A motor predictive control method and system based on disturbance compensation and a medium
By estimating motor parameter mismatch disturbances using a sliding mode observer based on a variable exponential reaching law, and optimizing the predicted values of torque and flux linkage, the problems of insufficient robustness and complex weight factor tuning in model predictive torque control are solved, and efficient control under parameter mismatch is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUNAN UNIV
- Filing Date
- 2024-10-15
- Publication Date
- 2026-06-12
AI Technical Summary
Existing model predictive torque control is not robust enough in the face of motor parameter mismatch, and the weighting factor tuning is complicated, making it difficult to achieve optimal control under different conditions.
A sliding mode observer based on a variable exponential reaching law is used to estimate the disturbance caused by parameter mismatch. The torque and flux prediction values are optimized through disturbance compensation. A series structure is designed to remove the weighting factor and select the optimal voltage vector for control.
It improves the robustness of permanent magnet synchronous motors under parameter mismatch conditions, simplifies the weight factor adjustment process, and improves control efficiency and stability.
Smart Images
Figure CN119519496B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of control technology for permanent magnet synchronous motors, and specifically to a predictive control method, system, and medium for motors based on disturbance compensation. Background Technology
[0002] In recent years, Model Predictive Control (MMCC), as a representative of high-performance control strategies, has received increasing attention. Generally, based on different control objectives, MMCC can be mainly divided into three categories: Model Predictive Current Control (MMDC), Model Predictive Speed Control (MMSC), and Model Predictive Torque Control (MMTC). Among them, MMTC is a control strategy that combines MMCC with Direct Torque Control (DTC) and plays a crucial role in motor drive systems. Traditional MMTC constructs a cost function for torque and flux linkage, and then uses this cost function to select the optimal voltage vector. However, for MMTC, excellent tracking control performance is highly dependent on an accurate motor model, especially accurate electrical and mechanical parameters. Due to changes in the operating environment and motor aging, motor parameters deviate from their original values, and parameter mismatch will destroy transient tracking performance, leading to errors in torque and flux linkage, and in more severe cases, potentially causing the entire control system to collapse. Therefore, how to cope with parameter disturbances and improve robustness is a major challenge for MMTC. Furthermore, weight factor tuning is another major challenge for MMTC. For model predictive torque control, a weighting factor needs to be designed to balance torque deviation and flux deviation. However, since different conditions require different weighting factors, adjusting the weighting factor is a very tedious task. Current strategies for addressing this problem generally include weighting factor self-tuning and weighting factor elimination. While weighting factor self-tuning can obtain the optimal weighting factor through real-time adjustment as conditions change, its implementation requires complex algorithms and a huge computational load. Weighting factor elimination is a feasible method for solving the weighting factor adjustment problem. By transforming the cost function equation or optimizing torque and flux separately, the weighting factor is no longer needed. However, this method usually requires precise motor parameters and has poor robustness to parameter mismatches. Summary of the Invention
[0003] The technical problem to be solved by this invention is to provide a motor predictive control method, system and medium based on disturbance compensation, which addresses the above-mentioned problems in the prior art. This invention aims to improve the robustness of motor control in the case of mismatch in resistance, inductance and flux linkage parameters of permanent magnet synchronous motors.
[0004] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:
[0005] A predictive control method for motors based on disturbance compensation includes the following steps:
[0006] S1, using a sliding mode observer based on a variable exponential reaching law to estimate the perturbation caused by parameter mismatch;
[0007] S2, the disturbance is compensated into the prediction equations for current and flux linkage to obtain the predicted values of current and flux linkage at time k+1.
[0008] S3, obtain the torque prediction value at time k+1 based on the current prediction value at time k+1, and obtain the torque prediction value and flux prediction value at time k+2 based on the torque prediction value and flux prediction value at time k+1 after delay compensation.
[0009] S4, Substitute the predicted torque value at time k+2 into the preset torque value function g1, and select the four voltage vectors in the voltage vector space that minimize the value of the torque value function g1 as candidate reference voltage vectors.
[0010] S5. The predicted flux linkage value at time k+2 is substituted into the preset flux linkage value function g2. Among the four candidate reference voltage vectors, the voltage vector that minimizes the value of the flux linkage value function g2 is selected as the final output voltage vector used to control the permanent magnet synchronous motor.
[0011] Optionally, the disturbances caused by parameter mismatch estimated by the sliding mode observer in step S1 include current disturbances and flux disturbances, and the functional expression of the current disturbance observer used to observe the current disturbance is:
[0012]
[0013] In the above formula, For the dq-axis current observation, u dq This is the dq-axis voltage. For dq-axis current disturbance, S idq Let g be the dq-axis sliding mode function of the current. idq Let be the dq-axis sliding mode gain coefficient of the current, and A, B, and C be coefficient matrices, and we have:
[0014]
[0015] Among them, R s L is the stator resistance. d and L q For the dq axis inductance, ω e Let ψ be the electric angular velocity. f For permanent magnet flux linkage; the functional expression of the flux linkage disturbance observer used to observe flux linkage disturbance is:
[0016]
[0017] In the above formula, The flux linkage observations are for the dq axis. For the dq-axis flux disturbance, S ψdq Let g be the dq-axis sliding mode function of the flux linkage. ψdq Let A1 and C1 be the sliding mode gain coefficients of the magnetic flux linkage along the dq axis, and let A1 and C1 be the coefficient matrices, and we have:
[0018]
[0019] Furthermore, the function expression of the variable exponential reaching law used in the sliding mode observer is:
[0020]
[0021] In the above formula, Let be the derivative of the sliding surface s, ε, K, α and c are constant coefficients, e is the system state, and τ and t are time.
[0022] Optionally, in step S2, the function expressions for compensating for the disturbance in the prediction equations of current and flux linkage to obtain the predicted values of current and flux linkage at time k+1 are as follows:
[0023]
[0024] In the above formula, i d (k+1) and i q (k+1) represent the predicted dq-axis current values at time k+1, Ts is the sampling period, Rs is the stator resistance, and L d and L q These are the d-axis and q-axis inductances, respectively, i d (k) and i q (k) represents the dq-axis current value at time k, ω e Let u be the electric angular velocity. d (k) and u q (k) represents the dq-axis voltage at time k, ψ f For permanent magnet flux linkage, F id (k) and F iq (k) represent the disturbances in the dq-axis currents due to parameter mismatch; ψ d (k+1) and ψ q (k+1) represent the predicted flux linkage along the dq axis at time k+1, and ψ d (k) and ψ q (k) represents the dq-axis flux linkage value at time k, F ψd (k) and F ψq (k) represents the disturbance of the dq axis flux linkage at time k due to parameter mismatch.
[0025] Optionally, the function expression for obtaining the torque prediction value at time k+1 based on the current prediction value at time k+1 in step S3 is as follows:
[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 predicted torque value at time k+1, n p Let i be the number of pole pairs of the permanent magnet motor. d (k+1) and i q (k+1) represent the predicted dq-axis current values at time k+1, ψ d (k+1) and ψ q (k+1) represents the predicted flux linkage values of the dq axis at time k+1.
[0028] Optionally, the functional expression for 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 in step S3 is as follows:
[0029]
[0030] In the above formula, T e (k+2) is the predicted torque value at time k+2, n p Let ψ be the number of pole pairs of the permanent magnet motor. d (k+2) and ψ q (k+2) represent the predicted flux linkage values along the dq axis at time k+2, i d (k+2) and i q (k+2) represent the predicted dq-axis current values at time k+2, and T s R is the sampling period. s L is the stator resistance. d and L q These are the d-q axis inductances, ψ d (k+1) and ψ q (k+1) represent the predicted flux linkage along the dq axis at time k+1, and ω e Let ψ be the electric angular velocity. d and ψ q These are the flux linkages along the dq axes, and ψ f For permanent magnet flux linkage, u d (k+1) and u q (k+1) represent the dq-axis voltages at time k+1, F ψd (k+1) and F ψq (k+1) represents the disturbance of the dq axis flux linkage at time k+1 due to parameter mismatch.
[0031] Optionally, the expression for the torque value function g1 in step S4 is:
[0032]
[0033] In the above formula, ΔTe represents the change in torque. T is the torque reference value. e (k+2) is the predicted torque value at time k+2.
[0034] Optionally, the functional expression of the magnetic flux linkage value function g2 in step S5 is:
[0035]
[0036] In the above formula, Δψ s This represents the change in magnetic flux. ψ is the reference value for magnetic flux linkage. s (k+2) is the predicted flux linkage value at time k+2.
[0037] Furthermore, the present invention also provides a motor predictive control system based on disturbance compensation, including a microprocessor and a memory interconnected thereto, wherein the microprocessor is programmed or configured to execute the motor predictive control method based on disturbance compensation.
[0038] Furthermore, the present invention also provides a computer-readable storage medium storing a computer program or instructions that are programmed or configured to execute the disturbance-compensated motor predictive control method by a processor.
[0039] In addition, the present invention also provides a computer program product, including a computer program or instructions, which are programmed or configured to execute the disturbance compensation-based motor predictive control method by a processor.
[0040] Compared with the prior art, the present invention has the following main advantages:
[0041] 1. The present invention includes estimating disturbances caused by parameter mismatch by using a sliding mode observer based on a variable exponential reaching law. The variable exponential reaching law takes into account both improving the convergence speed and reducing 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 sliding surface and reduced when it is close to the sliding surface, thereby reducing chattering.
[0042] 2. This invention includes selecting the four voltage vectors in the voltage vector space that minimize the torque value function g1 and outputting them to the flux linkage value function g2 as selectable reference voltage vectors. Then, among these four reference voltage vectors, the voltage vector that minimizes the flux linkage value function g2 is selected as the final output voltage vector used to control the permanent magnet synchronous motor. Through the above serial approach, a series structure is designed to divide the value function into two separate value functions: torque and flux linkage. The torque and flux linkage are optimized separately, thereby eliminating the weighting factor, avoiding the complex design process of the weighting factor, and improving control efficiency. Attached Figure Description
[0043] Figure 1 This is a schematic diagram of the basic process of the method in an embodiment of the present invention.
[0044] Figure 2 This is a schematic diagram of the control principle of an embodiment of the present invention.
[0045] Figure 3 This is a simulation waveform of the A-phase current of the permanent magnet synchronous motor in an embodiment of the present invention when there is a two-fold parameter mismatch.
[0046] Figure 4 This is a simulation waveform of the permanent magnet synchronous motor at twice the parameter mismatch speed in an embodiment of the present invention.
[0047] Figure 5 This is a simulation waveform diagram of the permanent magnet synchronous motor under two times parameter mismatch torque in an embodiment of the present invention. Detailed Implementation
[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, using a sliding mode observer based on a variable exponential reaching law (named the variable exponential sliding mode observer in this embodiment, specifically as follows) Figure 2 (As shown) to estimate the disturbance caused by parameter mismatch;
[0050] S2, the disturbance is compensated into the prediction equations for current and flux linkage to obtain the predicted values of current and flux linkage at time k+1.
[0051] S3, obtain the torque prediction value at time k+1 based on the current prediction value at time k+1, and obtain the torque prediction value and flux prediction value at time k+2 based on the torque prediction value and flux prediction value at time k+1 after delay compensation.
[0052] S4, substitute the predicted torque 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) Select the four voltage vectors that minimize the value of the torque value function g1 as candidate reference voltage vectors;
[0053] S5. The predicted flux linkage value at time k+2 is substituted into the preset flux linkage value function g2. Among the four candidate reference voltage vectors, the voltage vector that minimizes the value of the flux linkage value function g2 is selected as the final output voltage vector used to control the permanent magnet synchronous motor.
[0054] In step S1 of this embodiment, the disturbances estimated by the sliding mode observer due to parameter mismatch include current disturbances and flux disturbances, and the functional expression of the current disturbance observer used to observe the current disturbance is as follows (taking a permanent magnet synchronous motor as an example):
[0055]
[0056] In the above formula, For the dq-axis current observation, u dq This is the dq-axis voltage. For dq-axis current disturbance, S idq Let g be the dq-axis sliding mode function of the current. idq Let be the dq-axis sliding mode gain coefficient of the current, and A, B, and C be coefficient matrices, and we have:
[0057]
[0058] Among them, R s L is the stator resistance. d and L q For the dq axis inductance, ω e Let ψ be the electric angular velocity. f For permanent magnet flux linkage; the functional expression of the flux linkage disturbance observer used to observe flux linkage disturbance is:
[0059]
[0060] In the above formula, The flux linkage observations are for the dq axis. For the dq-axis flux disturbance, S ψdq Let g be the dq-axis sliding mode function of the flux linkage. ψdq Let A1 and C1 be the sliding mode gain coefficients of the magnetic flux linkage along the dq axis, and let A1 and C1 be the coefficient matrices, and we have:
[0061]
[0062] S ψdq =[S ψd S ψq ] T g ψdq=[g ψd g ψq ] T ;
[0063] Furthermore, the function expression of the variable exponential reaching law used in the sliding mode observer is:
[0064]
[0065] In the above formula, Let be the derivative of the sliding surface s, ε, K, α and c are constant coefficients, e is the system state, and τ and t are time. Figure 2 The representation of F in id and F iq These represent the dq-axis current disturbances, respectively. d-axis current disturbance and q-axis current disturbance F ψd and F ψq These represent the flux linkage disturbances along the d and q axes, respectively. d-axis flux perturbation and q-axis flux disturbance
[0066] In step S2 of this embodiment, the function expressions for compensating for the disturbance in the prediction equations of current and flux linkage to obtain the predicted values of current and flux linkage at time k+1 are as follows:
[0067]
[0068] In the above formula, i d (k+1) and i q (k+1) represent the predicted dq-axis current values at time k+1, Ts is the sampling period, Rs is the stator resistance, and L d and L q These are the d-axis and q-axis inductances, respectively, i d (k) and i q (k) represents the dq-axis current value at time k, ω e Let u be the electric angular velocity. d (k) and u q (k) represents the dq-axis voltage at time k, ψ f For permanent magnet flux linkage, F id (k) and F iq (k) represent the disturbances in the dq-axis currents due to parameter mismatch; ψ d (k+1) and ψ q (k+1) represent the predicted flux linkage along the dq axis at time k+1, and ψ d (k) and ψ q (k) represents the dq-axis flux linkage value at time k, F ψd (k) and Fψq (k) represents the disturbance of the dq axis flux linkage at time k due to parameter mismatch.
[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 as follows:
[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 predicted torque value at time k+1, n p Let i be the number of pole pairs of the permanent magnet motor. d (k+1) and i q (k+1) represent the predicted dq-axis current values at time k+1, ψ d (k+1) and ψ q (k+1) represents the predicted flux linkage values of the dq axis at time k+1.
[0072] In step S3 of this embodiment, the function expression for obtaining the torque prediction value and flux linkage prediction value at time k+2 based on the delay compensation of the torque prediction value and flux linkage prediction value at time k+1 is as follows:
[0073]
[0074]
[0075] In the above formula, T e (k+2) is the predicted torque value at time k+2, n p Let ψ be the number of pole pairs of the permanent magnet motor. d (k+2) and ψ q (k+2) represent the predicted flux linkage values along the dq axis at time k+2, i d (k+2) and i q (k+2) represent the predicted dq-axis current values at time k+2, and T s R is the sampling period. s L is the stator resistance. d and L q These are the d-q axis inductances, ψ d (k+1) and ψ q (k+1) represent the predicted flux linkage along the dq axis at time k+1, and ω e Let ψ be the electric angular velocity. d and ψ qThese are the flux linkages along the dq axes, and ψ f For permanent magnet flux linkage, u d (k+1) and u q (k+1) represent the dq-axis voltages at time k+1, F ψd (k+1) and F ψq (k+1) represents the disturbance of the dq axis flux linkage at time k+1 due to parameter mismatch.
[0076] The expression for the torque value function g1 in step S4 of this embodiment is as follows:
[0077]
[0078] In the above formula, ΔTe represents the change in torque. T is the torque reference value. e (k+2) represents the predicted torque value at time k+2. For example... Figure 2 As shown, the torque reference value is the real-time electric angular velocity ω. e (k) and reference electric angular velocity The difference is obtained through a PI controller.
[0079] The expression for the magnetic flux linkage value function g2 in step S5 of this embodiment is as follows:
[0080]
[0081] In the above formula, Δψ s Let ψ be the change in magnetic flux. s ref Reference value for magnetic flux ( Figure 2 (To be obtained based on the existing MTPA method), ψ s (k+2) represents the predicted flux linkage value at time k+2. Finally, the voltage vector that minimizes the flux linkage value function g2 is used as the final output to generate the control signal S for the permanent magnet synchronous motor. a,b,c An inverter that controls a permanent magnet synchronous motor.
[0082] Figure 3 The image shows the simulated waveform of the A-phase current of the permanent magnet synchronous motor under a double parameter mismatch after adopting the motor predictive control method based on disturbance compensation in this embodiment. Figure 3 It can be seen that, under the condition of parameter mismatch, the harmonic content of phase A current is relatively small. Figure 4 The image shows the simulated waveform of a permanent magnet synchronous motor at twice the parameter mismatch speed after adopting the motor predictive control method based on disturbance compensation in this embodiment. Figure 4 It can be seen that, even with mismatched parameters, the rotational speed can be stabilized at 500 r / min with minimal pulsation. Figure 5The image shows the simulated waveform of the permanent magnet synchronous motor under double parameter mismatch torque after adopting the motor predictive control method based on disturbance compensation in this embodiment. Figure 5 It can be seen that the torque ripple value is very small when the parameters are mismatched, proving that the motor predictive control method based on disturbance compensation in this embodiment effectively improves 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 disturbances caused by parameter mismatch. The estimated disturbance value is then compensated into the current and flux linkage prediction equations to obtain accurate current and flux linkage prediction values, which in turn lead to accurate torque prediction values. Finally, a series structure is used to optimize torque and flux linkage sequentially, thereby avoiding a complex weight factor adjustment process. This motor predictive control method based on disturbance compensation in this embodiment can improve the robustness of the system under the condition of parameter mismatch in resistance, inductance, and flux linkage of permanent magnet synchronous motors, and it also removes weight factors, thereby improving control efficiency.
[0084] Furthermore, this embodiment also provides a motor predictive control system based on disturbance compensation, including a microprocessor and a memory interconnected, wherein the microprocessor is programmed or configured to execute the motor predictive control method based on disturbance compensation.
[0085] Furthermore, this embodiment also provides a computer-readable storage medium storing a computer program or instructions that are programmed or configured to execute the disturbance-compensated motor predictive control method by 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 disturbance compensation-based motor predictive control method by a processor.
[0087] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0088] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.
Claims
1. A predictive control method for motors based on disturbance compensation, characterized in that, Includes the following steps: S1, using a sliding mode observer based on a variable exponential reaching law to estimate the perturbation caused by parameter mismatch; S2, the disturbance is compensated into the prediction equations for current and flux linkage to obtain the predicted values of current and flux linkage at time k+1. S3, obtain the torque prediction value at time k+1 based on the current prediction value at time k+1, and obtain the torque prediction value and flux prediction value at time k+2 based on the torque prediction value and flux prediction value at time k+1 after delay compensation. S4, Substitute the predicted torque value at time k+2 into the preset torque value function g1, and select the four voltage vectors in the voltage vector space that minimize the value of the torque value function g1 as candidate reference voltage vectors. S5, the predicted flux linkage value at time k+2 is substituted into the preset flux linkage value function g2, and the voltage vector that minimizes the value of the flux linkage value function g2 is selected from the four candidate reference voltage vectors as the final output voltage vector used to control the permanent magnet synchronous motor. In step S1, the disturbances estimated by the sliding mode observer due to parameter mismatch include current disturbances and flux disturbances, and the functional expression of the current disturbance observer used to observe the current disturbance is: ， In the above formula, These are the observed values of the dq-axis current. For dq axis voltage, For dq axis current disturbance. Let dq be the sliding mode function of the current. Let be the dq-axis sliding mode gain coefficient of the current. , and Let be the coefficient matrix, and we have: ， ， ， in, For stator resistance, and For dq axis inductance, Electric angular velocity, For permanent magnet flux linkage; the functional expression of the flux linkage disturbance observer used to observe flux linkage disturbance is: ， In the above formula, The flux linkage observations are for the dq axis. For dq axis flux disturbance. Let dq be the sliding mode function of the magnetic flux linkage. Let dq be the sliding mode gain coefficient of the magnetic flux linkage. and Let be the coefficient matrix, and we have: ， ； Furthermore, the function expression of the variable exponential reaching law used in the sliding mode observer is: ， ， In the above formula, For sliding surface The derivative of , , and The constant coefficients, For system status, and For time.
2. The motor predictive control method based on disturbance compensation according to claim 1, characterized in that, In step S2, the perturbation is compensated into the prediction equations for current and flux linkage, resulting in the following functional expressions for the predicted current and flux linkage values at time k+1: ， ， In the above formula, and These are the predicted dq-axis current values at time k+1. The sampling period is For stator resistance, and These are the d-q axis inductors, and These are the dq-axis current values at time k. Electric angular velocity, and Let be the dq-axis voltages at time k. For permanent magnet flux linkage, and These represent the disturbances in the dq-axis currents due to parameter mismatch. and These are the predicted values of the dq-axis flux linkage at time k+1. and Let be the dq axis flux linkage values at time k, respectively. and These represent the disturbances in the flux linkage along the dq axes at time k due to parameter mismatch.
3. The motor predictive control method based on disturbance compensation according to claim 1, characterized in that, The function expression for obtaining the torque prediction value at time k+1 based on the current prediction value at time k+1 in step S3 is as follows: ， In the above formula, This is the predicted torque value at time k+1. is the number of pole pairs in a permanent magnet motor. and These are the predicted dq-axis current values at time k+1. and These are the predicted flux linkage values along the dq axis at time k+1.
4. The motor predictive control method based on disturbance compensation according to claim 1, characterized in that, The functional expression for obtaining the torque prediction value and flux linkage prediction value at time k+2 based on the delay compensation of the torque prediction value and flux linkage prediction value at time k+1 in step S3 is as follows: ， ， In the above formula, This is the predicted torque value at time k+2. is the number of pole pairs in a permanent magnet motor. and These are the predicted dq-axis flux linkage values at time k+2. and These are the predicted dq-axis current values at time k+2. The sampling period is For stator resistance, and These are the d-q axis inductors, and These are the predicted values of the dq-axis flux linkage at time k+1. Electric angular velocity, and These are the magnetic flux linkages along the d and q axes, It is a permanent magnet flux linkage. and Let be the dq-axis voltages at time k+1. and These represent the disturbances in the flux linkage along the dq axis at time k+1 due to parameter mismatch.
5. The motor predictive control method based on disturbance compensation according to claim 1, characterized in that, The expression for the torque value function g1 in step S4 is as follows: In the above formula, This is the change in torque. This is a torque reference value. This is the predicted torque value at time k+2.
6. The motor predictive control method based on disturbance compensation according to claim 1, characterized in that, The expression for the flux linkage value function g2 in step S5 is as follows: In the above formula, This represents the change in magnetic flux. This is the reference value for magnetic flux linkage. This is the predicted flux linkage value at time k+2.
7. A motor predictive control system based on disturbance compensation, comprising a microprocessor and a memory interconnected, characterized in that, The microprocessor is programmed or configured to execute the motor predictive control method based on disturbance compensation as described in any one of claims 1 to 6.
8. A computer-readable storage medium storing a computer program or instructions, characterized in that, The computer program or instructions are programmed or configured to execute the motor predictive control method based on disturbance compensation as described in any one of claims 1 to 6 via a processor.
9. A computer program product, comprising a computer program or instructions, characterized in that, The computer program or instructions are programmed or configured to execute the motor predictive control method based on disturbance compensation as described in any one of claims 1 to 6 via a processor.