Motor prediction control method and system based on disturbance compensation and medium

Abstract

The invention discloses a motor prediction control method and system based on disturbance compensation and a medium, and the method comprises the steps: estimating disturbance caused by parameter mismatch through a sliding-mode observer based on a variable exponential reaching law; compensating to a prediction equation of current and flux linkage, and performing calculation and delay compensation to obtain a torque prediction value and a flux linkage prediction value at the k + 2 moment; substituting the torque predicted value at the k + 2 moment into a preset value function g1, and selecting four voltage vectors which enable the value of the torque value function g1 to be minimum in a voltage vector space as candidate reference voltage vectors; and the flux linkage value prediction at the k + 2 moment is substituted into a preset value function g2, and a voltage vector which enables the value function g2 to be minimum is selected from the four candidate reference voltage vectors to serve as a voltage vector which is finally output and used for controlling the permanent magnet synchronous motor. The method aims at improving the robustness of motor control under the condition that the resistance, inductance and flux linkage parameters of the permanent magnet synchronous motor are mismatched.

Description

Technical Field

[0001] The present invention relates to the technical field of control of permanent magnet synchronous motors, and in particular to a motor predictive control method, system and medium based on disturbance compensation. Background Art

[0002] In recent years, as a representative of high-performance control strategies, model predictive control has received increasing attention. Generally, according to different control objectives, model predictive control can be mainly divided into three categories: model predictive current control, model predictive speed control and model predictive torque control. Among them, model predictive torque control is a control strategy that combines model predictive control with direct torque control, and plays an important role in motor drive systems. Traditional model predictive torque control constructs cost functions of torque and flux, and then selects the optimal voltage vector through the cost function. However, for model predictive torque control, excellent tracking control performance is extremely dependent on accurate motor models, especially accurate electrical and mechanical parameters. Due to changes in the operating environment and aging of the motor, the motor parameters will deviate from their original values, and parameter mismatch will destroy the transient tracking performance, resulting in errors in torque and flux, and more seriously, may cause the entire control system to crash. Therefore, how to deal with parameter disturbances and improve robustness is a major problem facing model predictive torque control. In addition, weight factor tuning is another major problem facing model predictive torque control. For model predictive torque control, a weight factor needs to be designed to balance the torque deviation and flux deviation, but since different conditions require different weight factors, the adjustment of the weight factor is a very tedious task. The current strategies for dealing with this problem generally include weight factor self-tuning and weight factor elimination. Although weight factor self-tuning can obtain the optimal weight factor through real-time adjustment when conditions change, its implementation requires complex algorithms and huge computational effort. Weight factor elimination is a feasible method to solve the weight factor adjustment problem. By transforming the cost function equation or optimizing torque and flux separately, the weight factor is no longer needed. However, this method usually requires precise motor parameters and has poor robustness to parameter mismatch. Summary of the invention

[0003] Technical problem to be solved by the present invention: In view of the above-mentioned problems in the prior art, a motor predictive control method, system and medium based on disturbance compensation are provided. The present invention aims to improve the robustness of motor control when the resistance, inductance and flux linkage parameters of the permanent magnet synchronous motor are mismatched.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0005] A motor predictive control method based on disturbance compensation comprises the following steps:

[0006] S1, estimates the disturbance caused by parameter mismatch through a sliding mode observer based on a variable exponential reaching law;

[0007] S2, compensating the disturbance into the prediction equations of current and flux to obtain the predicted current value and flux prediction value at time k+1;

[0008] S3, obtaining the torque prediction value at time k+1 based on the current prediction value at time k+1, and obtaining the torque prediction value and flux prediction value at time k+2 based on the delay compensation of the torque prediction value and flux prediction value at time k+1;

[0009] S4, bring the torque prediction value at time k+2 into the preset torque value function g 1 , select the torque value function g in the voltage vector space 1 The four voltage vectors with the smallest values ​​are used as candidate reference voltage vectors;

[0010] S5, bring the magnetic link value prediction at time k+2 into the preset magnetic link value function g 2 , select the four candidate reference voltage vectors so that the flux linkage value function g 2 The voltage vector with the smallest value is used as the final output to control the voltage vector of the permanent magnet synchronous motor.

[0011] Optionally, the disturbance caused by parameter mismatch estimated by the sliding mode observer in step S1 includes current disturbance and flux disturbance, and the function expression of the current disturbance observer used to observe the current disturbance is:

[0012]

[0013] In the above formula, is the observed value of dq axis current, u dq is the dq axis voltage, is the dq axis current disturbance, S idq is the dq axis sliding mode function of the current, g idq is the dq axis sliding mode gain coefficient of the current, A, B and C are coefficient matrices, and:

[0014]

[0015] Among them, R s is the stator resistance, L d and L q is the dq axis inductance, ω e is the electrical angular velocity, ψ f is the permanent magnet flux; the function expression of the flux disturbance observer used to observe the flux disturbance is:

[0016]

[0017] In the above formula, is the observed value of dq-axis flux linkage, is the dq axis flux disturbance, S ψdq is the dq axis sliding mode function of the magnetic flux, g ψdq is the dq axis sliding mode gain coefficient of the flux linkage, A 1 and C 1 is a coefficient matrix, and has:

[0018]

[0019] And the function expression of the variable exponential reaching law adopted by the sliding mode observer is:

[0020]

[0021] In the above formula, is the derivative of the sliding surface s, ε, K, α and c are constant coefficients, e is the system state, τ and t are time.

[0022] Optionally, in step S2, the disturbance is compensated into the prediction equations of current and flux to obtain the function expressions of the current prediction value and the flux prediction value at time k+1:

[0023]

[0024] In the above formula, i d (k+1) and i q (k+1) are the predicted values ​​of dq axis current at time k+1, Ts is the sampling period, Rs is the stator resistance, L d and L q are the dq axis inductance, i d (k) and i q (k) are the dq axis current values ​​at time k, ω e is the electrical angular velocity, u d (k) and u q (k) are the dq axis voltage at time k, ψ f is the permanent magnet flux, F id (k) and F iq (k) are the disturbances of dq axis current when the parameters are mismatched; ψ d (k+1) and ψ q (k+1) are the predicted values ​​of dq axis flux at time k+1, ψ d (k) and ψ q (k) are the dq axis flux values ​​at time k, F ψd (k) and F ψq (k) are the disturbances of dq axis flux when the parameters are mismatched at time k.

[0025] Optionally, in step S3, the function expression for obtaining the torque prediction value at time k+1 based on the current prediction value at time k+1 is:

[0026] T e (k+1)=(3 / 2)n p [ψ d (k+1)i q (k+1)-ψ q (k+1)i d (k+1)],

[0027] In the above formula, T e (k+1) is the torque prediction value at time k+1, n p is the number of magnetic pole pairs of the permanent magnet motor, i d (k+1) and i q (k+1) are the predicted values ​​of dq axis current at time k+1, ψ d (k+1) and ψ q (k+1) are the predicted values ​​of dq axis flux at time k+1 respectively.

[0028] Optionally, in step S3, the function expression of the torque prediction value and the flux prediction value at time k+2 obtained by delay compensation based on the torque prediction value and the flux prediction value at time k+1 is:

[0029]

[0030] In the above formula, T e (k+2) is the torque prediction value at time k+2, n p is the number of magnetic poles of the permanent magnet motor, ψ d (k+2) and ψ q (k+2) are the predicted values ​​of dq axis flux at time k+2, i d (k+2) and i q (k+2) are the predicted values ​​of dq axis current at time k+2, T s is the sampling period, R s is the stator resistance, L d and L q are the dq axis inductance, ψ d (k+1) and ψ q (k+1) are the predicted values ​​of dq axis flux at time k+1, ω e is the electrical angular velocity, ψ d and ψ q are the dq axis flux, ψ f is the permanent magnet flux, u d (k+1) and u q (k+1) are the dq axis voltages at time k+1, F ψd(k+1) and F ψq (k+1) are the disturbances of dq axis flux when the parameters are mismatched at time k+1.

[0031] Optionally, the torque value function g in step S4 1 The function expression is:

[0032]

[0033] In the above formula, ΔTe is the torque change, is the torque reference value, T e (k+2) is the torque prediction value at time k+2.

[0034] Optionally, in step S5, the magnetic link value function g 2 The function expression is:

[0035]

[0036] In the above formula, Δψ s is the flux change, is the flux reference value, ψ s (k+2) is the predicted value of magnetic flux at time k+2.

[0037] In addition, the present invention also provides a motor predictive control system based on disturbance compensation, comprising a microprocessor and a memory connected to each other, wherein the microprocessor is programmed or configured to execute the motor predictive control method based on disturbance compensation.

[0038] In addition, the present invention also provides a computer-readable storage medium, in which a computer program or instruction is stored. The computer program or instruction is programmed or configured to execute the motor predictive control method based on disturbance compensation through a processor.

[0039] In addition, the present invention also provides a computer program product, including a computer program or instructions, wherein the computer program or instructions are programmed or configured to execute the motor predictive control method based on disturbance compensation through a processor.

[0040] Compared with the prior art, the present invention mainly has the following advantages:

[0041] 1. The present invention includes estimating the disturbance caused by parameter mismatch through a sliding mode observer based on a variable exponential reaching law. The variable exponential reaching law adopted takes into account both improving the convergence speed and reducing the chattering. By introducing the system state into the reaching law and adding a sign function to the exponential reaching term, the convergence speed is accelerated when the system state is on the principle sliding mode surface, and the convergence speed is reduced when it is close to the sliding mode surface, thereby reducing the chattering.

[0042] 2. The present invention includes selecting in the voltage vector space such that the torque value function g 1 The first four voltage vectors with the smallest value are output to the flux value function g 2 As the optional reference voltage vector, then among these four reference voltage vectors, the flux linkage value function g is selected 2 The voltage vector with the smallest value is used as the final output to control the voltage vector of the permanent magnet synchronous motor. Through the above-mentioned serial method, a series structure is designed to divide the value function into two separate value functions of torque and flux, and the torque and flux are optimized separately, thereby removing the weight factor, avoiding the complex design process of the weight factor, and improving the control efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 Schematic diagram of the basic flow of the method of the embodiment of the present invention.

[0044] Figure 2 Schematic diagram of the control principle of an embodiment of the present invention.

[0045] Figure 3 1 is a simulation waveform diagram of the A-phase current of the permanent magnet synchronous motor when there is a double parameter mismatch in an embodiment of the present invention.

[0046] Figure 4 It is a simulation waveform diagram of the permanent magnet synchronous motor at twice the parameter mismatch speed in an embodiment of the present invention.

[0047] Figure 5 It is a simulation waveform diagram of the permanent magnet synchronous motor under double parameter mismatch torque in an embodiment of the present invention. DETAILED DESCRIPTION

[0048] like Figure 1 and Figure 2 As shown, the motor predictive control method based on disturbance compensation in this embodiment includes the following steps:

[0049] S1, through a sliding mode observer based on a variable exponential reaching law (named as a variable exponential sliding mode observer in this embodiment, specifically as Figure 2 As shown) to estimate the disturbance caused by parameter mismatch;

[0050] S2, compensating the disturbance into the prediction equations of current and flux to obtain the predicted current value and flux prediction value at time k+1;

[0051] S3, obtaining the torque prediction value at time k+1 based on the current prediction value at time k+1, and obtaining the torque prediction value and flux prediction value at time k+2 based on the delay compensation of the torque prediction value and flux prediction value at time k+1;

[0052] S4, bring the torque prediction value at time k+2 into the preset torque value function g1 , in the voltage vector space (including u 0-7 (k) Eight basic voltage vectors, such as Figure 2 As shown in the figure), select the torque value function g 1 The four voltage vectors with the smallest values ​​are used as candidate reference voltage vectors;

[0053] S5, bring the magnetic link value prediction at time k+2 into the preset magnetic link value function g 2 , select the four candidate reference voltage vectors so that the flux linkage value function g 2 The voltage vector with the smallest value is used as the final output to control the voltage vector of the permanent magnet synchronous motor.

[0054] In step S1 of this embodiment, the disturbance caused by parameter mismatch estimated by the sliding mode observer includes current disturbance and flux disturbance, and the function expression of the current disturbance observer used to observe the current disturbance is (taking the permanent magnet synchronous motor as an example):

[0055]

[0056] In the above formula, is the observed value of dq axis current, u dq is the dq axis voltage, is the dq axis current disturbance, S idq is the dq axis sliding mode function of the current, g idq is the dq axis sliding mode gain coefficient of the current, A, B and C are coefficient matrices, and:

[0057]

[0058] Among them, R s is the stator resistance, L d and L q is the dq axis inductance, ω e is the electrical angular velocity, ψ f is the permanent magnet flux; the function expression of the flux disturbance observer used to observe the flux disturbance is:

[0059]

[0060] In the above formula, is the observed value of dq-axis flux linkage, is the dq axis flux disturbance, S ψdq is the dq axis sliding mode function of the magnetic flux, g ψdq is the dq axis sliding mode gain coefficient of the flux linkage, A 1 and C 1 is a coefficient matrix, and has:

[0061]

[0062] S ψdq =[S ψd S ψq ] T , g ψdq =[g ψd g ψq ] T ;

[0063] And the function expression of the variable exponential reaching law adopted by the sliding mode observer is:

[0064]

[0065] In the above formula, is the derivative of the sliding surface s, ε, K, α and c are constant coefficients, e is the system state, τ and t are time. Figure 2 The representation F id and F iq They represent the dq axis current disturbances respectively The d-axis current disturbance in and q-axis current disturbance F ψd and F ψq They represent the dq axis flux disturbance respectively The d-axis flux disturbance in and q-axis flux disturbance

[0066] In step S2 of this embodiment, the disturbance is compensated into the prediction equation of current and flux to obtain the function expression of the current prediction value and flux prediction value at time k+1:

[0067]

[0068] In the above formula, i d (k+1) and i q (k+1) are the predicted values ​​of dq axis current at time k+1, Ts is the sampling period, Rs is the stator resistance, L d and L q are the dq axis inductance, i d (k) and i q (k) are the dq axis current values ​​at time k, ω e is the electrical angular velocity, u d (k) and u q (k) are the dq axis voltage at time k, ψ f is the permanent magnet flux, F id (k) and F iq (k) are the disturbances of dq axis current when the parameters are mismatched; ψ d (k+1) and ψ q(k+1) are the predicted values ​​of dq axis flux at time k+1, ψ d (k) and ψ q (k) are the dq axis flux values ​​at time k, F ψd (k) and F ψq (k) are the disturbances of dq axis flux when the parameters are mismatched at time k.

[0069] In step S3 of this embodiment, the function expression for obtaining the torque prediction value at time k+1 based on the current prediction value at time k+1 is:

[0070] T e (k+1)=(3 / 2)n p [ψ d (k+1)i q (k+1)-ψ q (k+1)i d (k+1)],

[0071] In the above formula, T e (k+1) is the torque prediction value at time k+1, n p is the number of magnetic pole pairs of the permanent magnet motor, i d (k+1) and i q (k+1) are the predicted values ​​of dq axis current at time k+1, ψ d (k+1) and ψ q (k+1) are the predicted values ​​of dq axis flux at time k+1 respectively.

[0072] In step S3 of this embodiment, the function expression of the torque prediction value and the flux prediction value at time k+2 obtained based on the delay compensation of the torque prediction value and the flux prediction value at time k+1 is:

[0073]

[0074]

[0075] In the above formula, T e (k+2) is the torque prediction value at time k+2, n p is the number of magnetic poles of the permanent magnet motor, ψ d (k+2) and ψ q (k+2) are the predicted values ​​of dq axis flux at time k+2, i d (k+2) and i q (k+2) are the predicted values ​​of dq axis current at time k+2, T s is the sampling period, R s is the stator resistance, L d and L q are the dq axis inductance, ψ d(k+1) and ψ q (k+1) are the predicted values ​​of dq axis flux at time k+1, ω e is the electrical angular velocity, ψ d and ψ q are the dq axis flux, ψ f is the permanent magnet flux, u d (k+1) and u q (k+1) are the dq axis voltages at time k+1, F ψd (k+1) and F ψq (k+1) are the disturbances of dq axis flux when the parameters are mismatched at time k+1.

[0076] In step S4 of this embodiment, the torque value function g 1 The function expression is:

[0077]

[0078] In the above formula, ΔTe is the torque change, is the torque reference value, T e (k+2) is the torque prediction value at time k+2. Figure 2 As shown, the torque reference value is the real-time electrical angular velocity ω e (k) and the reference electrical angular velocity The difference is obtained through the PI controller.

[0079] In step S5 of this embodiment, the magnetic link value function g 2 The function expression is:

[0080]

[0081] In the above formula, Δψ s is the flux change, ψ s ref is the flux reference value ( Figure 2 is obtained based on the existing MTPA method), ψ s (k+2) is the predicted value of magnetic flux at time k+2. Finally, by making the magnetic flux value function g 2 The voltage vector with the smallest value is used as the final output to control the voltage vector of the permanent magnet synchronous motor to generate the control signal S a,b,c Inverter that controls a permanent magnet synchronous motor.

[0082] Figure 3 The A-phase current simulation waveform of the permanent magnet synchronous motor when the parameter mismatch is twice after the motor predictive control method based on disturbance compensation of this embodiment is adopted. Figure 3 It can be seen that when the parameters do not match, the harmonic content of phase A current is small. Figure 4The simulation waveform of the permanent magnet synchronous motor at twice the parameter mismatch speed after the motor predictive control method based on disturbance compensation of this embodiment is shown in FIG. Figure 4 It can be seen that when the parameters do not match, the speed can be stabilized at 500r / min with small pulsation. Figure 5 The waveform diagram of the torque simulation of the permanent magnet synchronous motor under double parameter mismatch after the motor predictive control method based on disturbance compensation of this embodiment is shown in FIG. Figure 5 It can be seen that in the case of parameter mismatch, the torque ripple value is very small, which proves that the motor predictive control method based on disturbance compensation in this embodiment effectively improves the robustness.

[0083] In summary, the motor predictive control method based on disturbance compensation in this embodiment includes designing a sliding mode observer based on a variable exponential approach rate to estimate the disturbance caused by parameter mismatch, compensating the estimated disturbance value into the current and flux prediction equations, obtaining accurate current prediction values ​​and flux prediction values, and then obtaining accurate torque prediction values, and then optimizing the torque and flux in succession through a series structure, thereby avoiding a complex weight factor adjustment process. The motor predictive control method based on disturbance compensation in this embodiment can improve the robustness of the system when the resistance, inductance, and flux parameters of the permanent magnet synchronous motor are mismatched, and removes the weight factor, thereby improving the control efficiency.

[0084] In addition, this embodiment also provides a motor predictive control system based on disturbance compensation, including a microprocessor and a memory connected to each other, wherein the microprocessor is programmed or configured to execute the motor predictive control method based on disturbance compensation.

[0085] In addition, this embodiment also provides a computer-readable storage medium, in which a computer program or instruction is stored. The computer program or instruction is programmed or configured to execute the motor predictive control method based on disturbance compensation through a processor.

[0086] In addition, this embodiment also provides a computer program product, including a computer program or instructions, which are programmed or configured to execute the motor predictive control method based on disturbance compensation through a processor.

[0087] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the functions in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0088] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A motor predictive control method based on disturbance compensation, characterized in that: The steps include: S1, estimates the disturbance caused by parameter mismatch through a sliding mode observer based on a variable exponential reaching law; S2, compensating the disturbance into the prediction equations of current and flux to obtain the predicted current value and flux prediction value at time k+1; S3, obtaining the torque prediction value at time k+1 based on the current prediction value at time k+1, and obtaining the torque prediction value and flux prediction value at time k+2 based on the delay compensation of the torque prediction value and flux prediction value at time k+1; S4, bringing the torque prediction value at time k+2 into the preset torque value function g1, and selecting four voltage vectors that minimize the value of the torque value function g1 in the voltage vector space as candidate reference voltage vectors; S5, bringing the predicted flux value at time k+2 into the preset flux value function g2, and selecting the voltage vector that minimizes the flux value function g2 from the four candidate reference voltage vectors as the final output voltage vector for controlling the permanent magnet synchronous motor.

2. The motor predictive control method based on disturbance compensation according to claim 1, characterized in that: The disturbance caused by parameter mismatch estimated by the sliding mode observer in step S1 includes current disturbance and flux disturbance, and the function expression of the current disturbance observer used to observe the current disturbance is: In the above formula, is the observed value of dq axis current, u dq is the dq axis voltage, is the dq axis current disturbance, S idq is the dq axis sliding mode function of the current, g idq is the dq axis sliding mode gain coefficient of the current, A, B and C are coefficient matrices, and: Among them, R s is the stator resistance, L d and L q is the dq axis inductance, ω e is the electrical angular velocity, ψ f is the permanent magnet flux; the function expression of the flux disturbance observer used to observe the flux disturbance is: In the above formula, is the observed value of dq-axis flux linkage, is the dq axis flux disturbance, S ψdq is the dq axis sliding mode function of the magnetic flux, g ψdq is the dq axis sliding mode gain coefficient of the flux linkage, A1 and C1 are coefficient matrices, and: And the function expression of the variable exponential reaching law adopted by the sliding mode observer is: In the above formula, is the derivative of the sliding surface s, ε, K, α and c are constant coefficients, e is the system state, τ and t are time.

3. The motor predictive control method based on disturbance compensation according to claim 1, characterized in that: In step S2, the disturbance is compensated into the prediction equation of current and flux to obtain the function expression of the current prediction value and flux prediction value at time k+1: In the above formula, i d (k+1) and i q (k+1) are the predicted values ​​of dq axis current at time k+1, Ts is the sampling period, Rs is the stator resistance, L d and L q are the dq axis inductance, i d (k) and i q (k) are the dq axis current values ​​at time k, ω e is the electrical angular velocity, u d (k) and u q (k) are the dq axis voltage at time k, ψ f is the permanent magnet flux, F id (k) and F iq (k) are the disturbances of dq axis current when the parameters are mismatched; ψ d (k+1) and ψ q (k+1) are the predicted values ​​of dq axis flux at time k+1, ψ d (k) and ψ q (k) are the dq axis flux values ​​at time k, F ψd (k) and F ψq (k) are the disturbances of dq axis flux when the parameters are mismatched at time k.

4. The motor predictive control method based on disturbance compensation according to claim 1, characterized in that: In step S3, the function expression for obtaining the torque prediction value at time k+1 based on the current prediction value at time k+1 is: T e (k+1)=(3 / 2)n p [ψ d (k+1)i q (k+1)-ψ q (k+1)i d (k+1)], In the above formula, T e (k+1) is the torque prediction value at time k+1, n p is the number of magnetic pole pairs of the permanent magnet motor, i d (k+1) and i q (k+1) are the predicted values ​​of dq axis current at time k+1, ψ d (k+1) and ψ q (k+1) are the predicted values ​​of dq axis flux at time k+1 respectively.

5. The motor predictive control method based on disturbance compensation according to claim 1, characterized in that: In step S3, the function expression of the torque prediction value and flux prediction value at time k+2 obtained by delay compensation based on the torque prediction value and flux prediction value at time k+1 is: In the above formula, T e (k+2) is the torque prediction value at time k+2, n p is the number of magnetic poles of the permanent magnet motor, ψ d (k+2) and ψ q (k+2) are the predicted values ​​of dq axis flux at time k+2, i d (k+2) and i q (k+2) are the predicted values ​​of dq axis current at time k+2, T s is the sampling period, R s is the stator resistance, L d and L q are the dq axis inductance, ψ d (k+1) and ψ q (k+1) are the predicted values ​​of dq axis flux at time k+1, ω e is the electrical angular velocity, ψ d and ψ q are the dq axis flux, ψ f is the permanent magnet flux, u d (k+1) and u q (k+1) are the dq axis voltages at time k+1, F ψd (k+1) and F ψq (k+1) are the disturbances of dq axis flux when the parameters are mismatched at time k+1.

6. The motor predictive control method based on disturbance compensation according to claim 1, characterized in that: The function expression of the torque value function g1 in step S4 is: In the above formula, ΔTe is the torque change, is the torque reference value, T e (k+2) is the torque prediction value at time k+2.

7. The motor predictive control method based on disturbance compensation according to claim 1, characterized in that: The function expression of the magnetic link value function g2 in step S5 is: In the above formula, Δψ s is the flux change, is the flux reference value, ψ s (k+2) is the predicted value of magnetic flux at time k+2.

8. A motor predictive control system based on disturbance compensation, comprising a microprocessor and a memory connected to each other, characterized in that: The microprocessor is programmed or configured to execute the motor predictive control method based on disturbance compensation as claimed in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program or instruction stored therein, characterized in that: The computer program or instruction is programmed or configured to execute the motor predictive control method based on disturbance compensation according to any one of claims 1 to 7 through a processor.

10. A computer program product comprising a computer program or instructions, characterized in that The computer program or instruction is programmed or configured to execute the motor predictive control method based on disturbance compensation according to any one of claims 1 to 7 through a processor.

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