Error compensation PMSM three-vector model prediction flux linkage control system and control method

Abstract

The PMSM three-vector model prediction flux linkage control system for error compensation comprises a signal detection circuit, a main circuit and a control circuit, and the control circuit processes a signal obtained by the signal detection circuit and further controls the main circuit; according to the error compensation PMSM three-vector model prediction flux linkage control method, on the basis of a permanent magnet synchronous motor mathematical model, flux linkage control variables are selected again, so that control is simple and easy to implement, and the influence of a reference load angle on model prediction flux linkage control is reduced; meanwhile, a flux linkage prediction error compensator is designed for the conditions of parameter change and system unmodeled dynamic disturbance, an error compensation value is calculated, error compensation is carried out on the three-vector model prediction flux linkage, and the robustness of permanent magnet synchronous motor model prediction flux linkage control is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of motor control, and relates to a PMSM three-vector model predictive flux control system with error compensation, and also relates to a control method for the above system. Background Art

[0002] Permanent magnet synchronous motors are widely used in electric vehicles, rail transit, numerical control machine tools, high-end washing machines, industrial robots and other fields due to their advantages such as high power density, large torque inertia ratio, simple structure and small volume. In order to achieve accurate control of permanent magnet synchronous motors, their control strategies have become a research hotspot for many scholars, including vector control, direct torque control and model predictive control. Among them, model predictive control has the advantages of intuitive and simple principle, high dynamic performance and easy implementation of multivariable constraints, and has received extensive attention in recent years.

[0003] The main idea of model predictive control is to predict the state of the system at the next moment based on the mathematical model of the controlled object according to the state value of the system at the current moment, perform online optimization by constructing a cost function, determine the optimal control sequence, and apply this control sequence to the control system. Model predictive control can be divided into model predictive current control, model predictive torque control, model predictive flux control and model predictive speed control according to different control objectives. Model predictive flux control takes the stator flux vector as the control target, without weight coefficients, and has fast dynamic response and good steady-state performance. However, in the model predictive flux control method, the given value of the equivalent stator flux is the permanent magnet flux value, the calculation of the load angle contains motor parameters, and the prediction equation is based on the mathematical model, so it has a large dependence on motor parameters; in practical applications, the actual values of motor parameters will be inconsistent with the nominal values on the motor nameplate due to factors such as temperature change and magnetic circuit saturation, and the model predictive flux control does not consider the unmodeled dynamic disturbance of the system, thus causing a steady-state error between the given value and the actual value of the flux, and ultimately affecting the performance of the system and resulting in poor system robustness. At present, the main methods to improve the parameter robustness of model predictive control are to observe the disturbance by a disturbance observer, motor parameter identification, model-free predictive control, etc. Among these methods, the method of the disturbance observer increases the complexity of the system, and at the same time, the parameters of the observer need to be adjusted; parameter identification is too dependent on the identification accuracy, increasing uncertainty; there are mainly two model-free predictive control methods, model-free predictive control based on superlocal and model-free predictive control based on current difference. In the superlocal-based method, there is still a problem of parameter tuning, while the current difference has the disadvantages of update stagnation and large storage capacity. Therefore, in view of the above problems, it is necessary to study an effective method to improve the robustness of model predictive flux control without increasing the complexity of the system and without parameter tuning. Summary of the Invention

[0004] The object of the present invention is to provide a PMSM three-vector model predictive flux control system with error compensation, which solves the problems of sensitivity of model predictive flux control to parameter changes and robustness problems caused by unmodeled dynamic disturbances in the system.

[0005] Another object of the present invention is to provide a control method for PMSM three-vector model predictive flux control with error compensation.

[0006] The technical solution adopted by the present invention is that a PMSM three-vector model predictive flux control system with error compensation includes a three-phase inverter for driving a permanent magnet synchronous motor, a current detection circuit for sampling the stator current of the permanent magnet synchronous motor, and a rotary encoder for measuring the rotor position angle of the permanent magnet synchronous motor. The output end of the current detection circuit is sequentially connected to a Clark transformation module, a Park transformation module, and a flux linkage value calculation module. The flux linkage value calculation module is respectively connected to a flux linkage prediction error compensation module, a flux linkage prediction module, and an action time calculation module. The flux linkage prediction error compensation module is mutually connected to the flux linkage prediction module and the action time calculation module. The action time calculation module is sequentially connected to an expected vector synthesis module and a cost function optimization module. The flux linkage prediction module is also connected to the cost function optimization module. The cost function optimization module is connected to the three-phase inverter. The optical encoder is connected to the action time calculation module through a digital PI controller.

[0007] The features of the present invention also lie in: The rotary encoder is also connected to the Park transformation module.

[0008] Another technical solution adopted by the present invention is a control method for PMSM three-vector model predictive flux control with error compensation. Using the above-mentioned PMSM three-vector model predictive flux control system with error compensation, the steps are as follows: Step 1, establish a mathematical model of the permanent magnet synchronous motor; Step 2, select a new flux linkage control variable, construct a cost function and calculate the flux linkage prediction equation of the permanent magnet synchronous motor; Step 3, design a flux linkage error compensation controller, add the error compensation value to the flux linkage prediction equation of the permanent magnet synchronous motor, and calculate the flux linkage prediction value; Step 4, the action time calculation module calculates the action time of the voltage vector, synthesizes the expected voltage vector through the expected vector synthesis module, and selects the optimal voltage vector to act on the three-phase inverter through the cost function with the flux linkage prediction value and the expected voltage vector to control the permanent magnet synchronous motor.

[0009] The features of another technical solution of the present invention also lie in: In step 1, the mathematical model of the permanent magnet synchronous motor is as follows: (1) (2) (3) (4) (5) Equation (1) In (5), is the direct-axis component of the stator voltage, is the quadrature-axis component of the stator voltage; is the stator resistance; is the direct-axis component of the stator current, is the quadrature-axis component of the stator current; is the rotor electrical angular velocity; is the direct-axis component of the stator flux linkage, is the quadrature-axis component of the stator flux linkage; is the time; is the direct-axis component of the stator inductance, is the quadrature-axis component of the stator inductance; is the permanent magnet flux linkage; is the electromagnetic torque; is the number of pole pairs of the motor.

[0010] The specific process of step 2 is as follows: According to the mathematical model of the permanent magnet synchronous motor, let , and the discretization using the backward Euler method gives: (6) In the formula: is the predicted value of the direct-axis flux linkage at time ( ); is the predicted value of the equivalent direct-axis flux linkage at time ( ); is the actual value of the quadrature-axis flux linkage at time; is the direct-axis component of the stator voltage at time ; Equation (6) is equivalent to controlling the variable with respect to the direct-axis flux linkage . By adopting new flux linkage control variables , for the model predictive flux linkage control of the permanent magnet synchronous motor, the value function can be reconstructed as: (7) In the formula, is the given value of the variable . According to i d = 0 control, ; and The calculation formulas are as follows: (8) (9) In the formula, is the quadrature-axis component of the stator voltage at moment.

[0012] The specific process of Step 3 is as follows: Step 3.1, sample the phase currents , , of the permanent magnet synchronous motor through the current detection circuit, and convert them to the currents in the two-phase stationary , coordinate system through the Clark transformation module; Step 3.2, collect the rotor position angle of the permanent magnet synchronous motor through the rotary encoder, and differentiate the rotor position angle to obtain the mechanical angular velocity of the permanent magnet synchronous motor; Step 3.3, convert the rotor position angle and the currents in the two-phase stationary coordinate system to the direct-axis current and quadrature-axis current in the two-phase rotating coordinate system through the Park transformation module (6); Step 3.4, obtain the actual value of the equivalent direct-axis magnetic flux and the actual value of the quadrature-axis magnetic flux through the magnetic flux calculation module from the direct-axis current and the quadrature-axis current ; Step 3.5, design a magnetic flux error compensation controller in the magnetic flux prediction error compensation module, input and into the magnetic flux prediction error compensation module, and calculate the error compensation value ; Step 3.6, input and into the over-magnetic flux prediction equation of the magnetic flux prediction module, and calculate the magnetic flux prediction value .

[0013] The process of obtaining the error compensation value is as follows: First, design a direct-axis magnetic flux prediction error compensator : (10) Among them, is the actual value of the equivalent direct-axis flux linkage at time is the predicted error compensation value of the equivalent direct-axis flux linkage at time is the predicted error compensation coefficient of the equivalent direct-axis flux linkage; in Equation (10), the predicted error compensator of the equivalent direct-axis flux linkage consists of two parts. The first part is the square of the difference between the predicted value of the equivalent direct-axis flux linkage and the actual value of the equivalent direct-axis flux linkage. The second part is at time and the square of the difference between the predicted error compensation values of the equivalent direct-axis flux linkage at time When the above two parts are both 0, it indicates that the error compensation value no longer changes and the error between the predicted value and the actual value of the direct-axis flux linkage is 0; taking the partial derivative of with respect to (11) Let Equation (11) be 0, and the value of when it is the smallest can be obtained, that is: (12) Let Equation (12) be written as: (13) Secondly, design the quadrature-axis flux linkage predicted error compensator : (14) In Equation (14), is the actual value of the quadrature-axis flux linkage at time is the predicted error compensation value of the quadrature-axis flux linkage at time is the predicted error compensation coefficient of the quadrature-axis flux linkage; in Equation (14), the predicted error compensator of the quadrature-axis flux linkage consists of two parts. The first part is the square of the difference between the predicted value of the quadrature-axis flux linkage and the actual value of the quadrature-axis flux linkage. The second part is at time and the square of the difference between the predicted error compensation values of the quadrature-axis flux linkage at time When the above two parts are both 0, it indicates that the error compensation value no longer changes and the error between the predicted value and the actual value of the quadrature-axis flux linkage is 0; taking the partial derivative of with respect to (15) Let Equation (15) be 0, then we get when it is the smallest value, that is: (16) Equation (16) is rewritten as: (17); The flux linkage prediction equation after adding the compensation term is: (18) In the formula, is the compensation value of the predicted error of the equivalent direct-axis flux linkage at time is the compensation value of the predicted error of the quadrature-axis flux linkage at time

[0014] Step 4 is specifically as follows: Step 4.1, subtract the mechanical angular velocity from the given value of the mechanical angular velocity , and after being processed by a digital PI controller, the given value of the quadrature-axis flux linkage is obtained; Step 4.2, with the control of the given value of the equivalent direct-axis flux linkage , input the given value of the quadrature-axis flux linkage , the given value of the equivalent direct-axis flux linkage , the actual value of the direct-axis flux linkage , the actual value of the quadrature-axis flux linkage , and the error compensation value into the action time calculation module to obtain the action times of two effective vectors and a zero vector ; The vector action time is subjected to expected vector synthesis in the expected vector synthesis module. The given flux linkage values , , the expected voltage vector and the predicted flux linkage values at time , are optimized through the value function of the value function optimization module, and a group of voltage vectors that minimize the value function value are selected to act on the three-phase inverter to achieve the control of the permanent magnet synchronous motor

[0015] The calculation process of the action time of the vector is: Derive the calculation formulas for the direct and quadrature-axis flux linkage slopes and when the zero vector acts in the PMSM three-vector model predictive flux linkage control with error compensation according to formula (18). The specific formulas are as follows: (19) (20) Two effective voltage vectors u i 、u j The direct-axis and quadrature-axis flux linkages slopes when acting 、 、 and are respectively: (21) (22) (23) (24) In the formula: u di 、 u qi represent the voltage components of the effective vector u i on the direct and quadrature axes; u dj 、 u qj represent the voltage components of the effective vector u j on the direct and quadrature axes; Let the predicted value of the stator flux linkage be equal to the equivalent reference stator flux linkage vector at the end of a control period, so the direct and quadrature axis stator flux linkage prediction formulas are rewritten as: (25) (26) In the formula: t i represents the action time of the effective vector u i ; t j represents the action time of the effective vector u j ; t z represents the action time of the zero vector; The sum of the action times of the three voltage vectors is , that is: (27) Combining equations (19) to (27) gives: (28) (29) (30).

[0018] The specific process of expected vector synthesis is as follows: According to the calculated vector action time, a total of 6 effective vectors with variable amplitudes and directions can be synthesized from two basic voltage vectors and zero vectors, as shown in Equations (31) and (32): (31) (32) Substitute the voltage vectors synthesized by Equations (31) and (32) into the value function. When the value of the value function is the smallest, a corresponding set of voltage vectors and action time are applied to the three-phase inverter to control the permanent magnet synchronous motor.

[0019] The beneficial effects of the present invention are as follows: (1) The error compensation PMSM three-vector model predictive flux control system of the present invention abandons the method of obtaining the reference flux vector by analyzing the mathematical relationship among the amplitude of the reference flux, the reference torque, and the load angle in the model predictive flux control, and reselects the flux control variable to realize the model predictive flux control of the permanent magnet synchronous motor. The given value of the flux can not contain the motor parameters, and there is no need to convert the torque and flux through the equivalent load angle containing the motor parameters, which has the advantages of simple algorithm and easy implementation; (2) The error compensation PMSM three-vector model predictive flux control method of the present invention constructs a flux prediction error compensator for the influence of motor parameter changes and system unmodeled dynamic disturbances on the predictive flux equation. When the motor parameters change and there are system unmodeled dynamic disturbances, the actual values of the flux and current can follow the given values, eliminating the steady-state error, thereby improving the robustness of the system. Description of the Drawings

[0020] Figure 1 is the schematic diagram of the error compensation PMSM three-vector model predictive flux control system of the present invention; Figure 2 is the speed waveform diagram of the error compensation PMSM three-vector model predictive flux control system of the present invention when the stator resistance, permanent magnet flux, and stator inductance change simultaneously; Figure 3 is the waveform diagram of the error compensation PMSM three-vector model predictive flux control system of the present invention when the stator resistance, permanent magnet flux, and stator inductance change simultaneously; Figure 4 is the waveform diagram of the error compensation PMSM three-vector model predictive flux control system of the present invention when the stator resistance, permanent magnet flux, and stator inductance change simultaneously.

[0021] In the figure, 1. Three-phase inverter, 2. Current detection circuit, 3. Permanent magnet synchronous motor, 4. Rotary encoder, 5. Clark transformation module, 6. Park transformation module, 7. Flux linkage value calculation module, 8. Flux linkage prediction error compensation module, 9. Flux linkage prediction module, 10. Action time calculation module, 11. Desired vector synthesis module, 12. Value function optimization module. Specific implementation mode

[0022] The present invention will be described in detail below with reference to the accompanying drawings and specific implementation modes.

[0023] The error compensation PMSM three-vector model predictive flux linkage control system and control method of the present invention aim to solve the problems of sensitivity of the three-vector model predictive flux linkage control of permanent magnet synchronous motors to motor parameter changes and robustness problems caused by unmodeled dynamic disturbances of the system.

[0024] Embodiment 1 The error compensation PMSM three-vector model predictive flux linkage control system of the present invention has a principle as Figure 1 shown, and includes a signal detection circuit, a main circuit, and a control circuit; the main circuit includes a three-phase inverter 1, which is mainly used to drive a permanent magnet synchronous motor 3; the signal detection circuit includes a current detection circuit 2 and a rotary encoder 4, which are mainly used to detect the current and rotor position signals of the permanent magnet synchronous motor 3; the control circuit includes a Clark transformation module 5, a Park transformation module 6, a flux linkage value calculation module 7, a flux linkage prediction error compensation module 8, a flux linkage prediction module 9, an action time calculation module 10, a desired vector synthesis module 11, and a value function optimization module 12, which are mainly used to process the signals obtained by the signal detection circuit to obtain control signals for controlling the main circuit.

[0025] The output end of the current detection circuit 2 is sequentially connected to the Clark transformation module 5, the Park transformation module 6, and the flux linkage value calculation module 7. The flux linkage value calculation module 7 is respectively connected to the flux linkage prediction error compensation module 8, the flux linkage prediction module 9, and the action time calculation module 10. The flux linkage prediction error compensation module 8 is respectively connected to the flux linkage prediction module 9 and the action time calculation module 10. The action time calculation module 10 is sequentially connected to the desired vector synthesis module 11 and the value function optimization module 12. The flux linkage prediction module 9 is also connected to the value function optimization module 12. The value function optimization module 12 is connected to the three-phase inverter 1. The optical encoder 4 is connected to the action time calculation module 10 through a digital PI controller. The rotary encoder 4 is also connected to the Park transformation module 6.

[0026] Among them, the control circuit uses the three-phase current obtained by the current detection circuit 2 to detect the permanent magnet synchronous motor 3 , and After being processed by the Clark transformation module 5, we obtain and ; The rotary encoder 4 detects the rotor position angle of the permanent magnet synchronous motor 3 , and by taking the derivative, we obtain the mechanical angular velocity of the motor ; 、 and After being processed by the Park transformation module 6, we obtain the direct-axis and quadrature-axis current feedback values in the two-phase rotating coordinate system and ; and After being processed by the flux linkage value calculation module 7, we obtain k The actual value of the equivalent direct-axis flux linkage at time and the actual value of the quadrature-axis flux linkage ; The actual flux linkage value 、 and k The predicted flux linkage values at time 、 After being processed by the flux linkage prediction error compensation module 8, we obtain the error compensation values 、 , k The predicted flux linkage values at time 、 are obtained by delaying one beat after being calculated by the flux linkage prediction module 9; The actual flux linkage values 、 and the error compensation values 、 After being processed by the flux linkage prediction module 9, we obtain The predicted flux linkage values at time 、 ; The given value of the mechanical angular velocity of the motor and the mechanical angular velocity of the motor After taking the difference and being processed by the PI controller, we obtain the given value of the quadrature-axis q-axis flux linkage ; From 、 and the error compensation values 、 and the actual flux linkage values 、 After being processed by the action time calculation module 10, we obtain the action times of two effective vectors and a zero vector ; The vector action time After passing through the desired vector synthesis module 11, we can obtain 6 groups of desired voltage vectors ; The given flux linkage values 、 , the desired voltage vector and The predicted flux linkage values at time 、 Through the value function optimization module 12, a set of optimal voltage vectors and action time are selected to act on the three-phase inverter 1 to control the permanent magnet synchronous motor 3.

[0027] Embodiment 2 For the PMSM three-vector model predictive flux control method with error compensation of the present invention, the PMSM three-vector model predictive flux control system with error compensation of Embodiment 1 is adopted, and it is specifically implemented according to the following steps: Step 1, establish the mathematical model of the permanent magnet synchronous motor 3; Among them, the mathematical model of the permanent magnet synchronous motor is specifically as follows: (1) (2) (3) (4) (5) Equation (1) In (5), and are the direct-axis component and the quadrature-axis component of the stator voltage respectively; is the stator resistance; and are the direct-axis component and the quadrature-axis component of the stator current respectively; is the rotor electrical angular velocity; and are the direct-axis component and the quadrature-axis component of the stator flux linkage respectively; is the time; and are the direct-axis component and the quadrature-axis component of the stator inductance respectively; is the permanent magnet flux linkage; is the electromagnetic torque; is the number of pole pairs of the motor.

[0028] Step 2, on the basis of the permanent magnet synchronous motor mathematical model, select new control variables for model predictive flux control, construct a value function and calculate the flux linkage prediction equation of the permanent magnet synchronous motor.

[0029] Abandon the method of obtaining the reference flux linkage vector by analyzing the mathematical relationship among the reference flux linkage amplitude, the reference torque and the load angle in the model predictive flux control, and reselect the flux control variables, so that the system given value does not contain motor parameters and there is no need to perform the conversion of the load angle. The specific control principle is as follows: It can be seen from Equation (4) and Equation (5) that the quadrature-axis flux is related to the electromagnetic torque, and there is a proportional-integral relationship between the torque and the speed. Therefore, the quadrature-axis flux reference can be directly obtained from the speed-loop PI regulator, and the quadrature-axis flux can be directly controlled, thus eliminating the need for conversion through the load angle.

[0030] According to Equation (1) and Equation (3), let , and by discretizing Equation (3) using the backward Euler method, we can obtain: (6) where: is the predicted value of the direct-axis flux at time ( ); is the predicted value of the equivalent direct-axis flux at time ( ); is the actual value of the quadrature-axis flux at time; is the direct-axis component of the stator voltage at time .

[0032] It can be seen from Equation (6) that the control of the direct-axis flux is equivalent to the control of the variable . By adopting new flux control variables , for the model predictive flux control of the permanent magnet synchronous motor, the cost function can be reconstructed as: (7) where, is the reference value of the variable . According to i d =0 control, . Therefore, the problem that the reference value of the direct-axis flux is inaccurate and cannot meet the requirements of the control system due to the inaccurate acquisition of the permanent magnet flux value can be avoided. and are calculated as shown in Equations (8) and (9): (8) (9) where, is the quadrature-axis component of the stator voltage at time .

[0033] Step 3: Design a flux prediction error compensation controller for the disturbances caused by the mismatched motor parameters and the unmodeled dynamic disturbances of the system, add the error compensation value to the flux prediction equation of the permanent magnet synchronous motor, and calculate the predicted flux value; Compensation is performed in the prediction model to improve the parameter robustness of the model prediction flux linkage control strategy.

[0034] Step 4, the action time calculation module 10 calculates the action time of the voltage vector, synthesizes the expected voltage vector through the expected vector synthesis module 11, passes the flux linkage prediction value and the expected voltage vector through the value function, selects the optimal voltage vector to act on the three-phase inverter 1, and controls the permanent magnet synchronous motor 3.

[0035] Embodiment 3 Based on Embodiment 2, the specific process of Step 3 is as follows: Step 3.1, the phase current of the permanent magnet synchronous motor 3 is sampled through the current detection circuit 2 、 、 , and is converted to the current in the two-phase stationary coordinate system through the Clark transformation module 5 、 ; Step 3.2, the rotor position angle of the permanent magnet synchronous motor 3 is collected through the rotary encoder 4 , and the differential of the rotor position angle is obtained to get the mechanical angular velocity of the permanent magnet synchronous motor 3; Step 3.3, the rotor position angle and the current in the two-phase stationary coordinate system are converted to the direct-axis current and the quadrature-axis current in the two-phase rotating coordinate system through the Park transformation module 6; Step 3.4, the direct-axis current and the quadrature-axis current are used by the flux linkage calculation module 7 to obtain the actual value of the equivalent direct-axis flux linkage and the actual value of the quadrature-axis flux linkage; Step 3.5, a flux linkage error compensation controller is designed in the flux linkage prediction error compensation module 8, and and are input into the flux linkage prediction error compensation module 8 to calculate the error compensation value ; The error compensation value can be obtained through the following process: First, design the direct-axis flux linkage prediction error compensator : (10) In Equation (10), is the actual value of the equivalent direct-axis flux linkage at time ; Equivalent direct-axis flux prediction error compensation value at a moment; is the equivalent direct-axis flux prediction error compensation coefficient. It can be seen from Equation (10) that the equivalent direct-axis flux prediction error compensator consists of two parts. The first part is the square of the difference between the predicted value of the equivalent direct-axis flux and the actual value of the equivalent direct-axis flux, and the second part is at the moment and the square of the difference between the equivalent direct-axis flux prediction error compensation values at the moment. When the above two parts are both 0, it indicates that the error compensation value no longer changes and the error between the predicted value and the actual value of the direct-axis flux is 0. Therefore, taking the partial derivative of with respect to , the equivalent direct-axis flux prediction error compensation value when is minimized can be obtained: (11) Let Equation (11) be 0, and the value of when is minimized can be obtained, that is: (12) For the convenience of implementation, Equation (12) can be written as: (13) Secondly, design the quadrature-axis flux prediction error compensator : (14) In Equation (14), is the actual value of the quadrature-axis flux at the moment; is the quadrature-axis flux prediction error compensation value at the moment; is the quadrature-axis flux prediction error compensation coefficient. It can be seen from (14) that the quadrature-axis flux prediction error compensator consists of two parts. The first part is the square of the difference between the predicted value of the quadrature-axis flux and the actual value of the quadrature-axis flux, and the second part is at the moment and the square of the difference between the quadrature-axis flux prediction error compensation values at the moment. When the above two parts are both 0, it indicates that the error compensation value no longer changes and the error between the predicted value and the actual value of the direct-axis flux is 0. Therefore, taking the partial derivative of with respect to , the quadrature-axis flux prediction error compensation value when is minimized can be obtained: (15) Let Equation (15) be 0, and the value of when is minimized can be obtained, that is: (16) For the convenience of implementation, Equation (16) can be written as: (17).

[0036] Step 3.6, input and into the over-flux linkage prediction equation of the flux linkage prediction module 9 to calculate the predicted flux linkage value .

[0037] The prediction equation after adding the compensation term is: (18) In the formula, is the compensation value of the predicted error of the equivalent direct-axis flux linkage at ; is the compensation value of the predicted error of the quadrature-axis flux linkage at .

[0038] Embodiment 4 Based on Embodiment 3, Step 4 is specifically as follows: Step 4.1, subtract the mechanical angular velocity from the given value of the mechanical angular velocity , and after being processed by a digital PI controller, obtain the given value of the quadrature-axis flux linkage ; Step 4.2, under the control of the given value of the equivalent direct-axis flux linkage , input the given value of the quadrature-axis flux linkage , the given value of the equivalent direct-axis flux linkage , the actual value of the direct-axis flux linkage , the actual value of the quadrature-axis flux linkage , and the error compensation value into the action time calculation module (10) to obtain the action times of two effective vectors and a zero vector ; The vector action time is subjected to expected vector synthesis in the expected vector synthesis module (11). The given flux linkage values , , the expected voltage vector and the predicted flux linkage value at time , are optimized through the value function of the value function optimization module 12, and a group of voltage vectors that minimize the value function value are selected to act on the three-phase inverter 1 to achieve the control of the permanent magnet synchronous motor 3.

[0039] Embodiment 5 Based on Embodiment 4, the calculation process of the action time of the vector is as follows: The orthogonal-axis flux linkages slopes of the PMSM three-vector model predictive flux control under zero vector action can be derived from Equation 18 and The calculation formulas are shown in Equations (19) and (20) as follows: (19) (20) The orthogonal-axis flux linkages slopes u i 、u j under the action of two effective voltage vectors 、 、 and are respectively: (21) (22) (23) (24) In the formula: u di 、 u qi represent the voltage components of the effective vector u i on the direct and orthogonal axes; u dj 、 u qj represent the voltage components of the effective vector u j on the direct and orthogonal axes.

[0040] Let the predicted value of the stator flux linkage be equal to the equivalent reference stator flux linkage vector at the end of a control period. Therefore, the prediction formulas for the direct and orthogonal axis stator flux linkages can be rewritten as: (25) (26) In the formula: t i represents the action time of the effective vector u i ; t j represents the action time of the effective vector u j ; t z represents the action time of the zero vector.

[0041] The sum of the action times of the three voltage vectors is , that is: (27) By simultaneously solving equations (19) to (27), the solution can be obtained as follows: (28) (29) (30) Example 6 Based on Example 5, the specific process of desired vector synthesis is as follows: According to the calculated vector action time, a total of 6 effective vectors with variable amplitudes and directions can be synthesized from two basic voltage vectors and zero vectors, as shown in equations (31) and (32): (31) (32) Substitute the synthesized voltage vector action in equations (31) and (32) into the cost function. When the cost function value is the smallest, the corresponding set of voltage vectors and action time are applied to the three-phase inverter, thereby controlling the permanent magnet synchronous motor 3.

[0044] Example 7 Simulation verification: For the error compensation PMSM three-vector model predictive flux control method in Embodiment 6 of the present invention, the flux variable of the model predictive flux control is reselected first, so that the given value of the flux is not affected by the permanent magnet flux value, and there is no need to calculate the load angle of the motor parameters, which has the advantages of simple calculation and strong robustness; at the same time, the prediction error caused by parameter perturbation and unmodeled dynamic perturbation in the model predictive flux control is analyzed, and a prediction error perturbation compensator is designed to compensate the prediction error existing in the system, improving the robustness of the system. To verify the effectiveness of the method of the present invention, MATLAB / SIMULINK is used for simulation verification.

[0045] In the simulation model, the Clark transformation module 5, Park transformation module 6, k flux value calculation module 7 at time, perturbation error compensation module 8, ([[]] k flux prediction module 9 at time (+1), action time calculation module 10, desired vector synthesis module 11, and cost function optimization module 12 are all implemented using the S-function Builder functional module and C language programming, and the sampling frequency is 10 kHz.

[0046] In the above simulation model, the parameters of the permanent magnet synchronous motor are set as follows: the permanent magnet flux linkage is 0.303 Wb, the direct-axis component of the stator inductance is 11.56 mH, the quadrature-axis component of the stator inductance is 11.56 mH, the rated voltage is 380 V, the rated current is 4.4 A, the stator resistance is 1.64 Ω, the rated speed is 2430 r / min, the number of pole pairs is 4, and the rotor inertia is 0.0011 kg•m 2 , the damping coefficient is 0.001 N•s / m, and the rated load torque is 9.6 N•m; the parameters of the simulation model are set as follows: the PI proportional coefficient is 0.0015, the integral coefficient is 0.00006, and the error compensation coefficient , . Figure 2 The permanent magnet flux linkage of the motor parameters is , the stator resistance is , the direct-axis component of the stator inductance is , the quadrature-axis component of the stator inductance is , starting from no-load to 1200 r / min; at 0.2 s, the speed reference suddenly changes from 1200 r / min to 1800 r / min; at 0.4 s, a 9.6 N•m load is suddenly applied; at 0.6 s, the load torque suddenly decreases from 9.6 N•m to no-load, the speed response waveform diagram, Figure 3 is waveform diagram; Figure 4 is waveform diagram. From Figure 2 it can be seen that in the PMSM three-vector model predictive flux control system with error compensation of the present invention, when the actual values of the permanent magnet flux linkage, stator resistance and stator inductance of the motor are inconsistent with the nominal values, its speed can accurately follow the reference, and the speed is not affected by the changes in motor parameters and the dynamic disturbances of the unmodeled system.

[0047] From Figure 3 and Figure 4 it can be seen that in the PMSM three-vector model predictive flux control system with error compensation of the present invention, when the actual values of the permanent magnet flux linkage, stator resistance and stator inductance of the motor are inconsistent with the nominal values, and the actual values can still accurately follow the given values, there is no steady-state error caused by parameter changes and the dynamic disturbances of the unmodeled system, and more accurate control can be achieved, improving the robustness of the system.

[0048] The above simulation verifies the effectiveness of the PMSM three-vector model predictive flux control method with error compensation of the present invention. Therefore, the PMSM three-vector model predictive flux control method with error compensation of the present invention can enable the motor to still achieve accurate control when the motor parameters are mismatched and there are system unmodeled dynamic disturbances, improving the robustness of the model predictive flux control.

Claims

1. The PMSM three-vector model predictive flux linkage control system with error compensation is characterized in that, It includes a three-phase inverter (1) that drives a permanent magnet synchronous motor (3), a current detection circuit (2) that samples the stator current of the permanent magnet synchronous motor (3), and a rotary encoder (4) that measures the rotor position angle of the permanent magnet synchronous motor (3). The output end of the current detection circuit (2) is sequentially connected to a Clark transformation module (5), a Park transformation module (6), and a flux linkage value calculation module (7). The flux linkage value calculation module (7) is respectively connected to a flux linkage prediction error compensation module (8), a flux linkage prediction module (9), and an action time calculation module (10). The flux linkage prediction error compensation module (8) is mutually connected to the flux linkage prediction module (9) and the action time calculation module (10). The action time calculation module (10) is sequentially connected to a desired vector synthesis module (11) and a value function optimization module (12). The flux linkage prediction module (9) is also connected to the value function optimization module (12). The value function optimization module (12) is connected to the three-phase inverter (1). The optoelectronic encoder (4) is connected to the action time calculation module (10) through a digital PI controller.

2. The PMSM three-vector model predictive flux linkage control system with error compensation according to claim 1, characterized in that, The rotary encoder (4) is also connected to the Park transformation module (6).

3. The PMSM three-vector model predictive flux control method with error compensation, adopting the PMSM three-vector model predictive flux control system with error compensation as described in claim 1 or 2, is characterized in that, The steps are as follows: Step 1, establish a mathematical model of the permanent magnet synchronous motor (3); Step 2, select a new flux linkage control variable, construct a value function and calculate the flux linkage prediction equation of the permanent magnet synchronous motor; Step 3, design a flux linkage error compensation controller, add the error compensation value to the flux linkage prediction equation of the permanent magnet synchronous motor, and calculate the flux linkage prediction value; Step 4, the action time calculation module (10) calculates the action time of the voltage vector, synthesizes the desired voltage vector through the desired vector synthesis module (11), and applies the flux linkage prediction value and the desired voltage vector through the value function to select the optimal voltage vector to act on the three-phase inverter (1) to control the permanent magnet synchronous motor (3).

4. The error compensation PMSM three-vector model predictive flux linkage control method according to claim 3, characterized in that, In the above Step 1, the mathematical model of the permanent magnet synchronous motor is as follows: (1) (2) (3) (4) (5) Equation (1) In (5), is the direct-axis component of the stator voltage, is the quadrature-axis component of the stator voltage; is the stator resistance; is the direct-axis component of the stator current, is the quadrature-axis component of the stator current; is the rotor electrical angular velocity; is the direct-axis component of the stator flux linkage, is the quadrature-axis component of the stator flux linkage; is the time; is the direct-axis component of the stator inductance, is the quadrature-axis component of the stator inductance; is the permanent magnet flux linkage; is the electromagnetic torque; is the number of pole pairs of the motor.

5. The error compensation PMSM three-vector model predictive flux linkage control method according to claim 3, characterized in that, The specific process of the above Step 2 is: According to the mathematical model of the permanent magnet synchronous motor, let , and the discretization by the backward Euler method can be obtained as follows: (6) In the formula: is the predicted value of the direct-axis flux linkage at the moment of ( ); is the predicted value of the equivalent direct-axis flux linkage at the moment of ( ); is the actual value of the quadrature-axis flux linkage at the moment of; is the direct-axis component of the stator voltage at the moment of ( ); The control of Equation (6) over the direct-axis flux linkage is equivalent to the control of the variable . By adopting new flux-linkage control variables and for the model predictive flux-linkage control of the permanent magnet synchronous motor, the cost function can be reconstructed as follows: (7) wherein, is the given value of the variable , and is controlled according to i d = 0; ; and The calculation formula is as follows: (8) (9) Wherein, is the quadrature axis component of the stator voltage at moment.

6. The error compensation PMSM three-vector model predictive flux linkage control method according to claim 5, characterized in that The specific process of the above Step 3 is: Step 3.1, sample the phase current of the permanent magnet synchronous motor (3) through the current detection circuit (2) , , , and convert it to the current in the two-phase stationary coordinate system through the Clark transformation module (5) , ; Step 3.2, collect the rotor position angle of the permanent magnet synchronous motor (3) through the rotary encoder (4) , for the rotor position angle take the differential to obtain the mechanical angular velocity of the permanent magnet synchronous motor (3) ; Step 3.3, transform the rotor position angle and the current in the two-phase stationary coordinate system through the Park transformation module (6) to obtain the direct-axis current and the quadrature-axis current in the two-phase rotating coordinate system; Step 3.4, direct-axis current and quadrature-axis current are used to obtain the actual value of the equivalent direct-axis flux linkage and the actual value of the quadrature-axis flux linkage ; Step 3.5, design a flux error compensation controller in the flux prediction error compensation module (8), and input and into the flux prediction error compensation module (8) to calculate the error compensation value ; Step 3.6, input and into the over-flux linkage prediction equation of the flux linkage prediction module (9), and calculate the predicted flux linkage value .

7. The error compensation PMSM three-vector model predictive flux linkage control method according to claim 6, characterized in that, The error compensation value The process of obtaining it is as follows: First, design a direct-axis flux prediction error compensator : (10) Among them, is the actual value of the equivalent direct-axis flux linkage at time is the predicted error compensation value of the equivalent direct-axis flux linkage at time is the equivalent direct-axis flux linkage prediction error compensation coefficient; in Equation (10), the equivalent direct-axis flux linkage prediction error compensator consists of two parts. The first part is the square of the difference between the predicted value of the equivalent direct-axis flux linkage and the actual value of the equivalent direct-axis flux linkage. The second part is the time and the square of the difference between the predicted error compensation values of the equivalent direct-axis flux linkage at time When the above two parts are both 0, it indicates that the error compensation value no longer changes at this time and the error between the predicted value and the actual value of the direct-axis flux linkage is 0; taking the partial derivative of with respect to can obtain the equivalent direct-axis flux linkage prediction error compensation value when it is the smallest: (11) Setting Equation (11) to 0, we can obtain when it is at its minimum value, that is: (12) Let Equation (12) be written as: (13) Secondly, design a quadrature-axis flux prediction error compensator : (14) In Equation (14), is the actual value of the quadrature-axis flux linkage at time is the predicted error compensation value of the quadrature-axis flux linkage at time is the predicted error compensation coefficient of the quadrature-axis flux linkage; the predicted error compensator of the quadrature-axis flux linkage in Equation (14) consists of two parts. The first part is the square of the difference between the predicted value and the actual value of the quadrature-axis flux linkage, and the second part is at time and at time the square of the difference between the predicted error compensation values of the quadrature-axis flux linkage. When the above two parts are both 0, it indicates that the error compensation value no longer changes at this time and the error between the predicted value and the actual value of the direct-axis flux linkage is 0; taking the partial derivative of with respect to can obtain the predicted error compensation value of the quadrature-axis flux linkage when is minimized: (15) Setting Equation (15) to 0 gives when it is at its minimum value, i.e.: (16) Equation (16) is rewritten as: (17)； The flux linkage prediction equation after adding the compensation term is: (18) Wherein, is the equivalent direct-axis flux prediction error compensation value at the is the quadrature-axis flux prediction error compensation value at the 8. The error compensation PMSM three-vector model predictive flux linkage control method according to claim 7, characterized in that, The specific content of the above Step 4 is: Step 4.1, subtract the mechanical angular velocity from the given value of the mechanical angular velocity , and after processing by a digital PI controller, obtain the given value of the quadrature-axis magnetic flux ; Step 4.2, direct-axis equivalent flux linkage given value Control, the quadrature-axis flux linkage given value , direct-axis equivalent flux linkage given value , direct-axis flux linkage actual value , quadrature-axis flux linkage actual value , error compensation value are input into the action time calculation module (10) to obtain the action times of two effective vectors and a zero vector ; vector action time is subjected to desired vector synthesis in the desired vector synthesis module (11). The flux linkage given value , , desired voltage vector and the flux linkage predicted value at time , are optimized through the value function of the value function optimization module (12), and a group of voltage vectors that minimize the value function are selected to act on the three-phase inverter (1) to achieve the control of the permanent magnet synchronous motor (3).

9. The PMSM three-vector model predictive flux linkage control method with error compensation according to claim 8, characterized in that, The calculation process of the action time of the above vector is: Derive the calculation formulas for the orthogonal-axis flux linkages slopes when the zero vectors act in the PMSM three-vector model predictive flux linkage control with error compensation according to formula (18), as follows: and The specific calculation formulas are as follows: (19) (20) Two effective voltage vectors u i 、u j Direct-axis flux linkages slopes during the action 、 、 and are respectively: (21) (22) (23) (24) In the formula: u di , u qi represent the effective vectors u i voltage components on the direct and quadrature axes; u dj , u qj represent the effective vectors u j voltage components on the direct and quadrature axes; Let the predicted value of the stator flux linkage be equal to the equivalent reference stator flux linkage vector at the end of a control period, so the direct-axis and quadrature-axis stator flux linkage prediction formulas are rewritten as: (25) (26) Wherein: t i represents the action time of the effective vector u i ; t j represents the action time of the effective vector u j ; t z represents the action time of the zero vector; The sum of the action times of the three voltage vectors is , that is: (27) Combining Equations (19) to (27) gives: (28) (29) (30)。 10. The PMSM three-vector model predictive flux linkage control method with error compensation according to claim 8, characterized in that, The specific process of the above desired vector synthesis is: According to the calculated vector action time, a total of 6 effective vectors with variable amplitudes and directions can be synthesized from two basic voltage vectors and a zero vector as shown in Equations (31) and (32): (31) (32) Substitute the voltage vector synthesized by Equations (31) and (32) into the value function, and when the value function value is the smallest, apply the corresponding set of voltage vectors and action time to the three-phase inverter (1) to control the permanent magnet synchronous motor (3).

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