Synchronous motor dual-mode prediction control method and system and wind power test application

Abstract

The invention discloses a synchronous motor dual-mode prediction control method and system and wind power test application, and belongs to the technical field of motor control and wind power test. The objective of the invention is to solve the problems of mode switching conflict, slow dynamic response, poor anti-interference performance and the like existing in cascade control of a traditional wind energy test platform. The method comprises the following steps: acquiring and processing a motor rotor position and a winding current signal, constructing a cross coupling compensation module and an equivalent state space model, designing a nonlinear disturbance compensation module to estimate and compensate disturbance of each loop, designing a prediction controller based on a unified cost function, and calculating the disturbance of each loop. And the weight is dynamically adjusted by combining a mode switcher to realize self-adaptive switching of a speed mode and a torque mode. The system comprises a signal acquisition module, a signal processing module, a model and compensation module, a prediction control module, a mode switching module and an execution module which work cooperatively. When the method is applied to a wind power test platform, control consistency, dynamic performance and anti-interference capability can be improved, parameter setting is simplified, test efficiency is improved, and the method is suitable for wind power system research and development verification scenes.

Description

Technical Field

[0001] This invention relates to the fields of motor control and wind power testing technology, and in particular to a dual-mode predictive control method, system and wind power testing application for synchronous motors. Background Technology

[0002] As offshore wind power develops towards larger capacities and deeper waters, wind power generation systems face severe challenges from complex turbulent wind conditions and extreme loads. To meet the research and verification needs of large-capacity wind turbine drivetrains, motor-to-torsional wind energy testing platforms have become a key technical means to simulate the dynamic characteristics of actual wind turbines. These platforms reproduce the aerodynamic forces on the turbine's main shaft by controlling the loading motor to apply a disturbance torque equivalent to the actual wind load. This allows for functional verification, control optimization, and fault simulation of wind power systems to be performed in a laboratory environment.

[0003] Currently, most mainstream wind energy testing platforms adopt a cascaded control structure based on proportional-integral (PI) regulators, typically a dual-closed-loop architecture of "outer loop speed control + inner loop current / torque control". In practical applications, this structure has the following shortcomings: First, the speed and torque loops use discrete controller designs (e.g., PI regulation in speed mode and current closed-loop in torque mode). In scenarios requiring switching control targets, such as maximum power point tracking testing and turbulence disturbance simulation, there is a risk of control logic conflicts and transient instability. Second, the multi-loop nested structure of traditional cascaded control not only increases parameter tuning complexity but also restricts the overall dynamic response speed due to inner loop bandwidth limitations. Furthermore, traditional cascaded control methods struggle to accurately capture the nonlinear characteristics and dynamic modal responses of wind turbines under inertia-flexible coupling. Under high-frequency disturbances or strong wind shear, control errors are amplified, affecting test accuracy and robustness.

[0004] Therefore, it is urgent to break through the inherent limitations of the traditional cascaded control architecture and design an advanced control strategy that is simple in structure, unified in mode, and flexible in performance to achieve the unified control objective of wind load disturbance simulation and optimal speed tracking, thereby improving the adaptability, flexibility and experimental efficiency of the wind energy testing platform. Summary of the Invention

[0005] The purpose of this invention is to provide a dual-mode predictive control method, system, and wind power testing application for synchronous motors, thereby improving the adaptability, flexibility, and experimental efficiency of wind energy testing platforms.

[0006] To achieve the above objectives, the present invention provides a dual-mode predictive control method for synchronous motors, comprising the following steps: S1. Collect the rotor position signal and winding current signal of the synchronous motor, and process them to obtain the rotor electrical angle, speed feedback signal and current component in the two-phase rotating coordinate system. S2. Based on the speed feedback signal and current components, construct a cross-coupling compensation module and establish an equivalent state space model of the synchronous motor in the rotating coordinate system. S3. Based on the equivalent state space model and feedback signal, design a nonlinear disturbance compensation module to estimate and compensate for the nonlinear disturbance components of the speed loop and current loop. S4. Based on the equivalent state-space model, disturbance compensation results, and given control objective, construct a unified cost function that includes speed tracking error and current tracking error, and design a predictive controller. S5. By dynamically adjusting the weight coefficients in the cost function through the control mode switcher, adaptive switching between speed control mode and torque control mode is achieved, and the optimal voltage command is output to drive the synchronous motor.

[0007] Preferably, in step S1, the processing includes: acquiring rotor position signals through an encoder, obtaining speed feedback signals through differential calculation and filtering; converting the three-phase winding current into current components in a two-phase stationary coordinate system through a Clarke converter, and then converting them into d-axis and q-axis current components in a rotating coordinate system through a Park converter.

[0008] Preferably, in step S2, the construction formula of the cross-coupling compensation module is as follows: ; in, , It is a cross-coupling compensation voltage. It is a speed feedback signal. , These are the d-axis and q-axis current feedback signals. , These are the inductances of the motor's d-axis and q-axis. It is the number of pole pairs of the motor. It is the magnetic flux of the motor.

[0009] Preferably, in step S3, the nonlinear disturbance compensation module includes a nonlinear velocity disturbance compensation module, a nonlinear d-axis current disturbance compensation module, and a nonlinear q-axis current disturbance compensation module; wherein, the calculation formula for the nonlinear velocity 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; The calculation formula for the nonlinear d-axis current disturbance compensation module is as follows: ; in, It is the d-axis current feedback signal The estimate, It is the nonlinear disturbance component acting on the d-axis current channel disturbance. The estimated value, , , Nonlinear d-axis current disturbance compensation module; The calculation formula for the nonlinear q-axis current disturbance compensation module is as follows: ; in, It is the q-axis current feedback signal The estimate, It is the nonlinear disturbance component acting on the q-axis current channel disturbance. The estimated value, , , Nonlinear Shaft current disturbance compensation module.

[0010] Preferably, in step S4, the system cost function is constructed: ;

[0011] in, , , As a weighting factor, , To predict the step size.

[0012] A dual-mode integrated predictive control system for synchronous motors, comprising: The signal acquisition module is used to acquire rotor position signals and winding current signals; The signal processing module, connected to the signal acquisition module, is used to convert the rotor position signal into rotor electrical angle and speed feedback signals, and to convert the three-phase current into current components in the rotating coordinate system. The model and compensation module is connected to the signal processing module and is used to construct the cross-coupled compensation module and the equivalent state space model, and to estimate and compensate for nonlinear disturbances through the nonlinear disturbance compensation module. The predictive control module, connected to the model and compensation module, is used to construct a cost function based on the error dynamic equation and output the optimal voltage command. The mode switching module is connected to the prediction control module and is used to dynamically adjust the cost function weight coefficients to achieve control mode switching. The execution module, connected to the predictive control module, is used to convert voltage commands into drive signals to control the synchronous motor.

[0013] Preferably, the signal acquisition module includes an encoder and a current sensor. The encoder is mounted on the rotor shaft of the synchronous motor, and the current sensor is used to acquire the three-phase winding current. The signal processing module includes 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 the current coordinate transformation.

[0014] Preferably, the model and compensation module includes a cross-decoupling compensation unit, a nonlinear velocity 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 to the velocity feedback output terminal and the current component output terminal of the signal processing module, and each nonlinear disturbance compensation unit is connected to the corresponding feedback signal output terminal and the equivalent state space model of the signal processing module.

[0015] Preferably, the predictive control module includes a speed / torque integrated predictive controller and a d-axis current predictive controller; the speed / torque integrated predictive controller outputs the optimal q-axis voltage command based on the speed error, q-axis current error and the weighting coefficient output by the mode switching module, and the d-axis current predictive controller outputs the optimal d-axis voltage command based on the d-axis current error.

[0016] Therefore, the synchronous motor dual-mode predictive control method, system, and wind power testing application using the above-described structure of the present invention have the following beneficial effects: (1) This invention constructs a unified predictive control framework that integrates the dual objectives of speed control and torque control modes. By introducing a mode switching mechanism to dynamically adjust the weight coefficients in the cost function, adaptive coordination between control objectives is achieved. This method effectively avoids the control conflicts and transient instability problems caused by the independent design of speed loop and torque loop in traditional cascaded control, and significantly improves the consistency and adaptability of the control strategy in the process of switching between multiple scenarios.

[0017] (2) The present invention adopts a simple control architecture, abandons the traditional multi-ring nested design mode, reduces parameter coupling between control links, simplifies the parameter tuning process of the controller, significantly reduces the engineering complexity of system deployment and debugging, and improves the maintainability and engineering practicality of the control system.

[0018] (3) The present invention designs nonlinear disturbance compensation modules for the speed channel, q-axis current channel and d-axis current channel respectively, which can effectively estimate and compensate for unknown nonlinear disturbances caused by external load and internal parameter perturbation in the synchronous motor control system, thereby significantly enhancing the robustness and anti-disturbance capability of the system and improving the dynamic performance and steady-state accuracy of the overall control system.

[0019] (4) The predictive controller designed in this invention 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 is particularly suitable for resource-constrained embedded control systems, providing a practical technical solution for industrial field deployment.

[0020] (5) Through the collaborative design of the control mode switcher and the unified predictive controller, the present invention can quickly respond to changes in wind conditions and switch test conditions, and has good versatility and scalability, which significantly improves the experimental efficiency and test effect of the wind energy test platform in application scenarios such as wind turbine development, control algorithm verification and fault condition simulation.

[0021] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the system of the present invention; Figure 2 This is a schematic diagram of the nonlinear velocity disturbance compensation module of the present invention; Figure 3 This is a schematic diagram of the nonlinear q-axis current disturbance compensation module of the present invention; Figure 4 This is a schematic diagram of the nonlinear d-axis current disturbance compensation module of the present invention; Figure 5 This is a schematic diagram of the system response when the control mode of the present invention switches from torque control to speed control; Figure 6 This is a schematic diagram of the system response when the control mode of the present invention switches from speed control to torque control; Figure 7 This is a schematic diagram illustrating the control performance verification under speed control mode; Figure 8 This is a schematic diagram for verifying torque control performance under torque control mode. Detailed Implementation

[0023] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0024] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0025] Example

[0026] This invention provides a dual-mode predictive control method, system, and wind power testing application for synchronous motors, such as... Figure 1 As shown. The system consists of the following modules: The encoder is mounted on the rotor shaft of the synchronous motor to acquire the rotor position signal of the motor. ; The angular velocity calculation module is used to perform differential calculations on the rotor position signal output by the encoder to obtain the angular velocity feedback signal. At the same time, the signal is filtered to reduce noise interference; Clarke converter is used to convert the acquired three-phase current signals of the synchronous motor. , , Converted to two-phase orthogonal Current components in coordinate system , .

[0027] Parker converter, used to adjust the rotor electrical angle The Clarke converter calculated , The current component is transformed to the dq rotating reference coordinate system to obtain its current component in the dq coordinate system. , .

[0028] The nonlinear speed disturbance compensation module is used to estimate the nonlinear disturbance components acting on the speed loop in real time based on the speed feedback signal and the dq-axis current feedback signal.

[0029] Nonlinear d-axis current disturbance compensation module, used to... The nonlinear disturbance component acting on the d-axis current channel is estimated in real time using the d-axis current feedback signal and the d-axis given voltage signal.

[0030] Nonlinear q-axis current disturbance compensation module, used to... The q-axis current feedback signal and q-axis voltage signal are used to estimate the nonlinear disturbance component acting on the q-axis current channel in real time.

[0031] The control mode switcher is used to dynamically adjust the speed / torque control weight factor according to actual control requirements, so as to achieve flexible switching of control modes.

[0032] The speed / torque integrated predictive controller constructs a unified cost function based on speed error and q-axis current error; according to the control weight coefficients output by the mode switcher, it outputs the optimal q-axis voltage command, realizing the integrated high-performance execution of speed control and torque control.

[0033] The d-axis current predictive controller constructs a cost function based on the d-axis current error and outputs the optimal d-axis voltage command to achieve precise control of the d-axis current.

[0034] The maximum torque-to-current ratio controller is used to calculate the corresponding optimal d-axis current command based on the q-axis feedback current signal in order to achieve the control objective of the maximum torque-to-current ratio.

[0035] Secondary maximum torque current ratio controller, used to determine the maximum torque current ratio based on a given torque signal. The corresponding optimal d-axis and q-axis current commands are calculated to achieve the control target of maximum torque-to-current ratio.

[0036] The cross-decoupling compensation module is used to calculate the voltage coupling components of the dq-axis current channels.

[0037] The inverse Park converter is used to convert the dq-axis given voltage signal calculated by the controller into a voltage signal in the three-phase stationary coordinate system. Space vector pulse width modulation (SVPWM module, which converts three-phase voltage commands into PWM switching signals that can be executed by the inverter); The three-phase inverter module receives PWM switching signals and drives the synchronous motor to run. Furthermore, this invention provides a dual-mode predictive control method for synchronous motors, the specific design steps of which are as follows: Step S1: Acquire the motor rotor position signal using an encoder. According to the rotor position signal The rotor electrical angle signal is calculated. By analyzing the rotor position signal output by the encoder Differential calculations and filtering are performed to obtain the speed feedback signal. Collect motor winding current signals. , , The motor was calculated using the Clarke converter. shaft and shaft current The motor obtained from the calculation shaft and shaft current , The d-axis and q-axis currents of the motor were calculated using the Park converter. , .

[0038] Step S2: Based on the speed feedback signal and dq axis current feedback signal , Construct a cross-coupling compensation module: ; in, , It is a cross-coupling compensation voltage. It is a speed feedback signal. , These are the d-axis and q-axis current feedback signals. , These are the inductances of the motor's d-axis and q-axis. It is the number of pole pairs of the motor. It is the magnetic flux of the motor.

[0039] Step S3: Based on the cross-coupling compensation module constructed in step S2, construct the equivalent state-space model of the synchronous motor in the dq coordinate system: ; in, , The equivalent voltages of the motor's d-axis and q-axis are defined as follows: , These are the actual voltages of the motor's d-axis and q-axis; , ; , ; , ; in, , These are the d-axis and q-axis currents of the motor, respectively. For motor magnetic flux; and These are the inductances of the motor's d-axis and q-axis, respectively. This represents the number of pole pairs of the motor. Stator resistance; It is the coefficient of viscous friction; For system inertia; , , These represent the nonlinear disturbance components acting on the velocity loop, q-axis current loop, and d-axis current loop, respectively. Step S4: Based on the equivalent system model and velocity feedback signal constructed in step S3 d-axis and q-axis current feedback signals , Nonlinear velocity disturbance compensation module: ; 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 for the nonlinear velocity disturbance compensation module.

[0040] Step S5: Estimate the nonlinear velocity disturbance signal output by the nonlinear velocity disturbance compensation module constructed in step S4. And the equivalent system model constructed in step S3, calculates how to maintain the motor at a given speed. The steady-state q-axis current is as follows: .

[0041] Step S6: Based on the equivalent system model constructed in step S3, and the q-axis current feedback signal and equivalent voltage signal Construct a nonlinear q-axis current disturbance compensation module: ; in, It is the q-axis current feedback signal The estimate, It is the nonlinear disturbance component acting on the q-axis current channel disturbance. The estimated value, , , Nonlinear q-axis current disturbance compensation module.

[0042] Step S7: Based on 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 Using the equivalent system model constructed in step S3, calculate how to maintain the motor at a given speed. The q-axis steady-state equivalent voltage is as follows: .

[0043] Step S8: Based on the system model obtained in step S3 and the d-axis current feedback signal and given voltage signal Construct a nonlinear d-axis current disturbance compensation module: ; in, It is the d-axis current feedback signal The estimate, It is the nonlinear disturbance component acting on the d-axis current channel disturbance. The estimated value, , , Nonlinear d-axis current disturbance compensation module.

[0044] Step S9: Based on the nonlinearity constructed in step S8 Nonlinear disturbance estimation signal output by the shaft current disturbance compensation module Using the equivalent system model constructed in step S3, calculate how to maintain the motor at a given d-axis current. The d-axis steady-state equivalent voltage is as follows: .

[0045] Step S10: Based on 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 rotational speed Construct the error dynamic equation of the equivalent system: ; in, , , , , These are the speed error, the motor's d-axis and q-axis current error, and the system's d-axis and q-axis equivalent voltage error, respectively.

[0046] Step S11: Based on the equivalent systematic error model obtained in step S10, use Taylor expansion to calculate the future prediction time length. Estimate the systematic error within: ; in, For the prediction matrix; This is the rotational speed error matrix; This is the q-axis current error matrix. This is the d-axis current error matrix.

[0047] Step S12: Based on the prediction model established in step S11, in order to achieve optimized control performance, the speed tracking error of the system is comprehensively considered. q-axis current tracking error and d-axis current error Construct the system cost function: ; in, , , As a weighting factor, , To predict the step size.

[0048] Step S13: Based on the q-axis speed feedback signal Construct a maximum torque-to-current ratio controller: ; in, It is the d-axis current command signal output by the controller at the maximum torque-to-current ratio.

[0049] Step S14: Based on the given torque Construct a second-order maximum torque-current ratio controller: ; in, , These are the d-axis and q-axis current command signals output by the secondary maximum torque current controller, respectively.

[0050] Step S15: The cost function constructed in step S12 Step S5 calculates the steady-state q-axis current that maintains a given rotational speed. The d-axis current command signal calculated in step S13 The d-axis current command signal calculated in step S14 and q-axis current command signal Construct a control mode switcher: ; in, , For logic variables controlling the mode switch; This indicates the control mode in which the controller will operate. This indicates the current control weights of the controller; This indicates that the controller is operating in speed mode; This indicates that the controller is operating in torque mode; This is the switching time. These are the parameters for controlling the mode switcher.

[0051] Step S16: Based on the cost function obtained in step S12, the prediction model obtained in step S11, and the weight coefficients output by the control mode switcher constructed in step S15... , Through further derivation, it can be equivalently expressed as follows: ; Step S17: Solve the cost function obtained in step S16. For control variables Partial derivatives: ; in, , , , , , .

[0052] make Thus, the optimal q-axis equivalent voltage error input is obtained: ; Step S18: Solve the cost function obtained in step S16. For control variables Partial derivatives: ; in, , , .

[0053] make Thus, the optimal d-axis equivalent voltage error input is obtained: ; 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: ; in, Provide a voltage signal for the q-axis. Provide a voltage signal for the d-axis.

[0054] Figures 2-4 The specific implementation block diagrams of the nonlinear velocity disturbance compensation module, the nonlinear q-axis current disturbance compensation module, and the nonlinear d-axis current disturbance compensation module are given respectively. The nonlinear velocity disturbance compensation module, the nonlinear q-axis current disturbance compensation module, and the nonlinear d-axis current disturbance compensation module can be implemented by reference.

[0055] Furthermore, the control parameter adjustment rules involved in the dual-mode integrated predictive controller of this invention are as follows: 1. Parameters in the nonlinear velocity disturbance compensation module , , Used to adjust the nonlinear speed disturbance compensation module for the nonlinear disturbance components acting on the speed channel. The compensation accuracy and speed meet the requirements. , , Its parameter size is positively correlated with compensation speed and accuracy.

[0056] 2. Parameters in the nonlinear velocity disturbance compensation module , , This is used to adjust the nonlinear q-axis current disturbance compensation module for the nonlinear disturbance component acting on the q-axis current channel. The compensation accuracy and speed meet the requirements. , , Its parameter size is positively correlated with compensation speed and accuracy.

[0057] 3. Parameters in the nonlinear velocity disturbance compensation module , , This is used to adjust the nonlinear d-axis current disturbance compensation module for the nonlinear disturbance component acting on the d-axis current channel. The compensation accuracy and speed meet the requirements. , , Its parameter size is positively correlated with compensation speed and accuracy.

[0058] 4. Parameters in the control mode switcher Used to adjust the transition time for control mode switching, to meet... Its parameter size is negatively correlated with the transition time.

[0059] 5. Parameters in the predictive controller and Used to adjust the prediction step size of the prediction controller to meet the following requirements. , The magnitude of its parameters is negatively correlated with the system's response speed.

[0060] Four operating conditions are set up to illustrate the effectiveness of the invention: 1. Operating Condition 1: Set the control mode to torque control, the torque reference to 6 Nm, the initial load to 5 Nm, and switch the control mode to speed control at 0.2 s, with the given speed to 1000 rpm.

[0061] 2. Operating Condition 2: Set the control mode to speed control, set the speed to 1000 rpm, and set the initial load to 5 Nm. After 2 seconds, switch the control mode to torque control, set the torque to 15 Nm, and set the load to 14.8 Nm.

[0062] 3. Operating Condition 3: The control mode is set to speed control, the set speed is 1000 rpm, the initial load is 5 Nm, the load is changed to 35 Nm at 0.15 s, and the set speed is modified at 0.3 s. rpm.

[0063] 4. Operating Condition 4: The control mode is set to torque control, the given torque is 15 Nm, and the given torque at 0.2 s is... Nm.

[0064] Figure 5 The response curves of motor speed, q-axis current, d-axis current, and output torque under operating condition 1 are presented. Figure 6 The response curves of motor speed, q-axis current, d-axis current, and output torque under operating condition 2 are presented. Figure 7 The response curves of motor speed, q-axis current, d-axis current, and output torque under operating condition 3 are presented. Figure 8 The response curves of motor output torque, q-axis current, and d-axis current under operating condition 4 are presented. The experimental results show that the dual-mode integrated predictive control method proposed in this invention not only supports flexible online switching of control modes but also enables fast and accurate tracking control of complex time-varying speed and torque commands. Simultaneously, this method effectively suppresses nonlinear disturbances acting on each channel of the system, significantly improving the dynamic response performance, disturbance rejection capability, and control flexibility of the synchronous motor control system.

[0065] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A dual-mode integrated predictive control method for synchronous motors, characterized in that, Includes the following steps: S1. Collect the rotor position signal and winding current signal of the synchronous motor, and process them to obtain the rotor electrical angle, speed feedback signal and current component in the two-phase rotating coordinate system. S2. Based on the speed feedback signal and current components, construct a cross-coupling compensation module and establish an equivalent state space model of the synchronous motor in the rotating coordinate system. S3. Based on the equivalent state space model and feedback signal, design a nonlinear disturbance compensation module to estimate and compensate for the nonlinear disturbance components of the speed loop and current loop. S4. Based on the equivalent state-space model, disturbance compensation results, and given control objective, construct a unified cost function that includes speed tracking error and current tracking error, and design a predictive controller. S5. By dynamically adjusting the weight coefficients in the cost function through the control mode switcher, adaptive switching between speed control mode and torque control mode is achieved, and the optimal voltage command is output to drive the synchronous motor.

2. The method according to claim 1, characterized in that, In step S1, the processing includes: acquiring rotor position signals through an encoder, obtaining speed feedback signals through differential calculation and filtering; converting the three-phase winding current into current components in a two-phase stationary coordinate system through a Clarke converter, and then converting them into d-axis and q-axis current components in a rotating coordinate system through a Park converter.

3. The method according to claim 1, characterized in that, In step S2, the construction formula for the cross-coupling compensation module is as follows: ； in, , It is a cross-coupling compensation voltage. It is a speed feedback signal. , yes shaft and Shaft current feedback signal, , These are the inductances of the motor's d-axis and q-axis. It is the number of pole pairs of the motor. It is the magnetic flux of the motor.

4. The method according to claim 1, characterized in that, In step S3, the nonlinear disturbance compensation module includes a nonlinear velocity disturbance compensation module, a nonlinear d-axis current disturbance compensation module, and a nonlinear q-axis current disturbance compensation module; wherein, the calculation formula for the nonlinear velocity 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; The calculation formula for the nonlinear d-axis current disturbance compensation module is as follows: ； in, It is the d-axis current feedback signal The estimate, It is the nonlinear disturbance component acting on the d-axis current channel disturbance. The estimated value, , , Nonlinear d-axis current disturbance compensation module; The calculation formula for the nonlinear q-axis current disturbance compensation module is as follows: ； in, It is the q-axis current feedback signal The estimate, It is the nonlinear disturbance component acting on the q-axis current channel disturbance. The estimated value, , , Nonlinear Shaft current disturbance compensation module.

5. The method according to claim 1, characterized in that, In step S4, the system cost function is constructed: ； in, , , As a weighting factor, , To predict the step size.

6. A synchronous motor dual-mode integrated predictive control system, characterized in that, include: The signal acquisition module is used to acquire rotor position signals and winding current signals; The signal processing module, connected to the signal acquisition module, is used to convert the rotor position signal into rotor electrical angle and speed feedback signals, and to convert the three-phase current into current components in the rotating coordinate system. The model and compensation module is connected to the signal processing module and is used to construct the cross-coupled compensation module and the equivalent state space model, and to estimate and compensate for nonlinear disturbances through the nonlinear disturbance compensation module. The predictive control module, connected to the model and compensation module, is used to construct a cost function based on the error dynamic equation and output the optimal voltage command. The mode switching module is connected to the prediction control module and is used to dynamically adjust the cost function weight coefficients to achieve control mode switching. The execution module, connected to the predictive control module, is used to convert voltage commands into drive signals to control the synchronous motor.

7. The system according to claim 6, characterized in that, The signal acquisition module includes an encoder and a current sensor. The encoder is mounted on the rotor shaft of the synchronous motor, and the current sensor is used to acquire the three-phase winding current. The signal processing module includes 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 the current coordinate transformation.

8. The system according to claim 6, characterized in that, The model and compensation module includes a cross-decoupling compensation unit, a nonlinear velocity 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 to the velocity feedback output terminal and the current component output terminal of the signal processing module, and each nonlinear disturbance compensation unit is connected to the corresponding feedback signal output terminal and the equivalent state space model of the signal processing module.

9. The system according to claim 6, characterized in that, The predictive control module includes a speed / torque integrated predictive controller and a d-axis current predictive controller. The speed / torque integrated predictive controller outputs the optimal q-axis voltage command based on the speed error, q-axis current error, and weighting coefficients output by the mode switching module. The d-axis current predictive controller outputs the optimal d-axis voltage command based on the d-axis current error.

10. A wind power testing platform wind energy simulation system, characterized in that, The synchronous motor dual-mode integrated predictive control method according to any one of claims 1-4, or the synchronous motor dual-mode integrated predictive control system according to any one of claims 6-9, is used to simulate the actual dynamic characteristics of the wind turbine and realize the reproduction of the aerodynamic forces on the main shaft of the wind turbine.

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