precise composite disturbance compensation to obtain the optimal voltage vector. On the one hand, a dq-axis disturbance observer that converges within a finite time is constructed to estimate the dq-axis given voltage deviation caused by the composite disturbance. On the other hand, a dq-axis disturbance correction controller is designed using first-order sliding mode control to correct the estimated dq-axis given voltage deviation, ultimately improving the disturbance estimation accuracy under electrical parameter perturbation. At the same time, due to the addition of a dq-axis disturbance correction term in the dq-axis disturbance observer, it can converge within a finite time, ensuring the observation accuracy.

[0235] Performance verification:

[0236] (1) To verify the robustness of the proposed control method, a traditional PI-regulator-based control model (hereinafter referred to as PI control) and the control method of the present invention (hereinafter referred to as VPC control) are respectively built using the Simulink simulation platform for comparative research. The control parameters are set as shown in Table 1:

[0237] Table 1 Control parameter table

[0238]

[0239]

[0240] The simulation results of the output speed, output torque, and d-axis current of PI control and VPC control under no-load conditions are respectively as Figures 4 to 6 shown. It can be seen that the overshoot of the tracking process of PI control is 25%, the adjustment time is 0.09 s, and the peak time is 0.025 s; the maximum fluctuation range of torque output under steady-state conditions is -0.5 to 2 N·m, and the maximum fluctuation range of d-axis current is -1.5 to 2.2 A; at the same time, there is no obvious overshoot in the speed tracking process of VPC control, the adjustment time is 0.04 s, the peak time is 0.025 s, and there is a very small amplitude chattering; the maximum fluctuation range of torque output under steady-state conditions is -0.5 to 0.5 N·m, and the maximum fluctuation range of d-axis current is -0.4 to 0.3 A. The above results can show that VPC control better improves the system dynamic response and steady-state performance under no-load conditions.

[0241] (2) Build a motor speed regulation platform to verify the dynamic performance and steady-state performance of the two methods. The platform parameter settings are consistent with the parameters in Table 1. The 19-channel DSPF28379D is selected for the development board, the ATK-DMF407 is used for the motor drive board, the sampling frequency is 20 kHz, and the UNI-TUTD2102CEX is used for the oscilloscope. The permanent magnet drive motor and the load motor both use 42JSF630AS-1000. The load current and torque signals are collected by the DSPF28379D and imported and displayed on the oscilloscope.

[0242] The waveform diagrams of the output speed, output torque, and d-axis current when PI control and VPC control simultaneously introduce a step load and a non-linear load are respectively as follows Figures 7 to 9 shown. The step load is introduced at 0.1 s with a value of 1 N·m, and the non-linear load is introduced at 0.2 s with a value of (0.2sin(100πt)+1.8) N·m. Through the analysis of the waveform diagrams, in terms of output speed control, compared with PI control, the adjustment time and overshoot of VPC control are significantly reduced during the motor startup phase, and it has obvious advantages in terms of speed drop and convergence speed control during the sudden load addition phase. In terms of output torque and d-axis current tracking control, compared with PI control, VPC control has obvious advantages in terms of tracking time and overshoot suppression. In summary, VPC control has more excellent dynamic and steady-state characteristics.

[0243] Example 3:

[0244] Refer to Figure 10 , an improved sliding mode control device for PMSM based on a two-stage dynamic boundary layer, including a memory and a processor; the memory is used to store computer program code and transmit the computer program code to the processor; the processor is used to execute the configuration and operation optimization method described in Example 2 according to the instructions in the computer program code.

[0245] Example 4:

[0246] A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the configuration and operation optimization method described in Example 2.

Claims

1. A PMSM voltage prediction control system based on composite disturbance compensation, characterized in that: The PMSM voltage prediction control system includes a speed loop control module, a current loop control module, a voltage disturbance compensation module, and a permanent magnet synchronous motor control sampling module; The permanent magnet synchronous motor control sampling module is used to collect the motor mechanical angular velocity ω when the permanent magnet synchronous motor rotates m , d-axis current i d and q-axis current i q , d-axis voltage deviation f d The voltage deviation from the q axis is f d ; The speed loop control module is used to control the motor mechanical angular velocity command value ω m * And the motor mechanical angular velocity ω m , the q-axis current command value i after composite disturbance compensation is calculated by the linear active disturbance rejection controller LADRC q * ; The current loop control module is used to control the d-axis current i d and q-axis current i q , d-axis voltage deviation f d The voltage deviation from the q axis is f d , the estimated value of the d-axis voltage deviation is calculated by the sliding mode controller SMO Estimated q-axis voltage deviation The voltage disturbance compensation module is used to compensate the q-axis current command value i after the composite disturbance compensation. q * , d-axis voltage deviation estimate Estimated q-axis voltage deviation Calculate the d-axis voltage command value u through the dq-axis disturbance observer d * , q-axis voltage command value u q * The d-axis voltage command value u is corrected by the dq-axis disturbance correction controller d * , q-axis voltage command value u q * make corrections; The permanent magnet synchronous motor control sampling module is also used to adjust the d-axis voltage command value u according to the corrected d-axis voltage command value u d * , q-axis voltage command value u q * Control the rotation of permanent magnet synchronous motor.

2. A PMSM voltage prediction control system based on composite disturbance compensation according to claim 1, characterized in that: The linear active disturbance rejection controller LADRC includes a linear tracking differentiator LTD, a linear extended state observer LESO, and a linear state error feedback controller LSEF; The mathematical model of the linear tracking differentiator LTD is shown in formula (5): In the above formula, e LTD is the tracking error; z1 is ω m * The tracking signal; z1 is the rate of change of z1; ω m * is the rotor mechanical angular velocity command value; r is the speed adjustable factor; The mathematical model of the linear extended state observer LESO is designed based on the variable exponential sliding mode reaching law, including equations (13) to (17): In the above formula, variable x1 = ω m ; x2 = f w ; u=i q * , They are ω m 、f w The estimated value of y1 represents the controller output, They are The rate of change; β1 and β2 are both adjustable gain parameters; (14)； In the above formula, f w is a composite disturbance, b0 is the standard value of the characteristic gain coefficient, J0, ψf0 are the per unit values ​​of moment of inertia and rotor flux respectively; i q * is the q-axis current command value; B0 is the standard value of the viscous friction coefficient; T L is the load torque; P n is the pole pair number; ψ f is the rotor flux; J is the moment of inertia; ω m is the rotor mechanical angular velocity; e fw is the disturbance estimation error, e fw =x sl -f w ; C(e) is the control function, Take the linear sliding surface s=ce+e fw , where ce is the sliding surface function, and the variable exponential sliding mode reaching law is shown in formula (15): In the above formula, ε, ρ, σ, δ are all gains of the variable exponential sliding mode reaching law; ε>0, δ>0, ρ>0, σ>0; The designed control function c(e) is shown in formula (16); In the above formula, F is the parameter in the control function c(e); h l 、h m They are The upper and lower bounds of f w Get the rate of change; The mathematical model of the linear state error feedback controller LSEF is shown in formula (18): In the above formula, u0 is the intermediate variable of the linear state error feedback controller LSEF.

3. The PMSM voltage prediction control system based on composite disturbance compensation according to claim 1, characterized in that: The mathematical model of the dq-axis disturbance observer is designed based on the reaching law of the terminal saturation function, including equations (19) to (40): The dq axis voltage equations of PMSM when electrical parameters are mismatched are defined as shown in equations (19) and (20): In the above formula, ω e is the rotor electrical angular velocity; f d 、f q are the d-axis and q-axis voltage deviations when the motor parameters are mismatched; F d 、F q f d 、f q The rate of change, |F d |≤D,|F q |≤Q, D and Q are F d 、F q The maximum value of; ΔL is the stator inductance perturbation; ΔR is the stator resistance perturbation; Δψ f is the stator flux perturbation; i d is the d-axis current component; R is the stator resistance; L is the stator inductance; u d 、u q are d-axis voltage and q-axis voltage respectively; The dq axis voltage observation equation is defined as shown in (21) and (22): In the above formula, are the estimated values ​​of d-axis and q-axis currents respectively; F d 、F q Estimated value of I dsmo ,I qsmo are the d-axis and q-axis disturbance observer functions respectively; G d , G q are the gains of the d-axis and q-axis disturbance observers respectively; U dsmc , U qsmc are the d-axis and q-axis disturbance correction controller functions respectively; Define the d-axis and q-axis current estimation errors s d 、s q And the d and q axis disturbance estimation errors e fd 、e fq As shown in formula (23): Combining equations (19) to (23), we get the dq axis sliding mode error equation as shown in equations (24) to (25): Select d 、s q As the sliding surface function, a reaching law based on the terminal saturation function is constructed as shown in formula (26) to make the system approach the sliding surface in a finite time T: In the above formula, k, α, ε are the gains based on the reaching law of the terminal saturation function; k>α>0,ε>0; Substituting the reaching law based on the terminal saturation function into equation (24) and equation (25) respectively, we obtain equation (31): Definition fd 、e fq The upper bounds of fd 、E fq , that is |e fd |≤E fd ;|e fq |≤E fq , we get the dq-axis disturbance observer function as shown in equation (32); After the system enters the sliding surface, equations (24) and (25) are rewritten as equation (34): Introducing sliding surface Where c1 is the gain of the sliding surface s2, and the d-axis disturbance correction controller function is designed as shown in formula (35); U dsmc =(G d -c1)e fd -Ks2-Dsgn(s2) (35) Introducing sliding surface The q-axis disturbance correction controller function is designed as shown in formula (37); U qsmc =(G q -c1)e fq -Ks3-Qsgn(s3) (37); Discretize equation (19) and equation (20) to get equation (38): In the above formula, T S is the system control cycle; i d (i) q (i) are the d-axis and q-axis stator currents at time i; d (i+1), i q (i+1) are the predicted currents corresponding to one-beat delay; u d (i) u q (i) are the d-axis and q-axis stator voltages at time i, respectively; are the estimated values ​​of the d-axis and q-axis voltage disturbances at time i; I dsmo (i) and (I) qsmo (i) are the d-axis and q-axis disturbance observers at time i respectively; To predict the current i d (i+2), i q (i+2) In the next control cycle T S The predicted value is reached within i d (i+2)=i d * ,i q (i+2)=i q * , delay equation (38) by one beat, and get equation (39): Rewrite equation (39) into equation (40), and obtain the optimal u for the next control cycle through equation (40): d * 、u q * :

4. The PMSM voltage prediction control system based on composite disturbance compensation according to claim 1, characterized in that: The mathematical model of the permanent magnet synchronous motor control sampling module is shown in equations (1) to (4): In the above formula, T e is the electromagnetic torque; P n is the pole pair number; ψ f is the rotor flux; i d 、i q are the d-axis and q-axis components of the stator current respectively; R is the stator resistance; L is the stator inductance; ω m is the rotor mechanical angular velocity; u d 、u q are the d-axis and q-axis components of the stator voltage respectively; T L is the load torque; J is the moment of inertia; B is the viscous friction coefficient.

5. A PMSM voltage prediction control method based on composite disturbance compensation, characterized in that: The PMSM voltage prediction control method comprises: Collect the mechanical angular velocity ω of the permanent magnet synchronous motor when it rotates m , d-axis current i d and q-axis current i q , d-axis voltage deviation f d The voltage deviation from the q axis is f d ; According to the motor mechanical angular velocity command value ω m * And the motor mechanical angular velocity ω m , the q-axis current command value i after composite disturbance compensation is calculated by the linear active disturbance rejection controller LADRC q * ; According to the d-axis current i d and q-axis current i q , d-axis voltage deviation f d The voltage deviation from the q axis is f d , the estimated value of the d-axis voltage deviation is calculated by the sliding mode controller SMO Q-axis voltage deviation estimate According to the q-axis current command value i after composite disturbance compensation q * , d-axis voltage deviation estimate Q-axis voltage deviation estimate Calculate the d-axis voltage command value u through the dq-axis disturbance observer d * , q-axis voltage command value u q * The d-axis voltage command value u is corrected by the dq-axis disturbance correction controller d * , q-axis voltage command value u q * make corrections; According to the corrected d-axis voltage command value u d * , q-axis voltage command value u q * Control the rotation of permanent magnet synchronous motor.

6. The PMSM voltage prediction control method based on composite disturbance compensation according to claim 5 is characterized in that: The linear active disturbance rejection controller LADRC includes a linear tracking differentiator LTD, a linear extended state observer LESO, and a linear state error feedback controller LSEF; The mathematical model of the linear tracking differentiator LTD is shown in formula (5); In the above formula, e LTD is the tracking error; z1 is ω m * Tracking signal; is the rate of change of z1; ω m * is the rotor mechanical angular velocity command value; r is the speed adjustable factor; The mathematical model of the linear extended state observer LESO is designed based on the variable exponential sliding mode reaching law, including equations (13) to (17); In the above formula, variable x1 = ω m ; x2 = f w ; u=i q * , They are ω m 、f w The estimated value of y1 represents the controller output, They are e's rate of change; β1 and β2 are both adjustable gain parameters; In the above formula, f w is a composite disturbance, b0 is the standard value of the characteristic gain coefficient, J0, ψf0 are the per unit values ​​of moment of inertia and rotor flux respectively; i q * is the q-axis current command value; B0 is the standard value of the viscous friction coefficient; T L is the load torque; P n is the number of pole pairs; ψf is the rotor flux; J is the moment of inertia; ω m is the rotor mechanical angular velocity; e fw is the disturbance estimation error, e fw =x s1 -f w ; C(e) is the control function, Take the linear sliding surface s=ce+e fw , where ce is the sliding surface function, and the variable exponential sliding mode reaching law is shown in formula (15): In the above formula, ε, ρ, σ, δ are all gains of the variable exponential sliding mode reaching law; ε>0, δ>0, ρ>0, σ>0; The designed control function c(e) is shown in formula (16); In the above formula, F is the parameter in the control function c(e); h l 、h m They are The upper and lower bounds of f w Get the rate of change; The mathematical model of the linear state error feedback controller LSEF is shown in formula (18): In the above formula, u0 is the intermediate variable of the linear state error feedback controller LSEF.

7. The PMSM voltage prediction control method based on composite disturbance compensation according to claim 5 is characterized in that: The mathematical model of the dq-axis disturbance observer is designed based on the reaching law of the terminal saturation function, including equations (19) to (40): The dq axis voltage equations of PMSM when electrical parameters are mismatched are defined as shown in equations (19) and (20): In the above formula, ω e is the rotor electrical angular velocity; f d 、f q are the d-axis and q-axis voltage deviations when the motor parameters are mismatched; F d 、F q f d 、f q The rate of change, |F d |≤D,|F q |≤Q, D and Q are F d 、F q The maximum value of; ΔL is the stator inductance perturbation; ΔR is the stator resistance perturbation; Δψ f is the stator flux perturbation; i d is the d-axis current component; R is the stator resistance; L is the stator inductance; u d 、u q are d-axis voltage and q-axis voltage respectively; The dq axis voltage observation equation is defined as shown in (21) and (22): In the above formula, are the estimated values ​​of d-axis and q-axis currents respectively; F d 、F q Estimated value of I dsmo ,I qsmo are the d-axis and q-axis disturbance observer functions respectively; G d , G q are the gains of the d-axis and q-axis disturbance observers respectively; U dsmc , U qsmc are the d-axis and q-axis disturbance correction controller functions respectively; Define the d-axis and q-axis current estimation errors s d 、s q And the d and q axis disturbance estimation errors e fd 、e fq As shown in formula (23): Combining equations (19) to (23), we get the dq axis sliding mode error equation as shown in equations (24) to (25): Select d 、s q As the sliding surface function, a reaching law based on the terminal saturation function is constructed as shown in formula (26) to make the system approach the sliding surface in a finite time T: In the above formula, k, α, ε are the gains based on the reaching law of the terminal saturation function; k>α>0, ε>0; Substituting the reaching law based on the terminal saturation function into equation (24) and equation (25) respectively, we obtain equation (31): Definition fd 、e fq The upper bounds of fd 、E fq , that is |e fd |≤E fd ;|e fq |≤E fq , we get the dq-axis disturbance observer function as shown in equation (32); After the system enters the sliding surface, equations (24) and (25) are rewritten as equation (34): Introducing sliding surface Where c1 is the gain of the sliding surface s2, and the d-axis disturbance correction controller function is designed as shown in formula (35); U dsmc =(G d -c1)e fd -Ks2-Dsgn(s2) (35); Introducing sliding surface The q-axis disturbance correction controller function is designed as shown in formula (37); U qsmc =(G q -c1)e fq -Ks3-Qsgn(s3) (37); Discretize equation (19) and equation (20) to get equation (38): In the above formula, T S is the system control cycle; i d (i) q (i) are the d-axis and q-axis stator currents at time i; d (i+1), i q (i+1) are the predicted currents corresponding to one-beat delay; u d (i) u q (i) are the d-axis and q-axis stator voltages at time i, respectively; are the estimated values ​​of the d-axis and q-axis voltage disturbances at time i; I dsmo (i) and (I) qsmo (i) are the d-axis and q-axis disturbance observers at time i respectively; To predict the current i d (i+2), i q (i+2) In the next control cycle T S The predicted value is reached within i d (i+2)=i d * ,i q (i+2)=i q * , delay equation (38) by one beat, and get equation (39): Rewrite equation (39) into equation (40), and obtain the optimal u for the next control cycle through equation (40): d * 、u q * :

8. The PMSM voltage prediction control method based on composite disturbance compensation according to claim 5 is characterized in that: According to the corrected d-axis voltage command value u d * , q-axis voltage command value u q * The control process of controlling the rotation of the permanent magnet synchronous motor is simplified into the mathematical model shown in equations (1) to (4): In the above formula, T e is the electromagnetic torque; P n is the pole pair number; ψ f is the rotor flux; i d 、i q are the d-axis and q-axis components of the stator current respectively; R is the stator resistance; L is the stator inductance; ω m is the rotor mechanical angular velocity; u d 、u q are the d-axis and q-axis components of the stator voltage respectively; T L is the load torque; J is the moment of inertia; B is the viscous friction coefficient.

9. A PMSM voltage prediction control device based on composite disturbance compensation, characterized in that: The PMSM voltage prediction control device includes a memory and a processor; the memory is used to store computer program code and transfer the computer program code to the processor; the processor is used to execute the PMSM voltage prediction control method as described in claims 5-8 according to the instructions in the computer program code.

10. A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the PMSM voltage prediction control method according to claims 5-8.

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