A synchronous motor double-mode predictive control method and system and a wind power test application

Abstract

The application discloses a synchronous motor double-mode predictive control method and system and a wind power test application, and belongs to the technical field of motor control and wind power test. The method aims to solve the problems of mode switching conflict, slow dynamic response and poor anti-interference of the traditional wind energy test platform cascade control. The method collects motor rotor position and winding current signals, processes the signals, constructs a cross-coupling compensation module and an equivalent state space model, designs a nonlinear disturbance compensation module to estimate and compensate disturbances of each loop, designs a predictive controller based on a unified cost function, and dynamically adjusts the weight to realize adaptive switching of the speed and torque modes in combination with a mode switcher. The system comprises signal acquisition, processing, model and compensation, predictive control, mode switching and execution modules, and the modules work cooperatively. The application to the wind power test platform can improve control consistency, dynamic performance and anti-interference ability, simplify parameter setting, improve test efficiency, and is suitable for wind power system research and development verification scenes.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of motor control and wind power testing, and particularly relates to a synchronous motor dual-mode predictive control method and system and wind power testing application. BACKGROUND

[0002] With the development of offshore wind power to large capacity and deep sea, wind power generation systems are facing the severe challenges of complex turbulent wind conditions and extreme loads. In order to meet the research and development verification needs of the transmission chain of large-capacity wind turbines, motor-towed wind energy testing platforms have become a key technical means to simulate the dynamic characteristics of actual wind wheels. Such platforms apply equivalent disturbance torques to the actual wind load by controlling the loading motor to realize the reproduction of the aerodynamic force of the wind turbine main shaft, and thus can complete the functional verification, control optimization and fault simulation of wind power systems in a laboratory environment.

[0003] Currently, most of the mainstream wind energy testing platforms use a cascade control structure based on a proportional-integral (PI) regulator, and the typical form is a double-closed-loop architecture of "outer loop speed control + inner loop current / torque control". In actual applications, this structure has the following shortcomings: first, the speed loop and the torque loop use separate controller designs (such as PI regulation in speed mode and current closed loop in torque mode), which has control logic conflicts and the risk of transient process instability in scenarios such as maximum power point tracking testing and turbulent disturbance simulation that require switching control targets. Second, the multi-loop nested structure of traditional cascade control not only increases the complexity of parameter tuning, but also limits the overall dynamic response speed due to the bandwidth limitation of the inner loop. In addition, the traditional cascade control method is difficult to accurately capture the nonlinear characteristics and dynamic modal responses of wind turbines under the influence of inertia-flexible coupling. Under high-frequency disturbance or strong wind shear, the control error is amplified, affecting the testing accuracy and robustness.

[0004] Therefore, it is urgent to break through the limitations of the traditional cascade control architecture and design an advanced control strategy with a simple structure, unified mode and flexible performance to achieve the unified control target of wind load disturbance simulation and optimal speed tracking, thereby improving the adaptability, flexibility and experimental efficiency of the wind energy testing platform. SUMMARY

[0005] The purpose of the present application is to provide a synchronous motor dual-mode predictive control method and system and wind power testing application to improve the adaptability, flexibility and experimental efficiency of the wind energy testing platform.

[0006] To achieve the above purpose, the present application provides a synchronous motor dual-mode predictive control method, comprising the following steps:

[0007] S1, collecting the rotor position signal and winding current signal of the synchronous motor, and obtaining the rotor electric angle, speed feedback signal and current component in the two-phase rotating coordinate system through processing;

[0008] S2, constructing a cross-coupling compensation module based on the speed feedback signal and the current components, and establishing an equivalent state space model of the synchronous motor in a rotating coordinate system;

[0009] S3, designing a nonlinear disturbance compensation module according to the equivalent state space model and the feedback signal, estimating and compensating nonlinear disturbance components of the speed loop and the current loop;

[0010] S4, constructing a unified cost function containing speed tracking error and current tracking error based on the equivalent state space model, the disturbance compensation result and a given control target, and designing a predictive controller;

[0011] S5, dynamically adjusting the weight coefficients in the cost function through a control mode switcher to realize adaptive switching between the speed control mode and the torque control mode, and outputting optimal voltage commands to drive the synchronous motor.

[0012] Preferably, in step S1, the processing includes: collecting rotor position signals through an encoder, obtaining a speed feedback signal through differential calculation and filtering processing; converting three-phase winding currents into current components in a two-phase stationary coordinate system through a Clarke converter, and then converting the d-axis and q-axis current components in the rotating coordinate system through a Park converter.

[0013] Preferably, in step S2, the construction formula of the cross-coupling compensation module is:

[0014] ;

[0015] wherein, , is the cross-coupling compensation voltage, is the speed feedback signal, , is the d-axis and q-axis current feedback signal, , is the d-axis and q-axis inductance of the motor, is the number of pole pairs of the motor, is the flux linkage of the motor.

[0016] Preferably, in step S3, the nonlinear disturbance compensation module includes a nonlinear speed disturbance compensation module, a nonlinear d-axis current disturbance compensation module and a nonlinear q-axis current disturbance compensation module; wherein the calculation formula of the nonlinear speed disturbance compensation module is:

[0017] ;

[0018] wherein, is the estimated value of the speed feedback signal , is an estimated value of a nonlinear disturbance component acting on the speed channel is a nonlinear speed disturbance compensation module parameter

[0019] The calculation formula of the nonlinear d-axis current disturbance compensation module is:

[0020]

[0021] wherein, is an estimated value of a d-axis current feedback signal is an estimated value of a nonlinear disturbance component acting on the d-axis current channel disturbance nonlinear d-axis current disturbance compensation module

[0022] The calculation formula of the nonlinear q-axis current disturbance compensation module is:

[0023]

[0024] wherein, is an estimated value of a q-axis current feedback signal is an estimated value of a nonlinear disturbance component acting on the q-axis current channel disturbance nonlinear q-axis current disturbance compensation module Preferably, in step S4, a system cost function is constructed:

[0025]

[0026]

[0027] wherein, is a weight factor, is a prediction step.

[0028] A synchronous motor dual-mode integrated predictive control system, comprising:

[0029] a signal acquisition module, configured to acquire a rotor position signal and a winding current signal;

[0030] ​​​​​​​​​​​​​​​​​​The signal processing module is connected with the signal acquisition module, and is used for converting the rotor position signal into a rotor electric angle and a speed feedback signal, and converting three-phase currents into current components in a rotating coordinate system.

[0031] The model and compensation module is connected with the signal processing module, and is used for constructing a cross-coupling compensation module and an equivalent state space model, and estimating and compensating nonlinear disturbances through a nonlinear disturbance compensation module.

[0032] The prediction control module is connected with the model and compensation module, and is used for constructing a cost function based on an error dynamic equation, and outputting optimal voltage instructions.

[0033] The mode switching module is connected with the prediction control module, and is used for dynamically adjusting a weight coefficient of the cost function, and realizing control mode switching.

[0034] The execution module is connected with the prediction control module, and is used for converting the voltage instructions into driving signals to control the synchronous motor.

[0035] Preferably, the signal acquisition module comprises an encoder and a current sensor, the encoder is installed on a rotor shaft of the synchronous motor, and the current sensor is used for acquiring three-phase winding currents; the signal processing module comprises an angular velocity calculation unit, a Clarke converter and a Park converter, the angular velocity calculation unit performs differential and filtering processing on the rotor position signal, and the Clarke converter and the Park converter sequentially complete current coordinate conversion.

[0036] Preferably, the model and compensation module comprises a cross-decoupling compensation unit, a nonlinear speed disturbance compensation unit, a nonlinear d-axis current disturbance compensation unit and a nonlinear q-axis current disturbance compensation unit; the cross-decoupling compensation unit is connected with a speed feedback output end and a current component output end of the signal processing module, and each nonlinear disturbance compensation unit is connected with a corresponding feedback signal output end of the signal processing module and the equivalent state space model.

[0037] Preferably, the prediction control module comprises a speed / torque integrated prediction controller and a d-axis current prediction controller; the speed / torque integrated prediction controller outputs a q-axis optimal voltage instruction based on a speed error, a q-axis current error and a weight coefficient output by the mode switching module, and the d-axis current prediction controller outputs a d-axis optimal voltage instruction based on a d-axis current error.

[0038] Therefore, the synchronous motor double-mode prediction control method, system and wind power test application with the above structure have the following beneficial effects:

[0039] (1) The application constructs a unified predictive control framework, fuses the dual goals of speed control and torque control mode, dynamically adjusts the weight coefficient in the cost function by introducing a mode switching mechanism, and realizes the adaptive coordination between control goals. This method effectively avoids the control conflict and transient instability problem caused by the independent design of the speed loop and the torque loop in the traditional cascade control, significantly improves the consistency and adaptability of the control strategy in the multi-scene switching process.

[0040] (2) The application adopts a simple control architecture, discards the traditional multi-loop nested design mode, reduces the parameter coupling between control loops, simplifies the parameter setting process of the controller, significantly reduces the engineering complexity of system deployment and debugging, and improves the maintainability and engineering practicability of the control system.

[0041] (3) The application designs a nonlinear disturbance compensation module for the speed channel, q-axis current channel and d-axis current channel respectively, which can effectively estimate and compensate the unknown nonlinear disturbance caused by external load and internal parameter perturbation in the synchronous motor control system, thereby significantly enhancing the robustness and anti-disturbance ability of the system, and improving the dynamic performance and steady-state accuracy of the overall control system.

[0042] (4) The predictive controller designed in the application derives a quasi-optimal control law with an explicit analytical solution, avoiding the real-time iterative solution of complex optimization problems in traditional model predictive control, greatly improving the real-time performance of the algorithm, and being particularly suitable for resource-limited embedded control systems, providing a feasible technical solution for industrial site deployment.

[0043] (5) Through the collaborative design of the control mode switcher and the unified predictive controller, the application can quickly respond to wind condition changes and test condition switching, has good universality and expandability, and significantly improves the experimental efficiency and test effect of the wind energy test platform in the application scenarios such as wind turbine development, control algorithm verification and fault condition simulation.

[0044] The technical solutions of the application will be further described in detail below with the help of the accompanying drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 is a system schematic diagram of the application;

[0046] Figure 2 is a schematic diagram of the nonlinear speed disturbance compensation module of the application;

[0047] Figure 3 is a schematic diagram of the nonlinear q-axis current disturbance compensation module of the application;

[0048] Figure 4 is a schematic diagram of the nonlinear d-axis current disturbance compensation module of the application;

[0049] Figure 5 System response diagram for the control mode of the present application switching from torque control to speed control;

[0050] Figure 6 System response diagram for the control mode of the present application switching from speed control to torque control;

[0051] Figure 7 Control performance verification diagram in the speed control mode;

[0052] Figure 8 Torque control performance verification diagram in the torque control mode. DETAILED DESCRIPTION

[0053] The technical solutions of the present application are further described below by means of the accompanying drawings and examples.

[0054] Unless otherwise defined, the technical terms or scientific terms used in the present application shall be understood as the usual meanings understood by those skilled in the art to which the present application belongs. The terms "first", "second", and the like used in the present application do not represent any order, number, or importance, but are only used to distinguish different components. The terms "include" or "contain" and the like mean that the elements or objects appearing before the terms cover the elements or objects listed after the terms and their equivalents, without excluding other elements or objects. The terms "connect" or "connected" and the like are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. The terms "up", "down", "left", "right", and the like are only used to represent relative positional relationships, and when the absolute positions of the described objects change, the relative positional relationships can also change accordingly.

[0055] EMBODIMENT

[0056] The present application provides a synchronous motor dual-mode predictive control method, system and wind power test application, as shown in Figure 1 The system consists of the following modules:

[0057] The encoder is installed on the rotor shaft of the synchronous motor to collect the rotor position signal of the motor

[0058] The angular velocity calculation module is used to differentially calculate the rotor position signal output by the encoder to obtain an angular velocity feedback signal , and to filter the signal to reduce noise interference;

[0059] The Clarke converter is used to convert the three-phase current signals , ​​ Convert to two-phase quadrature Current components in the coordinate system , .

[0060] Park converter, for converting the current components calculated by the Clarke converter to d-q rotating reference coordinate system to obtain the current components of the motor in the d-q coordinate system according to the rotor electrical angle . , Convert the current components calculated by the Clarke converter to d-q rotating reference coordinate system to obtain the current components of the motor in the d-q coordinate system according to the rotor electrical angle , .

[0061] Nonlinear speed disturbance compensation module, for estimating the nonlinear disturbance component acting on the speed loop in real time according to the speed feedback signal, d-q axis current feedback signal.

[0062] Nonlinear d-axis current disturbance compensation module, for estimating the nonlinear disturbance component acting on the d-axis current channel in real time according to the d-axis current feedback signal and the d-axis given voltage signal.

[0063] Nonlinear q-axis current disturbance compensation module, for estimating the nonlinear disturbance component acting on the q-axis current channel in real time according to the q-axis current feedback signal and the q-axis voltage signal.

[0064] Control mode switcher, for dynamically adjusting the speed / torque control weight factor according to the actual control requirement to realize flexible switching of the control mode.

[0065] Speed / torque integrated predictive controller, based on the speed error and the q-axis current error to construct a unified cost function; according to the control weight coefficient output by the mode switcher, output the optimal q-axis voltage instruction to realize the integration of speed control and torque control with high performance.

[0066] D-axis current predictive controller, based on the d-axis current error to construct a cost function, output the optimal d-axis voltage instruction to realize accurate control of the d-axis current.

[0067] Primary maximum torque current ratio controller, for calculating the corresponding optimal d-axis current instruction according to the q-axis feedback current signal to realize the control target of maximum torque current ratio.

[0068] Secondary maximum torque current ratio controller, for calculating the corresponding optimal d-axis and q-axis current instructions according to the given torque signal to realize the control target of maximum torque current ratio.

[0069] Cross-decoupling compensation module, for calculating the voltage coupling component of the d-q axis current channel.​​

[0070] Park inverse transformer, for converting the d-q axis given voltage signal calculated by the controller into voltage signal in three-phase static coordinate system;

[0071] Space voltage vector pulse width modulation (SVPWM module, converting three-phase voltage instruction into PWM switch signal executable by inverter);

[0072] Three-phase inverter module, receiving PWM switch signal, driving synchronous motor to operate;

[0073] In addition, the application provides a synchronous motor double-mode predictive control method, and the specific steps are as follows:

[0074] Step S1: collecting motor rotor position signal through encoder According to the rotor position signal , the rotor electrical angle signal is calculated and obtained; the rotor position signal output by the encoder is differentially calculated, and filtering processing is performed, so that the speed feedback signal is calculated; the winding current signal of the motor is collected , and the Clarke transformer is used to calculate the motor axis and axis current ; according to the calculated motor axis and axis current , , the Park transformer is used to calculate the motor d-axis and q-axis current , .

[0075] Step S2: according to the speed feedback signal and the d-q axis current feedback signal , , a cross-coupling compensation module is constructed:

[0076] ;

[0077] Among them, , is the cross-coupling compensation voltage, is the speed feedback signal, , is the d-axis and q-axis current feedback signal, , is the motor d-axis and q-axis inductance, is the pole pair number of the motor, is the flux linkage of the motor.

[0078] Step S3: According to the cross-coupling compensation module constructed in step S2, the equivalent state space model of the synchronous motor in the d-q coordinate system is constructed:

[0079] ;

[0080] wherein, , denote the equivalent voltages of the d-axis and q-axis of the motor, wherein , are the actual voltages of the d-axis and q-axis of the motor;

[0081] , ;

[0082] , ; , ;

[0083] wherein, , are the d-axis and q-axis currents of the motor, respectively; is the flux linkage of the motor; and are the d-axis and q-axis inductances of the motor, respectively; is the pole pair number of the motor; is the stator resistance; is the viscous friction coefficient; is the system inertia; , , denote the nonlinear disturbance components acting on the speed loop, the q-axis current loop, and the d-axis current loop, respectively;

[0084] Step S4: According to the equivalent system model constructed in step S3, the speed feedback signal , the d-axis and q-axis current feedback signals , , and the nonlinear speed disturbance compensation module:

[0085] ;

[0086] wherein, is the estimated value of the speed feedback signal , is the estimated value of the nonlinear disturbance component acting on the speed channel, , , is a nonlinear speed disturbance compensation module parameter.

[0087] Step S5: Calculate the q-axis steady-state equivalent voltage of the motor maintained at a given speed from the nonlinear disturbance estimation signal output by the nonlinear speed disturbance compensation module constructed in step S4 and the equivalent system model constructed in step S3. .

[0088] Step S6: Construct a nonlinear q-axis current disturbance compensation module from the equivalent system model constructed in step S3 and the q-axis current feedback signal and the equivalent voltage signal .

[0089] ;

[0090] wherein is an estimation of the q-axis current feedback signal , is an estimation of the nonlinear disturbance component acting on the q-axis current channel disturbance, , , the nonlinear q-axis current disturbance compensation module.

[0091] Step S7: Calculate the q-axis steady-state equivalent voltage of the motor maintained at a given speed from the nonlinear disturbance estimation signal output by the nonlinear q-axis current disturbance compensation module constructed in step S6 , the q-axis steady-state current calculated in step S5 and the equivalent system model constructed in step S3. .

[0092] Step S8: Construct a nonlinear d-axis current disturbance compensation module from the system model obtained in step S3 and the d-axis current feedback signal and the given voltage signal .

[0093] ;

[0094] wherein is an estimation of the d-axis current feedback signal , is an estimation of the nonlinear disturbance component acting on the d-axis current channel disturbance, , , the nonlinear d-axis current disturbance compensation module.

[0095] Step S9: Construct the nonlinear disturbance estimation signal according to the nonlinear model built in step S8 The nonlinear disturbance estimation signal outputted by the shaft current disturbance compensation module and the equivalent system model built in step S3, calculate the d-axis steady-state equivalent voltage of the motor maintained at a given d-axis current . .

[0096] Step S10: According to the q-axis steady-state current obtained in step S5 , the q-axis steady-state equivalent voltage obtained in step S7 , the d-axis steady-state equivalent voltage obtained in step S9 , the equivalent system model obtained in step S3, and the given speed , construct the error dynamic equation of the equivalent system:

[0097] ;

[0098] wherein, , , , , are the speed error, the d-axis and q-axis current errors of the motor, and the d-axis and q-axis equivalent voltage errors of the system, respectively.

[0099] Step S11: According to the equivalent system error model obtained in step S10, use Taylor expansion to estimate the system error within the future prediction time length :

[0100] ;

[0101] wherein, is the prediction matrix; is the speed error matrix; is the q-axis current error matrix, is the d-axis current error matrix.

[0102] Step S12: According to the prediction model established in step S11, in order to achieve optimal control performance, consider the speed tracking error , the q-axis current tracking error and the d-axis current error of the system, construct the system cost function:

[0103] ;

[0104] wherein, , , is the weight factor, , To predict the step size.

[0105] Step S13: According to the q-axis speed feedback signal , a first maximum torque current ratio controller is constructed:

[0106]

[0107] wherein, is the d-axis current given signal of the first maximum torque current ratio controller output.

[0108] Step S14: According to the given torque , a second maximum torque current ratio controller is constructed:

[0109]

[0110] wherein, , are the d-axis and q-axis current given signals of the second maximum torque current ratio controller output, respectively.

[0111] Step S15: According to the cost function constructed in step S12 , the q-axis steady-state current for maintaining the given speed calculated in step S5 , the d-axis current given signal calculated in step S13 , the d-axis current given signal calculated in step S14 , and the q-axis current given signal , a control mode switcher is constructed:

[0112]

[0113] wherein, , is the logic variable of the control mode switcher; represents the control mode in which the controller is to work, represents the current control weight of the controller; represents that the controller works in the speed mode; represents that the controller works in the torque mode; is the switching time; is the parameter of the control mode switcher.

[0114] Step S16: According to the cost function obtained in step S12, the prediction model obtained in step S11, and the weight coefficient output by the control mode switcher constructed in step S15, , through further derivation, it can be equivalent to the following form:

[0115] ;​​​

[0116] Step S17: Solve the cost function obtained in step S16. For control variables Partial derivatives:

[0117] ;

[0118] in, , , , , , .

[0119] make Thus, the optimal q-axis equivalent voltage error input is obtained:

[0120] ;

[0121] Step S18: Solve the cost function obtained in step S16. For control variables Partial derivatives:

[0122] ;

[0123] in, , , .

[0124] make Thus, the optimal d-axis equivalent voltage error input is obtained:

[0125] ;

[0126] Step S19: Input the optimal q-axis equivalent voltage error obtained in step S17. The optimal d-axis equivalent voltage error input obtained in step S18 The output of the cross-coupling compensation module constructed in step S2 Based on the equivalent system model constructed in step S3, a single closed-loop speed / torque predictive controller and a d-axis current predictive controller are constructed:

[0127] ;

[0128] in, Provide a voltage signal for the q-axis. Provide a voltage signal for the d-axis.

[0129] Figures 2-4The specific implementation block diagrams of the nonlinear speed disturbance compensation module, the nonlinear q-axis current disturbance compensation module and the nonlinear d-axis current disturbance compensation module are respectively given, and the nonlinear speed disturbance compensation module, the nonlinear q-axis current disturbance compensation module and the nonlinear d-axis current disturbance compensation module can be implemented by referring to the implementation.

[0130] In addition, the control parameter adjustment rules involved in the dual-mode integrated predictive controller are as follows:

[0131] 1. Parameters in the nonlinear speed disturbance compensation module , , are used to adjust the compensation accuracy and speed of the nonlinear speed disturbance compensation module for the nonlinear disturbance component acting on the speed channel, and satisfy , , , The parameter size is positively correlated with the compensation speed and accuracy.

[0132] 2. Parameters in the nonlinear speed disturbance compensation module , , are used to adjust the compensation accuracy and speed of the nonlinear q-axis current disturbance compensation module for the nonlinear disturbance component acting on the q-axis current channel, and satisfy , , , The parameter size is positively correlated with the compensation speed and accuracy.

[0133] 3. Parameters in the nonlinear speed disturbance compensation module , , are used to adjust the compensation accuracy and speed of the nonlinear d-axis current disturbance compensation module for the nonlinear disturbance component acting on the d-axis current channel, and satisfy , , , The parameter size is positively correlated with the compensation speed and accuracy.

[0134] 4. Parameters in the control mode switcher are used to adjust the transition time of the control mode switching, and satisfy The parameter size is negatively correlated with the transition time.

[0135] 5. Parameters in the predictive controller and are used to adjust the prediction step of the predictive controller, and satisfy , The parameter size is negatively correlated with the response speed of the system.

[0136] Four working conditions are set to illustrate the effectiveness of the application:

[0137] 1. Working condition 1: set the control mode to torque control, the torque reference is 6 Nm, the initial load is 5 Nm, and the control mode is switched to speed control at 0.2 s, and the given speed is 1000 rpm.

[0138] 2. Working condition 2: set the control mode to speed control, the given speed is 1000 rpm, the initial load is 5 Nm, and the control mode is switched to torque control at 2 s, the given torque is 15 Nm, and the load is set to 14.8 Nm.

[0139] 3. Working condition 3: set the control mode to speed control, the given speed is 1000 rpm, the initial load is 5 Nm, the load is changed to 35 Nm at 0.15 s, and the given speed is modified to rpm at 0.3 s.

[0140] 4. Working condition 4: set the control mode to torque control, the given torque is 15 Nm, and the given torque is Nm at 0.2 s.

[0141] Figure 5 The response curves of motor speed, q-axis current, d-axis current, and output torque under working condition 1 are given. Figure 6 The response curves of motor speed, q-axis current, d-axis current, and output torque under working condition 2 are given. Figure 7 The response curves of motor speed, q-axis current, d-axis current, and output torque under working condition 3 are given. Figure 8 The response curves of motor output torque, q-axis current, and d-axis current under working condition 4 are given. From the test results, it can be seen that the dual-mode integrated predictive control method proposed in the application not only supports online flexible switching of the control mode, but also can realize fast and accurate tracking control of complex time-varying speed and torque instructions. At the same time, this method can effectively suppress the nonlinear disturbance acting on each channel of the system, significantly improving the dynamic response performance, anti-disturbance ability and control flexibility of the synchronous motor control system.

[0142] Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the application and not to limit them. Although the application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the application can be modified or replaced by equivalents, and these modifications or replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the application.

Claims

1. A dual-mode integrated predictive control method for synchronous machines, characterized in that, The method comprises the following steps: S1, collecting rotor position signals and winding current signals of the synchronous motor, and obtaining rotor electric angle, speed feedback signals and current components in a two-phase rotating coordinate system through processing; S2, constructing a cross-coupling compensation module based on the speed feedback signals and the current components, and establishing an equivalent state space model of the synchronous motor in a rotating coordinate system; S3, designing a nonlinear disturbance compensation module according to the equivalent state space model and the feedback signals, and estimating and compensating nonlinear disturbance components of the speed loop and the current loop; S4. Constructing a unified cost function including speed tracking error and current tracking error 、 based on the equivalent state space model, the disturbance compensation result and given control target, and designing a predictive controller, the cost function is ； wherein, is a weight factor, is a prediction step size, is a future prediction time length; S5, dynamically adjusting the weight coefficients in the cost function through a control mode switcher to realize adaptive switching of the speed control mode and the torque control mode, and outputting optimal voltage commands to drive the synchronous motor, wherein the control mode switcher is represented as ； wherein is the q-axis steady-state current at a given speed under the control of the controller, is the d-axis current given signal, is the switching time, is the parameter of the control mode switcher, is the viscous friction coefficient, is the system inertia, is the motor d-axis and q-axis inductance, is the motor flux, is the d-axis current feedback signal, is the estimated value of the non-linear disturbance component acting on the speed channel; is the logic variable of the control mode switcher; indicates the control mode in which the controller will work, indicates the current control weight of the controller; indicates that the controller works in the speed mode; indicates that the controller works in the torque mode; According to the q-axis current feedback signal , a maximum torque current ratio controller is constructed: ； is a d-axis current command signal output from the maximum torque current ratio controller; According to the given torque , a quadratic maximum torque current ratio controller is constructed: ； d-axis and q-axis current command signals output from the quadratic maximum torque current ratio controller, is the number of pole pairs of the motor.

2. The method of claim 1, wherein, In step S1, the rotor position signals are collected through an encoder, and the speed feedback signals are obtained through differential calculation and filtering processing; the three-phase winding currents are converted into current components in a two-phase stationary coordinate system through a Clarke converter, and then converted into d-axis and q-axis current components in a rotating coordinate system through a Park converter.

3. The method of claim 1, wherein, In step S2, the construction formula of the cross-coupling compensation module is: ； wherein, is a cross-coupling compensation voltage, is a speed feedback signal, is axis and axis current feedback signal, are motor d-axis and q-axis inductances, is a number of pole pairs of the motor, is a flux linkage of the motor.

4. The method of claim 1, wherein, In step S3, the nonlinear disturbance compensation module comprises a nonlinear speed disturbance compensation module, a nonlinear d-axis current disturbance compensation module and a nonlinear q-axis current disturbance compensation module; wherein the calculation formula of the nonlinear speed disturbance compensation module is: ； in, It is a speed feedback signal The estimated value, It is a nonlinear disturbance component acting on the velocity channel. The estimated value, These are parameters of the nonlinear velocity disturbance compensation module; It is the q-axis current feedback signal; These are system auxiliary variables, among which It is the number of pole pairs of the motor. It is the magnetic flux of the motor. These are the d-axis and q-axis inductances of the motor. It is the d-axis current feedback signal; The calculation formula of the nonlinear d-axis current disturbance compensation module is: ； wherein, is an estimate of the d-axis current feedback signal is an estimate of the non-linear disturbance component of the disturbance acting on the d-axis current channel is a system auxiliary variable, wherein is the motor stator resistance, is the motor d-axis inductance, is the d-axis steady-state equivalent voltage of the motor maintained at a given d-axis current, is a non-linear d-axis current disturbance compensation module parameter;​​​ The calculation formula of the nonlinear q-axis current disturbance compensation module is: ； wherein is an estimate of the q-axis current feedback signal is an estimate of the nonlinear disturbance component of the disturbance acting on the q-axis current channel is a system auxiliary variable, wherein is the motor stator resistance, is the motor q-axis inductance, is the q-axis steady-state equivalent voltage of the motor maintained at a given speed, is a nonlinear q-axis current disturbance compensation module parameter.​​​ 5. A control system according to any one of the methods of claims 1-4, characterized by It comprises: A signal acquisition module for acquiring rotor position signals and winding current signals; A signal processing module connected with the signal acquisition module, for converting the rotor position signals into rotor electric angle and speed feedback signals, and converting three-phase currents into current components in a rotating coordinate system; A model and compensation module connected with the signal processing module, for constructing a cross-coupling compensation module and an equivalent state space model, and estimating and compensating nonlinear disturbances through a nonlinear disturbance compensation module; A predictive control module connected with the model and compensation module, for constructing a cost function based on an error dynamic equation, and outputting optimal voltage commands; A mode switching module connected with the predictive control module, for dynamically adjusting the weight coefficients of the cost function to realize control mode switching; An execution module connected with the predictive control module, for converting the voltage commands into driving signals to control the synchronous motor.

6. The control system of claim 5, wherein, The signal acquisition module comprises an encoder and a current sensor, the encoder is installed on the rotor shaft of the synchronous motor, and the current sensor is used to acquire three-phase winding currents; the signal processing module comprises an angular velocity calculation unit, a Clarke converter and a Park converter, the angular velocity calculation unit performs differential and filtering processing on the rotor position signals, and the Clarke converter and the Park converter sequentially complete current coordinate conversion.

7. The control system of claim 5, wherein, The model and compensation module comprises a cross decoupling compensation unit, a nonlinear speed disturbance compensation unit, a nonlinear d-axis current disturbance compensation unit and a nonlinear q-axis current disturbance compensation unit; the cross decoupling compensation unit is connected with the speed feedback output end and the current component output end of the signal processing module, and each nonlinear disturbance compensation unit is connected with the corresponding feedback signal output end of the signal processing module and the equivalent state space model.

8. The control system of claim 5, wherein, The predictive control module comprises a speed / torque integrated predictive controller and a d-axis current predictive controller; the speed / torque integrated predictive controller outputs a q-axis optimal voltage instruction based on a speed error, a q-axis current error and a weight coefficient output by the mode switching module, and the d-axis current predictive controller outputs a d-axis optimal voltage instruction based on a d-axis current error.

9. A wind energy simulation system for a wind turbine test platform, the system comprising: The synchronous motor double-mode integrated predictive control method of any one of claims 1-4 or the control system comprising any one of claims 5-8 is used to simulate actual wind wheel dynamic characteristics and realize reproduction of aerodynamic force of a fan main shaft.

Images