Speed control method, device and equipment of permanent magnet synchronous motor and storage medium

Abstract

The invention discloses a speed control method, device and equipment of a permanent magnet synchronous motor and a storage medium, relates to the technical field of permanent magnet synchronous motor control, and discloses the speed control method of the permanent magnet synchronous motor, which comprises the following steps: constructing an integrated speed controller according to a composite nonlinear feedback strategy and a sliding mode control strategy; constructing a collaborative observer according to the collaborative observer strategy; obtaining an estimated load of the permanent magnet synchronous motor, and calculating current feed-forward compensation according to the estimated load to obtain a feed-forward compensation gain value; and calculating a control signal value according to the feedforward compensation gain value, the integrated speed controller and the cooperative observer, and completing speed control of the permanent magnet synchronous motor according to the control signal value. Through a technical means of combining a composite nonlinear feedback strategy, a sliding mode control strategy and a collaborative observer strategy, high-precision and stable speed control of the permanent magnet synchronous motor under the conditions of parameter uncertainty and load disturbance is realized.

Description

Technical Field

[0001] This application relates to the technical field of permanent magnet synchronous motor control, and particularly to a speed control method, device, equipment and storage medium for a permanent magnet synchronous motor. Background Art

[0002] When a permanent magnet synchronous motor is applied to technical fields such as precision control of electric vehicles, industrial robots, and aviation, it is required that the motor control system can achieve high-precision speed tracking performance.

[0003] Traditional control methods such as a single proportional-integral (PI) controller or basic sliding mode control (SMC) can meet the requirements of fast response and robustness to a certain extent, but it is often difficult to maintain high-precision speed tracking in the face of parameter uncertainties, load disturbances, and variable operating conditions.

[0004] The above content is only used to assist in understanding the technical solution of this application, and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main purpose of this application is to provide a speed control method, device, equipment and storage medium for a permanent magnet synchronous motor, aiming to solve the technical problem of how to improve the speed control accuracy and stability of a permanent magnet synchronous motor in the face of parameter uncertainties and load disturbances.

[0006] To achieve the above purpose, this application proposes a speed control method for a permanent magnet synchronous motor, and the method includes:

[0007] Construct an integrated speed controller according to the composite nonlinear feedback strategy and the sliding mode control strategy;

[0008] Construct a cooperative observer according to the cooperative observer strategy;

[0009] Obtain the estimated load of the permanent magnet synchronous motor, and calculate the current feedforward compensation according to the estimated load to obtain the feedforward compensation gain value;

[0010] Calculate the control signal value according to the feedforward compensation gain value, the integrated speed controller, and the cooperative observer, and complete the speed control of the permanent magnet synchronous motor according to the control signal value.

[0011] In addition, to achieve the above purpose, this application also proposes a speed control device for a permanent magnet synchronous motor, and the speed control device for the permanent magnet synchronous motor includes: a controller construction module, configured to construct an integrated speed controller according to the composite nonlinear feedback strategy and the sliding mode control strategy;

[0012] An observer construction module, configured to construct a cooperative observer according to a cooperative observer strategy;

[0013] A gain value calculation module, configured to obtain an estimated load of a permanent magnet synchronous motor, and calculate a current feedforward compensation according to the estimated load to obtain a feedforward compensation gain value;

[0014] A speed control module, configured to calculate a control signal value according to the feedforward compensation gain value, the integrated speed controller, and the cooperative observer, and complete the speed control of the permanent magnet synchronous motor according to the control signal value.

[0015] In addition, to achieve the above object, the present application further provides a speed control device for a permanent magnet synchronous motor, the device including: a memory, a processor, and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the speed control method for a permanent magnet synchronous motor as described above.

[0016] In addition, to achieve the above object, the present application further provides a storage medium, the storage medium being a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the speed control method for a permanent magnet synchronous motor as described above are implemented.

[0017] In addition, to achieve the above object, the present application further provides a computer program product, the computer program product including a computer program, and when the computer program is executed by a processor, the steps of the speed control method for a permanent magnet synchronous motor as described above are implemented.

[0018] One or more technical solutions proposed by the present application have at least the following technical effects:

[0019] By combining a composite nonlinear feedback strategy, a sliding mode control strategy, and a cooperative observer strategy, an integrated speed controller is constructed. By combining the composite nonlinear feedback strategy and the sliding mode control strategy, the robustness and anti-disturbance ability of the system are effectively improved, ensuring that the permanent magnet synchronous motor can maintain high-precision speed control in the face of load disturbances and parameter uncertainties. Secondly, the cooperative observer strategy can accurately estimate the load torque and perform current feedforward compensation through the load estimation value, thereby effectively reducing the influence of load disturbances on the system. By calculating the control signals of the feedforward compensation gain value, the output of the integrated speed controller, and the output of the cooperative observer, the precise speed control of the motor is finally completed. Compared with the prior art, this solution overcomes the problems of insufficient response to load disturbances and system instability in traditional control methods through precise load estimation and an adaptive compensation mechanism. This solution enables the permanent magnet synchronous motor to maintain higher control precision and stronger adaptability under more complex working conditions, thus significantly improving the dynamic response and stability of the control system. Description of the Drawings

[0020] The drawings herein are incorporated into and form a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0021] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0022] Figure 1 It is a schematic flowchart provided for the first embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0023] Figure 2 It is a control block diagram of the permanent magnet synchronous motor provided for the first embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0024] Figure 3 It is a schematic flowchart provided for the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0025] Figure 4 It is a cooperative observer block diagram provided for the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0026] Figure 5(a) is a schematic diagram of the no-load area speed response of the speed controller provided for the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0027] Figure 5(b) is a schematic diagram of the speed response of the speed controller in the variable load area provided for the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0028] Figure 5(c) is a schematic diagram of the overshoot speed and overshoot speed response of the speed controller provided for the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0029] Figure 5(d) is a schematic diagram of the steady-state response time speed response of the speed controller provided for the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0030] Figure 6(a) is a schematic diagram of the no-load area speed response with different parameters provided for the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0031] Figure 6(b) is a schematic diagram of the speed response in the variable load area with different parameters provided for the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0032] Figure 6(c) is a schematic diagram of the overshoot speed and overshoot speed response of different parameters provided by the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0033] Figure 6(d) is a schematic diagram of the steady-state response time speed response of different parameters provided by the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0034] Figure 7(a) is a schematic diagram of SMO load torque estimation provided by the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0035] Figure 7(b) is a schematic diagram of SO load torque estimation provided by the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0036] Figure 8(a) is a schematic diagram of the speed response in the load change area provided by the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0037] Figure 8(b) is a detailed schematic diagram of Figure 8(a) provided by the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0038] Figure 9(a) is a schematic diagram of the q-axis current iq current response provided by the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0039] Figure 9(b) is a schematic diagram of the a-phase current ia current response provided by the second embodiment of the speed control method of the permanent magnet synchronous motor of the present application;

[0040] Figure 10 It is a schematic diagram of the brief flow of the speed control method of the permanent magnet synchronous motor provided by the second embodiment of the present application;

[0041] Figure 11 It is a schematic diagram of the module structure of the speed control device of the permanent magnet synchronous motor according to the embodiment of the present application;

[0042] Figure 12 It is a schematic diagram of the device structure of the hardware operating environment involved in the speed control method of the permanent magnet synchronous motor in the embodiment of the present application.

[0043] The realization, functional characteristics and advantages of the purpose of the present application will be further described with reference to the embodiments and the accompanying drawings. Detailed implementation manners

[0044] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0045] In order to better understand the technical solutions of the present application, the following will be described in detail with reference to the accompanying drawings of the specification and specific implementation manners.

[0046] The main solution of the embodiment of this application is: constructing an integrated speed controller according to the composite nonlinear feedback strategy and the sliding mode control strategy; constructing a cooperative observer according to the cooperative observer strategy; obtaining the estimated load of the permanent magnet synchronous motor, and calculating the current feedforward compensation according to the estimated load to obtain a feedforward compensation gain value; calculating a control signal value according to the feedforward compensation gain value, the integrated speed controller and the cooperative observer, and completing the speed control of the permanent magnet synchronous motor according to the control signal value.

[0047] In this embodiment, for the convenience of description, the speed control device for identifying the permanent magnet synchronous motor is used as the execution subject for the following elaboration.

[0048] Since the prior art on how to improve the speed control accuracy and stability of permanent magnet synchronous motors in the face of parameter uncertainty and load disturbance, this application provides a solution. By combining the composite nonlinear feedback strategy, the sliding mode control strategy and the cooperative observer strategy, an integrated speed controller is constructed. By combining the composite nonlinear feedback strategy and the sliding mode control strategy, the robustness and anti-disturbance ability of the system are effectively improved, ensuring that the permanent magnet synchronous motor can maintain high-precision speed control in the face of load disturbance and parameter uncertainty. Secondly, the cooperative observer strategy can accurately estimate the load torque and perform current feedforward compensation through the load estimated value, thereby effectively reducing the impact of load disturbance on the system. By calculating the control signal of the feedforward compensation gain value, the output of the integrated speed controller and the output of the cooperative observer, the precise speed control of the motor is finally completed. Compared with the prior art, this solution overcomes the problems of insufficient response to load disturbance and system instability in traditional control methods through accurate load estimation and an adaptive compensation mechanism. This solution enables the permanent magnet synchronous motor to maintain higher control accuracy and stronger adaptability under more complex working conditions, thus significantly improving the dynamic response and stability of the control system.

[0049] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of implementing the above functions, a speed control device for a permanent magnet synchronous motor, etc. The following takes the speed control device of the permanent magnet synchronous motor as an example to illustrate this embodiment and the following embodiments.

[0050] Based on this, the embodiment of this application provides a speed control method for a permanent magnet synchronous motor, referring to Figure 1 , Figure 1 is a schematic flowchart of the first embodiment of the speed control method for the permanent magnet synchronous motor of this application.

[0051] In this embodiment, the speed control method for the permanent magnet synchronous motor includes steps S10 to S40:

[0052] Step S10, construct an integrated speed controller according to the composite nonlinear feedback strategy and the sliding mode control strategy;

[0053] It should be noted that the composite nonlinear feedback strategy (CNF) is a strategy that optimizes control performance by combining linear feedback and nonlinear feedback. Linear feedback provides fast dynamic regulation ability, and nonlinear feedback adjusts the system response by introducing nonlinear functions, optimizing the fast convergence ability when the error is large and the stability when the error is small, reducing overshoot and improving dynamic performance. This strategy achieves better control effects by adjusting feedback gains and nonlinear function parameters.

[0054] In addition, the sliding mode control strategy (SMC) is a nonlinear control method based on a sliding surface, aiming to make the target variable quickly and robustly tend to the expected value under uncertainty and external disturbances. The core of sliding mode control is to define the sliding surface, that is, the expected state trajectory of the system and drive the system state to the sliding surface through the reaching law. The sliding mode control strategy usually includes a switching function, an exponential reaching law, and a dynamic adjustment term to improve accuracy and robustness.

[0055] It can be understood that the integrated speed controller is a controller designed by combining the composite nonlinear feedback strategy and the sliding mode control strategy, and is dedicated to the speed regulation of permanent magnet synchronous motors. When controlling the motor speed, the composite nonlinear feedback strategy can dynamically adjust the feedback gain when the speed error is small to avoid over-regulation; the sliding mode control strategy designs a sliding surface, and when the motor speed deviates from the target value, the speed state is quickly pulled back to the target value through the reaching law defined by the sliding surface. By combining the two, the integrated speed controller can ensure both fast response and control robustness. By integrating the advantages of the two strategies, the integrated speed controller can achieve fast response, precise control, and maintain high stability and robustness under load disturbances and parameter uncertainties.

[0056] In a feasible implementation, step S10 may include steps S11 to S14:

[0057] Step S11, obtain the rotor mechanical angular velocity tracking error and the change rate of the rotor mechanical angular velocity tracking error according to the permanent magnet synchronous motor speed state equation;

[0058] It should be noted that the permanent magnet synchronous motor speed state equation is a mathematical model that describes the dynamic behavior of the motor speed, and is used to express the relationship between the change of the speed and system parameters such as rotor inertia, motor damping coefficient, load torque, and q-axis current.

[0059] In this embodiment, the speed state equation of the permanent magnet synchronous motor is as follows:

[0060]

[0061] In the speed state equation of the permanent magnet synchronous motor, i q is the q-axis current; T L is the load torque; B m is the motor viscous damping; ω m is the rotor mechanical angular velocity; J m is the motor moment of inertia; P n represents the number of pole pairs of the motor; ψ f is the permanent magnet flux linkage.

[0062] In addition, the rotor mechanical angular velocity tracking error is the target speed, that is, the difference between the rotor mechanical angular velocity reference value and the current actual speed, which is used to reflect the degree to which the current speed of the motor deviates from the target speed. The change rate of the rotor mechanical angular velocity tracking error is the rate of change of the error with time, which is used to describe the dynamic change trend of the speed error. The calculation of the rotor mechanical angular velocity tracking error is as follows:

[0063] e ω = ω m - ω re f

[0064] In the calculation formula of the rotor mechanical angular velocity tracking error, ω m is the rotor mechanical angular velocity; ω ref represents the rotor mechanical angular velocity reference value.

[0065] It can be understood that the dynamic change of the speed is described by using the speed state equation of the permanent magnet synchronous motor, and the dynamic behavior of the current speed is calculated based on parameters such as the q-axis current, the motor moment of inertia, the load torque, and the damping coefficient. By comparing the target speed and the actual speed, the rotor mechanical angular velocity tracking error is calculated to reflect the deviation degree of the motor speed. By analyzing the time change of the speed error, the error change rate is obtained to describe the trend of the deviation change. These two key variables provide the basic data support for the subsequent construction of the sliding mode surface and the design of the control law.

[0066] Step S12, construct a nonlinear sliding mode surface equation according to the composite nonlinear feedback strategy, the speed state equation of the permanent magnet synchronous motor, the rotor mechanical angular velocity tracking error, and the change rate of the rotor mechanical angular velocity tracking error;

[0067] It should be noted that the nonlinear sliding mode surface equation is used to describe the target dynamic behavior of the system, combines nonlinear feedback design to optimize the control path, and enhances the robustness of the control system.

[0068] It can be understood that the composite non - linear feedback strategy dynamically adjusts the speed error and its change rate by defining the feedback gain and the non - linear correction function. By combining with the speed state equation of the permanent - magnet synchronous motor, a non - linear sliding surface is defined using the speed error and the error change rate.

[0069] In a feasible implementation manner, step S12 may include steps S121 to S124:

[0070] Step S121, obtain a constant matrix;

[0071] It can be understood that the constant matrix is a matrix composed of fixed values, which is usually used in control algorithms to calibrate specific parameters with fixed values. It can represent the static characteristics of the controller and ensure the stability in the control process. In the design of control systems, the constant matrix is usually used to determine the dynamic behavior of the system, such as constructing the gain matrix for state feedback or observers.

[0072] Step S122, according to the speed state equation of the permanent - magnet synchronous motor, obtain the reference value of the rotor mechanical angular velocity and the current value of the rotor mechanical angular velocity;

[0073] It should be noted that the reference value of the rotor mechanical angular velocity is the expected value of the control target speed and is used as the benchmark for speed regulation. It is usually set by an external input signal, such as the target speed set by the control system. Its value remains constant or changes dynamically over time and is used to guide the output of the controller.

[0074] In addition, the current value of the rotor mechanical angular velocity is the actual speed of the permanent - magnet synchronous motor at the current moment, which is usually measured by a sensor or estimated by an observer. After comparing with the reference value of the rotor mechanical angular velocity, the speed error is calculated to provide a feedback signal for the controller to adjust.

[0075] It can be understood that the speed state equation of the permanent - magnet synchronous motor is used to calculate and obtain the reference angular velocity and the current actual angular velocity of the motor. The reference angular velocity is the control target, that is, the ideal speed value that the motor needs to reach at a specific time point; while the current angular velocity is the actual value measured by the sensor in real - time during the operation of the motor. The speed state equation is a mathematical model that describes the dynamic characteristics of the motor and is used to relate factors such as the q - axis current, load torque, moment of inertia, etc., so as to deduce the dynamic change of the speed.

[0076] Step S123, according to the composite non - linear feedback strategy, obtain the composite non - linear feedback gain parameter, the non - linear correction function, and the state - feedback gain matrix;

[0077] It should be noted that the composite non - linear feedback gain parameter is an adaptive gain coefficient used to control the non - linear feedback part in the system. This parameter optimizes the control performance by adjusting the gain in real - time. It usually includes linear and non - linear parts to achieve low overshoot and fast response. The gain parameter may be dynamically adjusted according to the magnitude of the tracking error. When the error is large, the gain is higher to accelerate convergence, and when the error is small, the gain is reduced to reduce overshoot.

[0078] In addition, the non - linear correction function is a function used to compensate for the dynamic non - linear behavior of the system. By analyzing the non - linear characteristics of the motor error, the output of the controller is corrected. For example, when the error changes rapidly, the correction function can increase the control force non - linearly to approach the target state more quickly. The state - feedback gain matrix refers to the matrix in the control system that is used to perform weighted feedback on system state variables such as rotational speed, position, current, etc., for closed - loop control. It can assign different weights to state variables to optimize the overall control effect.

[0079] It can be understood that the composite non - linear feedback gain parameter is an important part of the controller for dynamically adjusting the gain of the controller. When the error is large, the gain parameter increases to enhance the control output force; when the error is small, the gain parameter decreases to avoid system overshoot caused by excessive control output. The non - linear correction function dynamically adjusts the non - linear part of the controller by analyzing the non - linear characteristics of the error, such as correcting the control output according to the square value of the error or other non - linear relationships. The state - feedback gain matrix is used to balance the weights of multiple system state variables, such as rotational speed error, error change rate, etc., providing important parameters for constructing the control law.

[0080] Step S124, construct a non - linear sliding mode surface equation according to the constant matrix, the rotor mechanical angular velocity tracking error, the rotor mechanical angular velocity reference value, the rotor mechanical angular velocity current value, the rotor mechanical angular velocity tracking error change rate, the composite non - linear feedback gain parameter, the non - linear correction function, and the state - feedback gain matrix.

[0081] It can be understood that the above - obtained parameters and error information are integrated to construct a non - linear sliding mode surface equation. The non - linear sliding mode surface equation defines the ideal control target surface, and the controller needs to drive the actual state to the sliding mode surface and maintain stability by adjusting the output. The non - linear sliding mode surface equation is as follows:

[0082]

[0083] In the non - linear sliding mode surface equation, c CNF represents the adaptive gain with CNF advantages; e ω represents the rotor mechanical angular velocity tracking error; represents the change rate of the rotor mechanical angular velocity tracking error; ω ref represents the reference value of the rotor mechanical angular velocity; F represents the state feedback gain matrix; ρ(ω ref , ω m ) represents the nonlinear correction function, and the output is a dynamic correction value, which can dynamically adjust the nonlinear part of the feedback control; represents the transpose of the constant matrix; ω m represents the actual value of the rotor mechanical angular velocity.

[0084] Step S13, according to the sliding mode control strategy, the nonlinear sliding mode surface equation, the rotor mechanical angular velocity tracking error, and the change rate of the rotor mechanical angular velocity tracking error, construct an adaptive exponential reaching law equation;

[0085] It should be noted that the adaptive exponential reaching law equation optimizes the dynamic performance and anti-chattering ability of the sliding mode control by dynamically adjusting the reaching rate and smoothing factor of the system.

[0086] It can be understood that, based on the sliding mode control strategy, an adaptive exponential reaching law is designed by using the nonlinear sliding mode surface equation, the velocity error and its change rate. By introducing the sign function and the exponential reaching term, the adaptive exponential reaching law equation ensures that the system state quickly converges to the sliding mode surface, and at the same time suppresses chattering through the nonlinear adjustment mechanism, enhancing the dynamic performance of the control.

[0087] In a feasible implementation manner, step S13 may include steps S131 to S134:

[0088] Step S131, according to the sliding mode control strategy, obtain the sliding mode exponential reaching law strategy;

[0089] It should be noted that the sliding mode exponential reaching law strategy is a key control strategy in sliding mode control, which is used to solve the problem of rapid convergence of the system state from the initial state to the sliding mode surface. It controls the reaching process to ensure that the system state can reach the sliding mode surface smoothly and quickly, while avoiding the chattering problem caused by too frequent switching in traditional sliding mode control. The sliding mode exponential reaching law strategy usually designs the reaching law so that the system state can not only quickly approach the target sliding mode surface, but also smoothly decelerate when approaching the sliding mode surface, thereby reducing jitter. The characteristic of the exponential reaching law is that the control law gradually weakens as the system state approaches, providing a smoother control effect.

[0090] It can be understood that the core of the sliding mode control strategy is to quickly drive the system state to the sliding mode surface and run along the sliding mode surface through controller design. The introduction of the exponential reaching law strategy can further optimize this process by dynamically adjusting the reaching speed and control force, reducing the jitter when the system state reaches the sliding mode surface.

[0091] Step S132: Obtain a switching function, a switching gain factor, and an exponential factor according to the sliding mode exponential reaching law strategy.

[0092] It should be noted that the switching function is the core element in sliding mode control and is used to determine when the system switches the control strategy or direction. The switching function is usually defined based on the sliding mode surface equation. When the system state deviates from the sliding mode surface, the switching function drives the controller to adjust the output and pushes the system state towards the sliding mode surface. Additionally, the switching gain factor is a parameter used in sliding mode control to adjust the switching intensity. The gain factor determines the strength of the switching control. When the gain factor is large, the controller has a stronger ability to correct errors; when the gain factor is small, the adjustment strength of the controller is weak. The gain factor can be determined through experiments or empirical methods, ensuring both sufficient speed of the control system and avoiding system oscillations caused by excessive control inputs. Additionally, the exponential factor is a parameter that determines the convergence speed when the system state approaches the sliding mode surface. The role of the exponential factor is to make the reaching process smoother by adjusting the nonlinear part of the control law and reduce the chattering problem of the system. At the beginning when the system deviates from the sliding mode surface, the exponential factor may increase the reaching speed; while when the state approaches the sliding mode surface, the exponential factor slows down the reaching speed to avoid overshoot of the state.

[0093] It can be understood that through the sliding mode exponential reaching law strategy, the switching function, the switching gain factor, and the exponential factor are designed. The switching function is used to define the switching conditions and direction of the control system. For example, when the error increases positively, the switching function triggers a negative adjustment; while when the error decreases, the switching function may stop output or gradually weaken. The switching gain factor is used to control the intensity of the switching action, and the exponential factor determines the nonlinear characteristics of the reaching process. This process requires determining the parameter values in combination with the error range and dynamic characteristics of the actual system. For example, when the error range is large, a switching function with a large gain factor can be designed to accelerate the system response speed; while when the error is small, the exponential factor can gradually decrease to smooth the control output.

[0094] Step S133: Calculate the error state quantity according to the rotor mechanical angular velocity tracking error and the change rate of the rotor mechanical angular velocity tracking error.

[0095] It should be noted that the error state quantity is a mathematical expression describing the system error in the sliding mode control process, usually including the rotor mechanical angular velocity tracking error and the change rate of the rotor mechanical angular velocity tracking error. It is used to characterize the deviation degree between the current state and the target state of the system. Exemplarily, if the target speed is 2000 revolutions per minute and the current speed is 1800 revolutions per minute, the error state quantity includes the speed error (200 revolutions per minute) and the change trend of the speed error (for example, increasing by 20 revolutions per minute per second).

[0096] It is understandable that the process of calculating the error state quantity needs to combine sensor measurement data and control objectives. For example, the sensor measures the current rotational speed in real time and compares it with the set target rotational speed to obtain the current error; then, according to the change of the error between two consecutive samplings, the error change rate is calculated. These data are combined to characterize the deviation degree between the current state and the target state of the system. The calculation of the error state quantity is as follows:

[0097]

[0098] In the calculation formula of the error state quantity, e ω represents the tracking error of the rotor mechanical angular velocity; represents the change rate of the tracking error of the rotor mechanical angular velocity.

[0099] Step S134, construct an adaptive exponential reaching law equation according to the nonlinear sliding mode surface equation, the switching function, the switching gain factor, the exponential factor, and the error state quantity.

[0100] It is understandable that all the parameters and information obtained in the previous steps are combined to construct an adaptive exponential reaching law equation. The function of this equation is to dynamically adjust the output of the controller according to the error state quantity and the real-time system operating state to ensure that the system state can quickly and smoothly approach the sliding mode surface and stay on the sliding mode surface. The adaptive exponential reaching law equation is as follows:

[0101]

[0102] In the adaptive exponential reaching law equation, e z represents the error state quantity; ε1>0 represents the switching gain factor; ε2>0 represents the exponential factor; σ>0 represents a small constant value; sgn() represents the switching function; s CNF represents the nonlinear sliding mode surface equation.

[0103] Step S14, construct an integrated speed controller according to the permanent magnet synchronous motor speed state equation, the nonlinear sliding mode surface equation, and the adaptive exponential reaching law equation.

[0104] It is understandable that the permanent magnet synchronous motor speed state equation, the nonlinear sliding mode surface equation, and the adaptive exponential reaching law equation are combined, and an integrated speed controller is designed by synthesizing these dynamic equations. The controller adjusts the control signal in real time to ensure that the speed error converges quickly, while maintaining high robustness and response speed. The integrated speed controller is as follows:

[0105]

[0106] In the integrated speed controller equation, iq represents the q-axis current component; i qmax represents the maximum q-axis current component; sat() and sgn() represent the saturation function and the switching function respectively; c CNF represents the adaptive gain with CNF advantages; ω ref represents the reference value of the rotor mechanical angular velocity; e ω represents the tracking error of the rotor mechanical angular velocity; represents the rate of change of the tracking error of the rotor mechanical angular velocity; e z represents the system state variable; ε1 > 0 represents the switching gain factor; ε2 > 0 represents the exponential factor; σ > 0 represents a small value; J m represents the moment of inertia of the motor rotor; P n represents the number of pole pairs of the motor; ψ f represents the permanent magnet flux linkage of the motor; B m represents the damping coefficient of the motor.

[0107] Step S20, construct a cooperative observer according to the cooperative observer strategy;

[0108] It should be noted that the cooperative observer strategy (SO) is a real-time state estimation method based on the error vector, used to estimate the state variables that are difficult to directly measure in the system, such as load torque and speed error. The cooperative observer adjusts the estimated value by using the system dynamic equation and the feedback error to ensure that the estimated state variable is close to the actual value. The cooperative observer strategy is usually realized by designing the error dynamic equation and the gain parameters. Additionally, the cooperative observer is a tool for estimating state variables through the dynamic equation and error feedback. The cooperative observer combines the error vector, gain parameters, and cooperative observer control parameters to perform real-time estimation of the key variables in the system for subsequent compensation or control.

[0109] In this embodiment, an error dynamic adjustment equation can be designed in combination with the cooperative observer strategy, and the cooperative observer gain parameters can be selected to optimize the convergence speed and estimation accuracy of the observer. The state equation of the rotor mechanical angular velocity is used to calculate the estimated value of the load torque and the estimated value of the rotor mechanical angular velocity through the dynamic equation. According to the estimated value of the load torque, the estimated value of the rotor mechanical angular velocity, and the cooperative observer gain parameters, the construction of the cooperative observer is completed.

[0110] Step S30, obtain the estimated load of the permanent magnet synchronous motor, and calculate the current feedforward compensation according to the estimated load to obtain the feedforward compensation gain value;

[0111] It should be noted that the estimated load is the estimated value of the load torque obtained through the cooperative observer, which is used to reflect the influence of the external load on the permanent magnet synchronous motor during the current operation. The load torque is one of the important factors affecting the motor performance. When the load increases, the motor requires additional input power to maintain the target speed. Since the load torque is difficult to measure directly, the estimated load is calculated in real time through the observer combined with error feedback and the motor dynamic equation. This estimated load provides data support for subsequent current compensation, thereby reducing the influence of load disturbance on speed control.

[0112] It can be understood that the current feedforward compensation is a method of directly calculating the compensation current through the estimated load torque. The compensation current based on the load estimated value directly cancels out the influence of the load on the motor speed, avoiding speed fluctuations caused by load changes. Different from traditional feedback control, the goal of feedforward compensation is to compensate for disturbances in advance, thereby improving the response speed and disturbance rejection ability of the control system. The magnitude of the compensation current is directly calculated from the load estimated value and the parameters of the motor, which is an important means to achieve fast and stable control.

[0113] In addition, the feedforward compensation gain value is the current compensation amount calculated through the estimated load torque and the motor parameters, which is used to adjust the gain of the control signal of the motor. The magnitude of the gain value is related to the current load state and operation requirements of the motor, and directly affects the output stability of the motor. It is the result of comprehensive current feedforward compensation, which is used to reduce the influence of load disturbance on the motor speed.

[0114] Exemplarily, the current load torque is estimated by combining the rotor mechanical angular velocity error and the load disturbance model to obtain the estimated load. Using the parameters of the motor, such as the rotor inertia, motor flux linkage, etc., and the estimated load, the magnitude of the compensation current is derived so that the compensation current can effectively counteract the disturbance caused by the load torque.

[0115] Step S40, calculate the control signal value according to the feedforward compensation gain value, the integrated speed controller, and the cooperative observer, and complete the speed control of the permanent magnet synchronous motor according to the control signal value.

[0116] It should be noted that the control signal value is the final control quantity calculated through the feedforward compensation gain value, the output of the integrated speed controller, and the estimated value of the cooperative observer, which is used to adjust the motor input to achieve the target speed. This signal synthesizes the output results of current compensation and speed closed-loop control, and is the core signal in the speed control process. In this embodiment, the control signal value can be the reference current.

[0117] It is understandable that a current compensation signal is calculated through the feedforward compensation gain value to pre-cancel the influence of load disturbance on speed. The feedforward compensation gain value is directly calculated from the estimated load torque and motor parameters to ensure that the compensation signal can accurately match the current load. The output signal of the integrated speed controller, which is based on the sliding mode control strategy and the composite nonlinear feedback strategy, dynamically adjusts the rotor mechanical angular velocity error and its change rate, thereby correcting the speed error and enhancing the robustness of the system. The cooperative observer provides the estimation results of the state variables during this process, including the estimated value of the load torque and the estimated value of the speed error, for further optimizing the control signal. The control signal value is calculated by integrating the feedforward compensation signal, the output signal of the integrated speed controller, and the estimation value of the cooperative observer. By inputting the control signal value into the permanent magnet synchronous motor, precise regulation of the motor speed is achieved. Throughout the process, the control signal value is continuously adjusted in real time to adapt to external load changes and dynamic environments, thereby ensuring the stability and accuracy of the motor speed. The calculation of the control signal value is as follows:

[0118]

[0119] In the control current calculation formula, represents the reference current. △i q represents the compensation current according to the load torque. k t >0 represents the feedforward compensation gain; i q represents the q-axis current component; i qmax represents the maximum q-axis current component; sat(), sgn() represent the saturation function and the switching function respectively; c CNF represents the adaptive gain with the advantages of CNF; ω ref represents the reference value of the rotor mechanical angular velocity; e ω represents the rotor mechanical angular velocity tracking error; represents the change rate of the rotor mechanical angular velocity tracking error; e z represents the system state quantity; ε1>0 represents the switching gain factor; ε2>0 represents the exponential factor; σ>0 represents a small value; J m represents the moment of inertia of the motor rotor; P n represents the number of pole pairs of the motor; ψ f represents the permanent magnet flux linkage of the motor; B m represents the damping coefficient of the motor. Additionally, sat(i q ) is the output of the integrated speed controller; △i q is the feedforward compensation current value, and is where, k t is the feedforward compensation gain constant, is the estimated load torque. Finally, sat(i q ) and △i qAdd them to obtain a reference current signal, that is,

[0120] In a feasible implementation, step S40 may include steps S41 to S43:

[0121] Step S41, obtain a current feedforward compensation signal value according to the feedforward compensation gain value;

[0122] It should be noted that the current feedforward compensation signal value is a control signal obtained according to the feedforward compensation gain value.

[0123] It can be understood that a current feedforward compensation signal value can be obtained by using the feedforward compensation gain value, and the setting of the feedforward compensation gain value is based on the estimated load torque. Exemplarily, when the load is expected to increase, by adjusting the gain value, the speed fluctuation caused by the load disturbance can be avoided.

[0124] Step S42, calculate a speed closed-loop control signal value according to the integrated speed controller and the cooperative observer;

[0125] It should be noted that the cooperative observer is a state estimation tool designed based on the system model, which is used to estimate the state variables that are difficult to directly measure in the system in real time, such as load torque, rotor mechanical angular velocity, etc. The cooperative observer dynamically adjusts the estimated value to be as close as possible to the actual state by combining the physical model of the motor and the real-time measurement data. In the control of permanent magnet synchronous motors, a typical use of the cooperative observer is to estimate the load disturbance, so as to provide accurate disturbance compensation information for the controller and enhance the system performance.

[0126] In addition, the speed closed-loop control signal value is a feedback control signal calculated by the integrated speed controller according to the real-time error, which is used to adjust the input of the motor to reach the target speed. The characteristic of closed-loop control is to correct the control output by monitoring the state of the system (such as speed) in real time to ensure the stable and accurate operation of the system. Exemplarily, when the actual speed of the motor is lower than the target speed, the closed-loop control signal will increase the input power to increase the speed until the target value is reached.

[0127] It can be understood that by combining the functions of the integrated speed controller and the cooperative observer, the speed closed-loop control signal value is calculated. The cooperative observer estimates the state variables such as load torque in real time and provides more accurate input data for the integrated speed controller; the integrated speed controller then dynamically adjusts the control output according to the real-time error and the observed data to ensure the stability and accuracy of the speed closed-loop. Exemplarily, when the cooperative observer detects an increase in the load torque, the integrated speed controller will increase the control signal according to the speed error and the estimated value to compensate for the influence of the load change.

[0128] Step S43: Calculate the target control signal value based on the current feedforward compensation signal value and the speed closed-loop control signal value, and complete the speed control of the permanent magnet synchronous motor according to the target control signal value.

[0129] It can be understood that the feedforward compensation signal value and the speed closed-loop control signal value are combined to calculate the target control signal value. The target control signal value is the final decision on the actual input to the motor, integrating the fast response ability of feedforward compensation and the precise adjustment ability of closed-loop control. When calculating the target control signal value, it is necessary to balance the roles of feedforward and feedback. For example, when the load disturbance is large, the feedforward compensation signal may play a major part, while in steady-state operation, the closed-loop control signal may play a dominant role. After the calculation is completed, the target control signal is used to adjust the input of the permanent magnet synchronous motor, such as adjusting the drive current or voltage of the motor, so as to achieve precise control of the motor speed.

[0130] Refer to Figure 2 , Figure 2 which is the control block diagram of the permanent magnet synchronous motor for the first embodiment of the speed control method of the permanent magnet synchronous motor in this application.

[0131] As Figure 2 shown, the permanent magnet synchronous motor control system includes parts such as a speed loop, a current loop, an inverter, and sensors, and describes the complete control process from the input of the rotor mechanical angular velocity reference value to the operation of the motor. In the speed loop, the rotor mechanical angular velocity reference value is input to the speed controller, and through a sliding mode control, PI control, composite nonlinear feedback control, or a combination strategy thereof, the reference value of the q-axis current is generated; in addition, the cooperative load torque observation module estimates the load disturbance in real time, generates a load torque compensation signal, and calculates the actual q-axis current control signal together with the q-axis current reference value. This signal is further adjusted by the PI controller in the current loop to obtain the reference voltage values of the d-axis and q-axis, which are converted into the reference voltage signal of the coordinate system after the inverse Park transformation. Subsequently, the SVPWM module generates the switching control signal of the inverter, and converts the input DC voltage into the three-phase AC voltage for driving the motor through the inverter. Through the sensors, the three-phase current of the motor is fed back to the system, converted into the current signal of the coordinate system through the Clark transformation, and then the d-axis and q-axis current feedback signals are generated through the Park transformation for the closed-loop control of the current loop. The sensors are also used to measure the angular velocity and position of the rotor, and are fed back to the speed controller and the Park transformation module to complete the dynamic adjustment of the entire closed-loop control system. Finally, through the coordinated action of the speed loop and the current loop, the control system realizes precise adjustment of the motor speed and current, ensuring the stable and efficient operation of the permanent magnet synchronous motor under various working conditions.

[0132] This embodiment provides a speed control method for a permanent magnet synchronous motor. By combining a composite nonlinear feedback strategy and a sliding mode control strategy to construct an integrated speed controller, and combining a cooperative observer for real-time estimation and compensation of load torque and speed error, and through the cooperative control technology of feedforward compensation and closed-loop feedback, fast response, precise control and high robustness of the permanent magnet synchronous motor under load disturbance and parameter uncertainty are achieved, solving the problems of low control accuracy, poor dynamic performance and insufficient anti-interference ability caused by disturbance and nonlinear characteristics in traditional control methods, and achieving the beneficial effects of improving control accuracy, enhancing system stability and dynamic performance.

[0133] Based on the first embodiment of the present application, in the second embodiment of the present application, the same or similar content as the above-mentioned embodiment one can be referred to the above introduction and will not be repeated hereinafter. On this basis, please refer to Figure 3 , step S20 of the speed control method of the permanent magnet synchronous motor further includes steps S21 to S23:

[0134] Step S21, obtaining the rotor mechanical angular velocity tracking error and the load torque observation error;

[0135] It should be noted that the rotor mechanical angular velocity tracking error refers to the difference between the target angular velocity of the motor and the current actual angular velocity, which is used to characterize the accuracy of the motor speed control. This error reflects the degree to which the motor deviates from the target state during operation and is one of the important input variables for speed control.

[0136] In addition, the load torque observation error refers to the deviation between the load torque estimated by the cooperative observer and the actual load torque. Since the load torque is usually difficult to measure directly, the cooperative observer obtains the value of the load torque through dynamic estimation, and the observation error is used to evaluate the accuracy of the estimation.

[0137] Step S22, calculating an error vector according to the rotor mechanical angular velocity tracking error and the load torque observation error;

[0138] It should be noted that the error vector is a mathematical expression formed by combining multiple error variables, the rotor mechanical angular velocity tracking error and the load torque observation error, which is used to characterize the overall degree to which the current state of the system deviates from the target state. The error vector is an important input for the design of the cooperative observer and system control. The error vector is called a manifold in the cooperative observer. A manifold is a mathematical tool used to describe the relationship between error variables in a multi-dimensional space. The error vector, as a manifold, represents the global state of the system error, including the coupling characteristics of the speed error and the load error. Through the manifold, the cooperative observer can understand and process the distribution and dynamic change trend of these errors in space. The calculation of the error vector is as follows:

[0139]

[0140] In the error vector calculation formula, ψ represents the error between the estimated values and the actual values of the speed and the load torque. represents the observed error of the rotor mechanical angular velocity; represents the observed error of the load torque.

[0141] Step S23: Construct a cooperative observer according to the error vector, the cooperative observer strategy, and the rotor mechanical angular velocity state equation.

[0142] It can be understood that, by synthesizing the error vector, the cooperative observer strategy, and the rotor mechanical angular velocity state equation, a cooperative observer is designed. Through the feedback of the error vector, the gain parameters of the observer are adjusted in real time to improve the observation accuracy. According to the dynamically changing error characteristics, the adjustment rules of the observer are designed. For example, when the error is large, the estimation strength of the state variables is enhanced. Using the rotor mechanical angular velocity state equation, a mathematical model of the observer is established so that it can reflect the actual dynamic behavior of the system. When the load suddenly changes, the cooperative observer will detect the change trend through the error vector and adjust the parameters of the observer in real time to quickly correct the estimated value of the load torque.

[0143] In a feasible implementation manner, step S23 may include steps S231 to S235:

[0144] Step S231: Obtain the cooperative observer gain parameters and the cooperative observer control parameters according to the cooperative observer strategy.

[0145] It should be noted that the cooperative observer gain parameter is a parameter in the observer used to adjust the sensitivity and response speed of the observer to errors. The gain parameter directly affects the estimation accuracy of the unmeasurable state variables, such as the load torque, the rotor mechanical angular velocity, etc. The setting of the gain parameter is usually based on the dynamic characteristics and error range of the system. For example, when the error is large, a higher gain parameter can be set to accelerate the estimation convergence speed; when the error is small, the gain parameter can be reduced to reduce the estimation fluctuation.

[0146] In addition, the cooperative observer control parameter is a parameter used to adjust the rate at which the system converges to the manifold. Different from the gain parameter, the cooperative observer control parameter pays more attention to the dynamic characteristics of convergence, indicating the speed of convergence to the manifold. The value of the control parameter directly affects the speed at which the system error converges to the manifold. A smaller cooperative observer control parameter can reach the target manifold faster; a larger cooperative observer control parameter can make the convergence process smoother.

[0147] It can be understood that by analyzing the dynamic characteristics, error range, and real-time requirements of the system, the gain parameters of the observer and the control parameters of the cooperative observer are determined according to the cooperative observer strategy. The rate of change of the system error and the requirement for estimation accuracy need to be comprehensively considered. For example, when the system error changes rapidly, the gain parameter should be appropriately increased to accelerate the estimation speed of the state variables; when the system is stable, the gain parameter can be decreased to reduce the risk of oscillation. At the same time, according to the control objective of the system, the control parameters need to be adjusted to optimize the convergence performance. When the error changes violently or the system deviation is large, smaller control parameters are selected to accelerate the convergence speed of the error to the target manifold; when the error tends to be stable or small, larger control parameters are selected to improve the system stability.

[0148] Step S232: According to the state equation of the rotor mechanical angular velocity, obtain the motor damping coefficient, the moment of inertia of the motor rotor, the actual value of the rotor mechanical angular velocity, the number of pole pairs of the motor, and the permanent magnet flux linkage of the motor.

[0149] It should be noted that the motor damping coefficient is a parameter that describes the energy loss characteristics in the motor mechanical system. It represents the degree of energy loss in the motor during rotation due to factors such as mechanical resistance and friction. A larger damping coefficient will slow down the dynamic response of the system but make it more stable; while a smaller damping coefficient makes the system more sensitive but may be prone to overshoot.

[0150] In addition, the moment of inertia of the motor rotor is a physical quantity that describes the ability of the motor rotor to resist rotational changes, representing the inertia generated by the mass distribution of the rotor during rotation. The larger the moment of inertia, the slower the speed change of the motor, but the stronger the adaptability to load disturbances. The actual value of the rotor mechanical angular velocity refers to the real-time angular velocity of the motor rotor measured by a sensor. This is an important parameter for the current operating state of the system, used to evaluate the dynamic performance and error of the system.

[0151] In addition, it should be noted that the number of pole pairs of the motor is a parameter that describes the magnetic field structure of the motor, representing the number of magnetic pole pairs in the motor rotor. The number of pole pairs has a direct impact on the operating characteristics of the motor, such as the relationship between speed and frequency, and is an important parameter in motor design. The permanent magnet flux linkage of the motor is a quantitative description of the magnetic field strength generated by the permanent magnets in the motor rotor. It reflects the electromagnetic performance of the motor and has an important impact on the torque output and dynamic response of the motor.

[0152] It can be understood that the fixed parameters and real-time state variables of the motor operation are obtained through the state equation of the rotor mechanical angular velocity. Obtaining these parameters can provide an accurate physical basis for the cooperative observer and ensure the high reliability of the observer's estimation.

[0153] Step S233: Calculate the estimated value of the load torque according to the cooperative observer gain parameter, the cooperative observer control parameter, and the error vector;

[0154] It should be noted that the estimated value of the load torque is the estimated value of the motor load torque obtained by the cooperative observer through real-time calculation and dynamic adjustment. It is a key variable in motor control and is used to compensate for the influence of load disturbances.

[0155] It can be understood that the estimated value of the load torque is dynamically calculated according to the cooperative observer gain parameter, the cooperative observer control parameter, and the error vector. The cooperative observer gain parameter determines the response intensity of the observer to the error vector. Through the feedback adjustment of the error vector, the cooperative observer can capture the degree of deviation of the current state of the system. At the same time, the rate of convergence to the manifold is adjusted through the cooperative observer control parameter. Combining these parameters and the error vector, the cooperative observer estimates the load torque in real time through an internal dynamic calculation formula, and can accurately calculate the estimated value of the current system load torque, providing an accurate input for the subsequent controller to ensure that the system can effectively compensate for load disturbances and optimize the motor performance.

[0156] Step S234: Calculate the estimated value of the rotor mechanical angular velocity according to the cooperative observer gain parameter, the cooperative observer control parameter, the motor damping coefficient, the motor rotor inertia, the actual value of the rotor mechanical angular velocity, the number of pole pairs of the motor, and the permanent magnet flux linkage of the motor;

[0157] It should be noted that the estimated value of the rotor mechanical angular velocity is the estimated value of the rotor angular velocity obtained by the cooperative observer through the system model and real-time error calculation. It provides an alternative input for the controller when the actual value cannot be directly measured or there is a measurement delay.

[0158] It can be understood that by integrating the fixed parameters of the system and the dynamic error information, the cooperative observer is used to calculate the estimated value of the rotor mechanical angular velocity. The estimated value of the rotor mechanical angular velocity can provide a reliable input for the controller when the sensor is unavailable or delayed, ensuring the continuity of the system operation.

[0159] Step S235: Construct a cooperative observer according to the estimated value of the load torque and the estimated value of the rotor mechanical angular velocity.

[0160] It can be understood that the estimated value of the load torque and the estimated value of the rotor mechanical angular velocity are integrated as the output of the cooperative observer, and at the same time, the gain parameter and the cooperative observer control parameter of the observer are adjusted by combining the error feedback. The cooperative observer is as follows:

[0161]

[0162] In the formula of the cooperative observer, denotes the estimated value of the mechanical angular velocity of the rotor; denotes the estimated value of the load torque; B m denotes the damping coefficient of the motor; J m denotes the moment of inertia of the motor rotor; ω m denotes the actual value of the mechanical angular velocity of the rotor; p n denotes the number of pole pairs of the motor; ψ f denotes the permanent magnet flux linkage of the motor; m1 and m2 denote the gain parameters of the cooperative observer; T denotes the control parameter used to adjust the rate at which the system converges to the manifold. By selecting appropriate gain coefficients m1 < 0, m2 > 0, and T > 0, the cooperative observer can ensure that the system observation error converges to 0 within a finite time.

[0163] Additionally, the cooperative observer provides accurate state information inputs for the system, such as load disturbances and speed states, by dynamically adjusting and optimizing the estimation process, thereby optimizing the control strategy.

[0164] Referring to Figure 4 , Figure 4 is the block diagram of the cooperative observer for the second embodiment of the speed control method of the permanent magnet synchronous motor in this application.

[0165] As Figure 4 shown, for estimating the load torque and the mechanical angular velocity of the permanent magnet synchronous motor, the input signals include i q (q-axis current component of the permanent magnet synchronous motor) and ω m (actual value of the mechanical angular velocity of the rotor). Input i q from the left side, and this module calculates the input signal generated by the q-axis current according to the permanent magnet flux linkage ψ f , the number of pole pairs p n of the motor, and the moment of inertia J m of the rotor. This input signal is subtracted from the estimated value of the load torque m distributed by the proportional module 1 / J to obtain the acceleration signal. The acceleration signal is converted into the estimated mechanical angular velocity by the integration module and simultaneously superimposed with the damping effect B m / J m and then fed back to the system input. In the other path on the right side, the cooperative observer adjusts and through the cooperative observer control parameter combined with error calculation. The error is provided by the difference between the actual rotational speed ω m input and the estimated rotational speed . The feedback path further corrects the estimated values of the load torque and rotational speed, thus completing the dynamic estimation closed-loop of the entire observer.

[0166] In addition, it can be understood that different combinations of control schemes with controllers and load observers can be established, and the combined schemes can be tested and verified. Each row in Table 1 represents a different combination of control strategies, such as PI control, sliding mode control (SMC), composite nonlinear feedback control (CNF), and their cooperation with load observers (such as sliding mode observer SMO and cooperative observer SO). The table aims to compare the effects of these different schemes in practical applications, and verify whether the scheme of this embodiment has better speed tracking performance by comparing their performance.

[0167] Table 1

[0168]

[0169] In addition, based on Table 1, the initial speed of the PMSM is set to 0 rpm, the reference speed is 1000 rpm, and the simulation time is 4 s. The PMSM starts with no load and runs with a variable load after 1 s and a constant load after 3 s. In addition, in this embodiment, the allowable steady-state tracking error range is ±5%.

[0170] It can be understood that Schemes 1-5 in Table 1 are used to verify the high transient performance of the proposed CNFSMC method. The control results of PI control, SMC, CNF, SMC+CNF, and CNFSMC methods are compared.

[0171] Referring to FIGS. 5(a), 5(b), 5(c) and 5(d), FIGS. 5(a), 5(b), 5(c) and 5(d) are the speed responses of the speed tracking responses of different speed controllers. Among them, FIGS. 5(a), 5(b), 5(c) and 5(d) are respectively the schematic diagram of the speed response in the no-load area of the speed controller, the schematic diagram of the speed response in the variable load area of the speed controller, the schematic diagram of the overshoot speed and overshoot speed response of the speed controller, and the schematic diagram of the speed response of the steady-state response time of the speed controller, respectively representing the tracking responses of different PMSM speed controllers. Compared with PI control, SMC and SMC+CNF, the proposed CNFSMC achieves low speed overshoot and short settling time, as shown in FIG. 5(a). The proposed CNFSMC has excellent transient tracking performance, similar to CNF. In FIGS. 5(a) and 5(b), the change of the load torque not only significantly increases the speed fluctuation and settling time of CNF, but also causes a decrease in the steady-state response speed in subsequent tracking. The load disturbance rejection performance of CNF is significantly poor. In addition, although the PI speed response remains within an acceptable error range when the load torque changes, there are still large speed fluctuations. During the change of the load torque, the steady-state speed fluctuations of CNFSMC, SMC+CNF and SMC are all kept within ±0.5% of the reference speed, having excellent anti-interference performance. This shows that the strong robustness of SMC is well reflected in CNFSMC and SMC+CNF. In addition, the proposed CNFSMC always keeps the steady-state tracking error within the range of ±0.5%, having higher tracking accuracy compared with other controllers. The quantitative results of FIG. 5(a) are shown in FIGS. 5(c) and 5(d). It can be seen from FIG. 5(c) that the overshoots of CNF, CNFSMC, SMC+CNF, SMC and PI control increase in turn. The overshoot speed of the proposed CNFSMC is small, being 4.84 rpm, which is reduced by 99.25, 150.58 and 327.99 rpm compared with SMC+CNF, SMC and PI control respectively, and is close to 4.21 rpm of CNF. Compared with SMC+CNF, SMC and PI control, its overshoot (0.48%) is reduced by about 95.39%, 96.91% and 98.56% respectively, and is close to the overshoot (0.42%) of CNF control. It can be seen from FIG. 5(d) that compared with other controllers, the steady-state response time of the proposed CNFSMC in this paper is 0.02 s, which is 0.02, 0.05, 0.06 and 0.11 s shorter than that of CNF, SMC+CNF, SMC and PI control respectively. The quantitative results of overshoot and settling time show that the advantages of CNF are well utilized in CNFSMC.

[0172] Based on the above qualitative and quantitative results, the proposed CNFSMC combines the excellent transient response of CNF with the strong robustness of SMC to load disturbances, achieving the integration of multiple performances and improving the accuracy of PMSM speed control.

[0173] In addition, it can be understood that to verify the robustness of CNFSMC under motor parameter variations, according to Scenarios 1 - 5 in Table 1, the stator resistance and inductance are set to 2Rs and 0.95Ls respectively. Referring to Fig. 6(a), Fig. 6(b), Fig. 6(c), and Fig. 6(d), which are the speed tracking responses of different speed controllers. Among them, Fig. 6(a), Fig. 6(b), Fig. 6(c), and Fig. 6(d) are the schematic diagrams of the speed responses in the no-load region with different parameters, the speed responses in the variable-load region with different parameters, the overshoot speed and overshoot speed responses with different parameters, and the schematic diagrams of the speed responses of the steady-state response time with different parameters respectively, showing the tracking responses of different controllers under PMSM parameter variations.

[0174] As shown in Fig. 6, the trend of the tracking performance of different controllers under parameter variations is consistent with Fig. 5. In addition, Fig. 6(a) and Fig. 6(b) also show the irregular chattering of the speed tracking curve when the load changes. This is due to the mismatch of control parameters caused by the combined effect of parameter variations and load changes, reducing the stability of speed tracking. Despite these obvious jitters, CNFSMC still maintains its robustness with a steady-state error of ±0.5%.

[0175] Table 2 presents the comparison of the transient responses of different speed controllers before and after the change of PMSM parameters.

[0176] Table 2

[0177]

[0178] As can be seen from Fig. 6(c), Fig. 6(d) and Table 2, compared with the rated operating conditions, the change of motor parameters will lead to the change of speed overshoot. Although compared with other methods, the proposed CNFSMC has the largest percentage change in speed overshoot before and after parameter change, which is 22.92%, its overshoot is still smaller than that of PI control, SMC and SMC+CNF, and is closer to CNF. Among all methods, the steady-state response time of CNFSMC is also the shortest, only 0.02 s. These results indicate that even in the case of parameter change, the proposed CNFSMC can exhibit excellent transient performance. In addition, from Table 2, it can be observed that the performance similarity of SMC, SMC+CNF and CNF can be reflected from the percentage change difference. The percentage change of SMC+CNF (1.92%) is between 0.45% of SMC and 4.76% of CNF. The absolute difference in percentage change between SMC+CNF and SMC is 1.47%, which is less than the difference of 2.84% between SMC+CNF and CNF. This shows that the transient performance of SMC+CNF is closer to SMC, which is consistent with the results in Fig. 6(a).

[0179] In addition, it can be understood that Scheme 6-7 in Table 1 is used to verify the observation performance of the proposed SO method. SMO is compared with SO. The estimation performance of the load observer can be evaluated by the normalized root mean square error (NRMSE), and the formula for the normalized root mean square error is as follows:

[0180]

[0181] In the formula, RMSE represents the root mean square error; S actual represents the measured signal; represents the estimated signal; N represents the number of collected samples.

[0182] In addition, it can be understood that referring to Fig. 7(a) and Fig. 7(b), Fig. 7(a) and Fig. 7(b) are the load torque estimations based on different observers. Among them, Fig. 7(a) and Fig. 7(b) are the schematic diagrams of SMO load torque estimation and SO load torque estimation respectively, and Fig. 7(a) and Fig. 7(b) show the load torque estimations based on different observers.

[0183] Table 3 lists the comparison data of the estimation accuracy of the load observer.

[0184] Table 3

[0185] Load observer Maximum absolute measurement value (N·m) RMSE (N·m) NRMSE (%) SMO 160.000 2.20 1.38 Proposed SO 160.000 2.11 1.32

[0186] As can be seen from Figs. 7(a) and 7(b), the proposed SO and SMO can both successfully estimate the load torque in real time. Meanwhile, there is almost no chattering in SO. This shows that the proposed SO suppresses chattering better than SMO and improves the stability of the observation system. As can be seen from Table 3, the RMSE and NRMSE of the proposed SO are 2.11 N·m and 1.32% respectively. These evaluation index values are lower than those of SMO, indicating that the proposed SO has excellent estimation performance.

[0187] In addition, it can be understood that Schemes 5 to 7 are adopted to analyze the influence of load disturbance compensation on the speed tracking performance. The experimental results of CNFSMC, CNFSMC+SMO and CNFSMC+SO are compared and analyzed.

[0188] Referring to Figs. 8(a) and 8(b), Figs. 8(a) and 8(b) are the speed responses after load disturbance compensation. Among them, Figs. 8(a) and 8(b) are the schematic diagram of the speed response in the load change area and the detailed schematic diagram of Fig. 8(a) respectively, and Figs. 8(a) and 8(b) show the speed responses after load disturbance compensation. As shown in Figs. 8(a) and 8(b), the load disturbance compensation significantly improves the speed tracking accuracy. The steady-state speed tracking error of CNFSMC after load disturbance compensation during the load change process is ±0.15%, which is 70% higher than the accuracy of CNFSMC without load disturbance compensation. In addition, the output chattering of CNFSMO+SO is less than the output flutter of CNFSMC+SMO, indicating that SO suppresses chattering better than SMO.

[0189] In addition, it can be understood that referring to Figs. 9(a) and 9(b), Figs. 9(a) and 9(b) are the PMSM current responses under load disturbance compensation. Among them, Figs. 9(a) and 9(b) are the schematic diagram of the q-axis current iq current response and the schematic diagram of the a-phase current ia current response respectively, and Figs. 9(a) and 9(b) show the PMSM current responses under load disturbance compensation. The q-axis current of the CNFSMC+SO scheme is shown in Fig. 9(a). Reference current Output current sat(i q ) and compensation current △i q are composed. As can be seen from the figure, the current is consistent with the load change trend. Fig. 9(b) shows the total harmonic distortion (THD) value of the a-phase current starting from 2.5 s, with a fundamental frequency of 50 Hz and a period of one cycle. The THD of CNFSMC+SO is 40.61%, which is lower than that of CNFSMC (51.75%) and CNFSMC+SMO (40.86%). Compared with other methods, the proposed CNFSMC+SO in this embodiment has better current harmonic suppression ability.

[0190] This embodiment provides a speed control method for a permanent magnet synchronous motor. By introducing a technical means that combines a cooperative observer strategy with an integrated speed controller, and using the dynamic feedback of the error vector and the design of a non-linear sliding mode surface, it solves the technical problems of the permanent magnet synchronous motor, such as the decline in control accuracy and the sluggish dynamic response caused by load disturbances and parameter uncertainties under complex working conditions. It achieves the beneficial effects of improving the dynamic response speed of the system, enhancing the control accuracy and robustness, and effectively suppressing the influence of load disturbances on speed control, thereby realizing the precise adjustment and efficient control of the motor operating state.

[0191] Exemplarily, to facilitate understanding of the implementation process of the speed control method for the permanent magnet synchronous motor obtained by combining this embodiment with the above-mentioned Embodiment 1, please refer to Figure 10 , Figure 10 A brief flow schematic diagram of a speed control method for a permanent magnet synchronous motor is provided. Specifically:

[0192] Closed-loop control from the input reference value of the rotor mechanical angular velocity to the motor operation is achieved through a speed controller module, a load disturbance observer module, and a permanent magnet synchronous motor vector control system. First, in the speed controller module, the reference value of the rotor mechanical angular velocity and the actual value of the rotor mechanical angular velocity are input. Through the calculation formula of the rotor mechanical angular velocity tracking error, the rotor mechanical angular velocity tracking error is calculated as the basis for control. Subsequently, the rotor mechanical angular velocity tracking error is input into the non-linear sliding mode surface equation, and a sliding mode surface is constructed through a composite non-linear feedback strategy to adjust the control performance of the system. Finally, a control signal is generated through the integrated speed controller, and a saturation control signal for adjusting the motor speed is calculated. The speed tracking control formula with load disturbance compensation uses the saturation control signal output by the integrated speed controller and the feedforward adjustment amount of load disturbance compensation to calculate the actual control signal, which ensures the tracking accuracy of the motor speed and the compensation for load disturbances. As the core execution module, the permanent magnet synchronous motor vector control system drives the motor and generates a dynamic response after receiving the control signal, the actual value of the rotor mechanical angular velocity, and the load torque. The actual value of the rotor mechanical angular velocity, the control signal, and the load torque output by the motor are returned to the speed controller and the load disturbance observer module through the feedback path. In the load disturbance observer module, the error vector calculation formula calculates the error vector based on the actual value of the rotor mechanical angular velocity and the load torque. The cooperative observer combines the error vector to dynamically estimate the estimated value of the load torque and the estimated value of the rotor mechanical angular velocity, and at the same time calculates the load torque compensation amount through the feedforward compensation gain value to correct the control signal, thereby reducing the influence of load disturbances on the system. Through the comprehensive action of the feedback closed-loop and feedforward compensation, the whole system realizes the precise tracking of the target reference value of the rotor mechanical angular velocity, effectively suppresses load disturbances, and improves the dynamic performance and control accuracy of the permanent magnet synchronous motor.

[0193] It should be noted that the above examples are only for understanding the present application and do not constitute a limitation on the speed control method of the permanent magnet synchronous motor of the present application. Based on this technical concept, more forms of simple transformations are within the protection scope of the present application.

[0194] The present application also provides a speed control device for a permanent magnet synchronous motor. Please refer to Figure 11 , the speed control device of the permanent magnet synchronous motor includes:

[0195] A controller construction module 10, configured to construct an integrated speed controller according to a composite nonlinear feedback strategy and a sliding mode control strategy;

[0196] An observer construction module 20, configured to construct a cooperative observer according to a cooperative observer strategy;

[0197] A gain value calculation module 30, configured to obtain an estimated load of the permanent magnet synchronous motor and calculate a current feedforward compensation according to the estimated load to obtain a feedforward compensation gain value;

[0198] A speed control module 40, configured to calculate a control signal value according to the feedforward compensation gain value, the integrated speed controller, and the cooperative observer, and complete the speed control of the permanent magnet synchronous motor according to the control signal value.

[0199] The speed control device of the permanent magnet synchronous motor provided by the present application adopts the speed control method of the permanent magnet synchronous motor in the above embodiment, and can solve the technical problem of how to improve the speed control accuracy and stability of the permanent magnet synchronous motor in the face of parameter uncertainty and load disturbance. Compared with the prior art, the beneficial effects of the speed control device of the permanent magnet synchronous motor provided by the present application are the same as those of the speed control method of the permanent magnet synchronous motor provided by the above embodiment, and other technical features in the speed control device of the permanent magnet synchronous motor are the same as the features disclosed in the method of the above embodiment, and will not be elaborated here.

[0200] In an embodiment, the controller construction module 10 is further configured to obtain a rotor mechanical angular velocity tracking error and a change rate of the rotor mechanical angular velocity tracking error according to the permanent magnet synchronous motor speed state equation; construct a nonlinear sliding mode surface equation according to the composite nonlinear feedback strategy, the permanent magnet synchronous motor speed state equation, the rotor mechanical angular velocity tracking error, and the change rate of the rotor mechanical angular velocity tracking error; construct an adaptive exponential reaching law equation according to the sliding mode control strategy, the nonlinear sliding mode surface equation, the rotor mechanical angular velocity tracking error, and the change rate of the rotor mechanical angular velocity tracking error; and construct an integrated speed controller according to the permanent magnet synchronous motor speed state equation, the nonlinear sliding mode surface equation, and the adaptive exponential reaching law equation.

[0201] In one embodiment, the controller construction module 10 is further configured to obtain a constant matrix; obtain a reference value of the rotor mechanical angular velocity and a current value of the rotor mechanical angular velocity according to the permanent magnet synchronous motor speed state equation; obtain a composite nonlinear feedback gain parameter, a nonlinear correction function, and a state feedback gain matrix according to the composite nonlinear feedback strategy; and construct a nonlinear sliding mode surface equation according to the constant matrix, the rotor mechanical angular velocity tracking error, the reference value of the rotor mechanical angular velocity, the current value of the rotor mechanical angular velocity, the change rate of the rotor mechanical angular velocity tracking error, the composite nonlinear feedback gain parameter, the nonlinear correction function, and the state feedback gain matrix.

[0202] In one embodiment, the controller construction module 10 is further configured to obtain a sliding mode exponential reaching law strategy according to the sliding mode control strategy; obtain a switching function, a switching gain factor, and an exponential factor according to the sliding mode exponential reaching law strategy; calculate an error state quantity according to the rotor mechanical angular velocity tracking error and the change rate of the rotor mechanical angular velocity tracking error; and construct an adaptive exponential reaching law equation according to the nonlinear sliding mode surface equation, the switching function, the switching gain factor, the exponential factor, and the error state quantity.

[0203] In one embodiment, the speed control module 40 is further configured to obtain a rotor mechanical angular velocity tracking error and a load torque observation error; calculate an error vector according to the rotor mechanical angular velocity tracking error and the load torque observation error; and construct a cooperative observer according to the error vector, the cooperative observer strategy, and the rotor mechanical angular velocity state equation.

[0204] In one embodiment, the observer construction module 20 is further configured to obtain a cooperative observer gain parameter and a cooperative observer control parameter according to the cooperative observer strategy;

[0205] obtain a motor damping coefficient, a motor rotor moment of inertia, an actual value of the rotor mechanical angular velocity, a number of motor pole pairs, and a motor permanent magnet flux linkage according to the rotor mechanical angular velocity state equation; calculate an estimated value of the load torque according to the cooperative observer gain parameter, the cooperative observer control parameter, and the error vector; calculate an estimated value of the rotor mechanical angular velocity according to the cooperative observer gain parameter, the cooperative observer control parameter, the motor damping coefficient, the motor rotor moment of inertia, the actual value of the rotor mechanical angular velocity, the number of motor pole pairs, and the motor permanent magnet flux linkage; and construct a cooperative observer according to the estimated value of the load torque and the estimated value of the rotor mechanical angular velocity.

[0206] In one embodiment, the speed control module 40 is further configured to obtain a current feedforward compensation signal value according to the feedforward compensation gain value; calculate a speed closed-loop control signal value according to the integrated speed controller and the cooperative observer; calculate a target control signal value according to the current feedforward compensation signal value and the speed closed-loop control signal value, and complete the speed control of the permanent magnet synchronous motor according to the target control signal value.

[0207] The present application provides a speed control device for a permanent magnet synchronous motor. The speed control device for a permanent magnet synchronous motor includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the speed control method of the permanent magnet synchronous motor in the first embodiment above.

[0208] Reference is made below to Figure 12 , which shows a schematic structural diagram of a speed control device for a permanent magnet synchronous motor suitable for implementing the embodiments of the present application. The speed control device for a permanent magnet synchronous motor in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 12 The speed control device for a permanent magnet synchronous motor shown is only an example and should not impose any limitation on the functions and usage scope of the embodiments of the present application.

[0209] As Figure 12As shown, the speed control device of the permanent magnet synchronous motor may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. In the RAM 1004, various programs and data required for the operation of the speed control device of the permanent magnet synchronous motor are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems may be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the speed control device of the permanent magnet synchronous motor to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows the speed control device of the permanent magnet synchronous motor having various systems, it should be understood that it is not required to implement or have all the shown systems. More or fewer systems may be implemented or had alternatively.

[0210] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for performing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network through the communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of the embodiments disclosed in the present application are executed.

[0211] The speed control device of the permanent magnet synchronous motor provided by the present application adopts the speed control method of the permanent magnet synchronous motor in the above embodiment, and can solve the technical problem of how to improve the speed control accuracy and stability of the permanent magnet synchronous motor in the face of parameter uncertainty and load disturbance. Compared with the prior art, the beneficial effects of the speed control device of the permanent magnet synchronous motor provided by the present application are the same as those of the speed control method of the permanent magnet synchronous motor provided by the above embodiment, and other technical features in the speed control device of the permanent magnet synchronous motor are the same as the features disclosed in the method of the previous embodiment, and will not be elaborated here.

[0212] It should be understood that each part disclosed in this application can be implemented by hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0213] As described above, the above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0214] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the speed control method of the permanent magnet synchronous motor in the above embodiments.

[0215] The computer-readable storage medium provided by this application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or flash memory, optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or combined with an instruction execution system, device, or device. The program code contained on the computer-readable storage medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0216] The above computer-readable storage medium can be included in the speed control device of the permanent magnet synchronous motor; it can also exist separately and not be assembled into the speed control device of the permanent magnet synchronous motor.

[0217] The above computer-readable storage medium carries one or more programs, which, when executed by a speed control device of a permanent magnet synchronous motor, cause the speed control device of the permanent magnet synchronous motor to: construct an integrated speed controller according to a composite non-linear feedback strategy and a sliding mode control strategy; construct a cooperative observer according to a cooperative observer strategy; obtain an estimated load of the permanent magnet synchronous motor, and calculate a current feed-forward compensation according to the estimated load to obtain a feed-forward compensation gain value; calculate a control signal value according to the feed-forward compensation gain value, the integrated speed controller, and the cooperative observer, and complete the speed control of the permanent magnet synchronous motor according to the control signal value.

[0218] Computer program code for performing the operations of this application may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., by connecting through an Internet service provider using the Internet).

[0219] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0220] The modules involved in the embodiments of the present application can be implemented in software or in hardware. In some cases, the name of the module does not constitute a limitation on the unit itself.

[0221] The readable storage medium provided by the present application is a computer-readable storage medium. The computer-readable storage medium stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned speed control method of the permanent magnet synchronous motor, and can solve the technical problem of how to improve the speed control accuracy and stability of the permanent magnet synchronous motor in the face of parameter uncertainty and load disturbance. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as those of the speed control method of the permanent magnet synchronous motor provided by the above embodiments, and will not be elaborated here.

[0222] The present application also provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps of the speed control method of the permanent magnet synchronous motor as described above are implemented.

[0223] The computer program product provided by the present application can solve the technical problem of how to improve the speed control accuracy and stability of the permanent magnet synchronous motor in the face of parameter uncertainty and load disturbance. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as those of the speed control method of the permanent magnet synchronous motor provided by the above embodiments, and will not be elaborated here.

[0224] The above are only some embodiments of the present application, and thus do not limit the patent scope of the present application. Any equivalent structural transformation made by using the content of the specification and drawings of the present application under the technical concept of the present application, or direct / indirect application in other related technical fields, is included in the patent protection scope of the present application.

Claims

1. A speed control method for a permanent magnet synchronous motor, characterized in that: The method comprises: An integrated speed controller is constructed based on the composite nonlinear feedback strategy and sliding mode control strategy; According to the collaborative observer strategy, a collaborative observer is constructed; Obtaining an estimated load of the permanent magnet synchronous motor, and calculating a current feedforward compensation according to the estimated load to obtain a feedforward compensation gain value; A control signal value is calculated according to the feedforward compensation gain value, the integrated speed controller and the collaborative observer, and speed control of the permanent magnet synchronous motor is completed according to the control signal value.

2. The method according to claim 1, characterized in that The step of constructing an integrated speed controller according to the composite nonlinear feedback strategy and the sliding mode control strategy comprises: According to the permanent magnet synchronous motor speed state equation, the rotor mechanical angular velocity tracking error and the rotor mechanical angular velocity tracking error change rate are obtained; Constructing a nonlinear sliding surface equation according to a composite nonlinear feedback strategy, the permanent magnet synchronous motor speed state equation, the rotor mechanical angular velocity tracking error, and the rotor mechanical angular velocity tracking error change rate; Constructing an adaptive exponential reaching law equation according to a sliding mode control strategy, the nonlinear sliding mode surface equation, the rotor mechanical angular velocity tracking error, and the rotor mechanical angular velocity tracking error change rate; An integrated speed controller is constructed according to the permanent magnet synchronous motor speed state equation, the nonlinear sliding surface equation and the adaptive exponential reaching law equation.

3. The method according to claim 2, characterized in that The step of constructing a nonlinear sliding surface equation according to the composite nonlinear feedback strategy, the permanent magnet synchronous motor speed state equation, the rotor mechanical angular velocity tracking error, and the rotor mechanical angular velocity tracking error change rate comprises: Get the constant matrix; According to the permanent magnet synchronous motor speed state equation, a rotor mechanical angular velocity reference value and a rotor mechanical angular velocity current value are obtained; According to the composite nonlinear feedback strategy, composite nonlinear feedback gain parameters, nonlinear correction function and state feedback gain matrix are obtained; A nonlinear sliding surface equation is constructed according to the constant matrix, the rotor mechanical angular velocity tracking error, the rotor mechanical angular velocity reference value, the rotor mechanical angular velocity current value, the rotor mechanical angular velocity tracking error change rate, the composite nonlinear feedback gain parameter, the nonlinear correction function and the state feedback gain matrix.

4. The method according to claim 2, characterized in that The step of constructing an adaptive exponential reaching law equation according to the sliding mode control strategy, the nonlinear sliding mode surface equation, the rotor mechanical angular velocity tracking error, and the rotor mechanical angular velocity tracking error change rate comprises: According to the sliding mode control strategy, the sliding mode exponential reaching law strategy is obtained; According to the sliding mode exponential reaching law strategy, a switching function, a switching gain factor and an exponential factor are obtained; Calculating an error state quantity according to the rotor mechanical angular velocity tracking error and the rotor mechanical angular velocity tracking error change rate; An adaptive exponential reaching law equation is constructed according to the nonlinear sliding surface equation, the switching function, the switching gain factor, the exponential factor and the error state quantity.

5. The method according to claim 1, characterized in that The step of constructing a collaborative observer according to the collaborative observer strategy includes: Obtain rotor mechanical angular velocity tracking error and load torque observation error; Calculating an error vector according to the rotor mechanical angular velocity tracking error and the load torque observation error; A collaborative observer is constructed according to the error vector, the collaborative observer strategy and the rotor mechanical angular velocity state equation.

6. The method according to claim 5, characterized in that The step of constructing a collaborative observer according to the error vector, the collaborative observer strategy and the rotor mechanical angular velocity state equation comprises: According to the cooperative observer strategy, the cooperative observer gain parameter and the cooperative observer control parameter are obtained; According to the rotor mechanical angular velocity state equation, the motor damping coefficient, the motor rotor moment of inertia, the actual value of the rotor mechanical angular velocity, the motor pole pair number and the motor permanent magnet flux are obtained; Calculating a load torque estimation value according to the collaborative observer gain parameter, the collaborative observer control parameter and the error vector; Calculating an estimated value of the rotor mechanical angular velocity according to the collaborative observer gain parameter, the collaborative observer control parameter, the motor damping coefficient, the motor rotor moment of inertia, the actual value of the rotor mechanical angular velocity, the motor pole pair number, and the motor permanent magnet flux linkage; A cooperative observer is constructed according to the load torque estimation value and the rotor mechanical angular velocity estimation value.

7. The method according to claim 1, characterized in that The step of calculating a control signal value according to the feedforward compensation gain value, the integrated speed controller and the collaborative observer, and completing the speed control of the permanent magnet synchronous motor according to the control signal value comprises: According to the feedforward compensation gain value, obtaining a current feedforward compensation signal value; Calculating a speed closed-loop control signal value according to the integrated speed controller and the collaborative observer; A target control signal value is calculated according to the current feedforward compensation signal value and the speed closed-loop control signal value, and speed control of the permanent magnet synchronous motor is completed according to the target control signal value.

8. A speed control device for a permanent magnet synchronous motor, characterized in that: The device comprises: A controller building module for building an integrated speed controller based on a composite nonlinear feedback strategy and a sliding mode control strategy; An observer construction module, used to construct a collaborative observer according to a collaborative observer strategy; A gain value calculation module, used to obtain an estimated load of the permanent magnet synchronous motor, and calculate a current feedforward compensation according to the estimated load to obtain a feedforward compensation gain value; The speed control module is used to calculate the control signal value according to the feedforward compensation gain value, the integrated speed controller and the collaborative observer, and complete the speed control of the permanent magnet synchronous motor according to the control signal value.

9. A speed control device for a permanent magnet synchronous motor, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the speed control method for a permanent magnet synchronous motor according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the speed control method of the permanent magnet synchronous motor according to any one of claims 1 to 7 are implemented.

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