Permanent magnet synchronous motor speed active disturbance rejection control method, medium and device

Abstract

The application relates to the technical field of permanent magnet motor control, in particular to a permanent magnet synchronous motor speed active disturbance rejection control method, medium and equipment, the method comprising the following steps: establishing a state space model of a three-order observer high-order extended observer; adding a low-pass filter on the state space model of the three-order observer high-order extended observer and introducing parameters to obtain a state space model of an improved high-order extended state observer; defining a disturbance sensitive function and a noise sensitive function according to the state space model of the improved high-order extended state observer; quantifying the anti-disturbance performance and noise suppression performance of the active disturbance rejection control through the disturbance sensitive function and the noise sensitive function; and ensuring that the control accuracy and robustness of the active disturbance rejection control system under dynamic working conditions reach optimal performance indexes. The application solves the technical problem of the imbalance among the control accuracy, interference suppression and noise suppression of the existing permanent magnet motor speed control strategy.

Description

Technical Field

[0001] This invention relates to the field of permanent magnet motor control technology, and in particular to a method, medium, and device for automatic disturbance rejection control of the speed of a permanent magnet synchronous motor. Background Technology

[0002] Currently, PI control is the most widely used speed control strategy for permanent magnet motors. However, PI control suffers from slower convergence speed, reduced accuracy, and decreased robustness when faced with low-frequency disturbances and high-frequency noise. Therefore, researchers have proposed various novel control strategies to replace PI control, with Active Disturbance Rejection Control (ADRC) being one of the most popular. ADRC compensates for the system's inner-loop input values ​​by using an Extended State Observer (ESO) to observe and define the total disturbance value, thus counteracting the effects of disturbance noise. However, this requires sufficiently high gain in the ESO's state parameters so that ADRC's response to the total disturbance is faster than the system's inner-loop response; otherwise, ADRC will output incorrect signals, leading to functional failures in the motor control system. High gain and differential calculations within the ESO amplify the disturbance and high-frequency noise signals entering ADRC, reducing the system's noise suppression capability; low gain, on the other hand, reduces the system's convergence speed and disturbance rejection capability, affecting ADRC's overall disturbance estimation ability and speed. To address this, researchers have proposed another observer: the Higher-Order Extended Observer (HESO). By increasing the order of the observer's extended states, asymptotic convergence of higher-order terms in the polynomial form of disturbance estimation is achieved, thereby improving the observer's accuracy. However, because HESO uses higher-order derivatives, the amplification factor of high-frequency disturbance signals and noise by HESO is much higher than that of ESO, which actually leads to a further decrease in HESO's observation accuracy. In addition, most existing observer gain parameter tuning adopts the "bandwidth method," resulting in poor parameter setting flexibility. When the system's dynamic quality fails to meet current requirements, all gain parameters need to be readjusted, greatly increasing the complexity and difficulty of system operation. Summary of the Invention

[0003] The main objective of this invention is to provide a method, medium, and device for automatic disturbance rejection control of permanent magnet synchronous motor speed, aiming to solve the technical problem of imbalance between control accuracy, disturbance suppression, and noise suppression in existing permanent magnet motor speed control strategies.

[0004] To achieve the above objectives, this invention proposes a method for automatic disturbance rejection control of the speed of a permanent magnet synchronous motor, comprising the following steps:

[0005] S1. Establish the state-space model of the third-order observer and the higher-order extended observer;

[0006] S2. Add a low-pass filter and introduce parameters to the state-space model of the higher-order extended observer of the third-order observer. This yields the state-space model of the improved high-order extended state observer;

[0007] S3, By adjusting parameters By modifying and improving the disturbance rejection performance and response speed of the higher-order extended state observer, the dynamic performance of active disturbance rejection control can be altered.

[0008] S4. Define disturbance sensitivity function and noise sensitivity function based on the state space model of the improved high-order extended state observer. Quantify the disturbance rejection performance and noise suppression performance of the active disturbance rejection control through the disturbance sensitivity function and noise sensitivity function to ensure that the control accuracy and robustness of the active disturbance rejection control system under dynamic conditions reach the optimal performance index.

[0009] A further improvement of the permanent magnet synchronous motor speed active disturbance rejection control method of the present invention lies in the following: the state space model of the third-order observer high-order extended observer is as follows:

[0010] ;

[0011] in: express Reference value of shaft current , Represents current. This indicates that the parameter is a reference value or a given value; This represents the error between the observed value and the actual value. and Represents the state variable gain parameter. This represents the speed estimate. Represents intermediate state variables. This represents the estimated total disturbance. This represents the actual values ​​of the observation parameters of the third-order observer and the higher-order extended observer. Represents the variable The predicted gain express The differential value, express The differential value, express The differential value of .

[0012] A further improvement of the permanent magnet synchronous motor speed active disturbance rejection control method of the present invention lies in the improved state space model of the high-order extended state observer as follows:

[0013] ;

[0014] in: This indicates the set low-pass filter time parameter. Indicates the disturbance observation adjustment parameters. This represents the error value after filtering by the low-pass filter. Representing variables The differential.

[0015] A further improvement of the permanent magnet synchronous motor speed active disturbance rejection control method of the present invention lies in that, after S3, before defining the disturbance sensitivity function and noise sensitivity function according to the state space model of the improved high-order extended state observer, the actual total disturbance is defined. Error between observed and actual values The transfer function between them is the disturbance sensitivity function. The perturbation sensitivity function of ESO is obtained:

[0016] ;

[0017] The perturbation sensitivity function of HESO is obtained as follows:

[0018] ;

[0019] in: This represents the observer gain parameter. Let the order be the observer. The calculation formula is:

[0020] ;

[0021] in: Indicates controller bandwidth. This represents the Laplace operator.

[0022] A further improvement of the permanent magnet synchronous motor speed active disturbance rejection control method of the present invention lies in that, after S3, before defining the disturbance sensitivity function and noise sensitivity function according to the state space model of the improved high-order extended state observer, the actual total disturbance is defined. The transfer function between the estimated disturbance and the noise sensitivity function is defined as the noise sensitivity function. The noise sensitivity function of ESO is obtained as follows:

[0023] ;

[0024] The noise sensitivity function of HESO is obtained as follows:

[0025] .

[0026] A further improvement of the permanent magnet synchronous motor speed active disturbance rejection control method of the present invention lies in defining the disturbance sensitivity function and noise sensitivity function according to the state space model of the improved high-order extended state observer as follows:

[0027] ;

[0028] .

[0029] The present invention also provides a readable storage medium storing a computer program adapted to be loaded by a processor and executed as described above for the active disturbance rejection control method for the speed of a permanent magnet synchronous motor.

[0030] The present invention also provides a computer device, the computer device including a memory and a processor, the memory storing a computer program, and when the computer program is executed by the processor, running the permanent magnet synchronous motor speed active disturbance rejection control method as described above.

[0031] The technical solution of the present invention has the following beneficial effects:

[0032] The active disturbance rejection control method for permanent magnet synchronous motor speed of the present invention introduces new controllable variables by improving the high-order extended state observer (IHESO). By adjusting the values ​​of the new variables, the performance of the observer is adjusted, thereby improving the degree of freedom of parameter tuning and enhancing the accuracy and robustness of the active disturbance rejection control (ADRC) controller. This solves the technical problem of the imbalance between control accuracy, disturbance suppression and noise suppression in existing permanent magnet motor speed control strategies.

[0033] This invention defines two new transfer functions, including one for defining the actual total disturbance. With error The transfer function between them is the disturbance sensitivity function. Define the actual total disturbance The transfer function between the estimated disturbance and the noise sensitivity function is the noise sensitivity function. The two new transfer functions mentioned above help to more intuitively quantify and analyze the disturbance rejection and noise suppression performance of ADRC. The performance of ADRC can be directly determined based on the Bode plot trend of the transfer function, ensuring that the control accuracy and robustness of the ADRC system under dynamic conditions reach the optimal performance index, and avoiding the state of overall performance imbalance caused by only maintaining a single performance advantage.

[0034] This invention combines a low-pass filter (LPF) with an observer, integrating the LPF structure into the observer's calculation equation for the error between the observed and actual target values. The internal structure of the observer is reorganized to ensure the reliability and structural stability of the newly designed Improved High-Order Extended State Observer (IHESO). The LPF filters the signal input to the IHESO calculation equation, removing some noise signals and reducing the impact of noise on the observer. This improves the IHESO's observation accuracy for both the total disturbance and the actual target value, thereby effectively improving the overall noise suppression performance and accuracy of ADRC. Simultaneously, the time parameter in the LPF... Introduced into the IHESO state equations, with the gain parameter remaining constant, by changing... The value can adjust the gain parameter's effect on the gain in the state equation, improving the IHESO's observation accuracy of the target value while also increasing the flexibility of IHESO parameter tuning and performance adjustment.

[0035] To address the issue of poor flexibility in gain parameter tuning, this invention introduces a new controllable parameter based on the traditional "bandwidth method". . The total disturbance estimate is set in the prediction equation for the IHESO observations. It is a separately adjustable module. When IHESO's observation accuracy of the total disturbance is insufficient or external disturbances change and it is necessary to adjust a certain aspect of ADRC's performance, it can be adjusted... By altering IHESO's disturbance rejection performance and response speed, its robustness to disturbance variations will be significantly improved, thereby enhancing the dynamic performance of ADRC. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0037] Figure 1 This is a schematic diagram of the structure of the permanent magnet synchronous motor speed active disturbance rejection control method of the present invention;

[0038] Figure 1 This is a traditional HESO structure block diagram;

[0039] Figure 2 Here is a block diagram of ADRC based on IHESO;

[0040] Figure 3 Bode plots of the IHESO and HESO interference sensitivity functions Ge;

[0041] Figure 4 Bode plots of the noise suppression functions Gz for IHESO and HESO;

[0042] Figure 5 The results are from a steady-state test of the motor based on the HESO-based ADRC strategy (50% of rated load).

[0043] Figure 6 The results are based on the IHESO-based ADRC strategy and show the steady-state test results of the motor (50% of rated load).

[0044] Figure 7 The results of motor loading experiments (50% of rated load) based on the HESO-based ADRC strategy are shown.

[0045] Figure 8 The results of motor load reduction experiments (50% of rated load) based on the HESO-based ADRC strategy are shown.

[0046] Figure 9 The results of motor loading experiments (50% of rated load) based on the IHESO-based ADRC strategy are shown.

[0047] Figure 10 The results of motor load reduction experiments (50% of rated load) based on the IHESO-based ADRC strategy are shown.

[0048] Figure 11 The results of motor acceleration / deceleration tests based on the HESO-based ADRC strategy are shown.

[0049] Figure 12 The results are from motor acceleration / deceleration tests based on the IHESO-based ADRC strategy. Detailed Implementation

[0050] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0051] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0052] Furthermore, in this invention, descriptions involving "first," "second," etc., are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0053] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0054] Furthermore, the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they are feasible for those skilled in the art. If the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0055] When the observer observes the total disturbance, the high state variable gain amplifies the disturbance signal and high-frequency noise signal, leading to inaccurate compensation signals in the inner loop of the input system and a decrease in the anti-interference capability of Active Disturbance Rejection Control (ADRC). The high-frequency signal input to the observer (including noise and some high-frequency components of the signal) is significantly amplified after several internal differentiation operations, which reduces the high-frequency signal and noise suppression capability of the ADRC controller (hereinafter referred to as "noise suppression capability"). The tuning of the observer's state variable gain parameters typically uses the "bandwidth method," where each parameter is proportional to the bandwidth value, resulting in poor flexibility in parameter adjustment and indirectly affecting the ADRC's disturbance rejection performance. To address these issues, a balance needs to be maintained between the ADRC's disturbance rejection performance and noise suppression performance. Quantitative analysis of disturbance rejection and noise suppression performance was conducted to study their changing trends during gain parameter tuning, thereby determining the optimal gain parameter value. This ensures that ADRC meets performance requirements in both disturbance rejection and noise suppression while maintaining optimal control accuracy and robustness under dynamic conditions. Since the differential calculation component inherent in the observer amplifies noise, a filter is added to the observer to reduce input noise and improve noise suppression. However, considering potential conflicts between the new filter and the original observer structure, the improved observer needs structural reconfiguration to ensure the normal operation of the Improved Higher-Order Extended State Observer (IHESO). To address the issue of poor parameter setting flexibility, IHESO introduces a new controllable variable. Adjusting the value of this new variable regulates observer performance, increasing the degree of freedom in parameter tuning and enhancing the accuracy and robustness of the ADRC controller.

[0056] like Figure 2 As shown in the figure, this invention proposes a method for automatic disturbance rejection control of the speed of a permanent magnet synchronous motor, comprising the following steps:

[0057] S1. Establish the state-space model of the third-order observer and the higher-order extended observer;

[0058] S2. Add a low-pass filter and introduce parameters to the state-space model of the higher-order extended observer of the third-order observer. This yields the state-space model of the improved high-order extended state observer;

[0059] S3, By adjusting parameters By modifying and improving the disturbance rejection performance and response speed of the higher-order extended state observer, the dynamic performance of active disturbance rejection control can be altered.

[0060] S4. Define disturbance sensitivity function and noise sensitivity function based on the state space model of the improved high-order extended state observer. Quantify the disturbance rejection performance and noise suppression performance of the active disturbance rejection control through the disturbance sensitivity function and noise sensitivity function to ensure that the control accuracy and robustness of the active disturbance rejection control system under dynamic conditions reach the optimal performance index.

[0061] Specifically, the state-space model of the higher-order extended observer of the third-order observer is as follows:

[0062] ;

[0063] in: express Reference value of shaft current , Represents current. This indicates that the parameter is a reference value or a given value; This represents the error between the observed value and the actual value. and Represents the state variable gain parameter. , , Indicates the controller bandwidth; This represents the speed estimate. Represents intermediate state variables. This represents the estimated total disturbance. This represents the actual value of the observation parameters of the third-order observer and the higher-order extended observer. In this invention, it represents the mechanical angular velocity of the motor. , Represents the variable The predicted gain express The differential value, express The differential value, express The differential value of .

[0064] Specifically, a low-pass filter (LPF) was added to the basic structure of the HESO system to reduce the number of iterations and achieve optimization; adjustable parameters were introduced. To better adjust the observer's accuracy in observing the total disturbance, the adjustable parameters will be... Assuming the total disturbance estimate is included in the calculation formula, and reorganizing the improved observer structure, the state-space model of the improved high-order extended state observer is obtained as follows:

[0065] ;

[0066] in: This indicates the set low-pass filter time parameter. Indicates the disturbance observation adjustment parameters. This represents the error value after filtering by the low-pass filter. Representing variables The differential.

[0067] like Figure 1 The diagram shown is a structural block diagram of HESO. Figure 2 The diagram illustrates the structural framework of the designed IHESO and the principle of the ADRC structure based on IHESO. A low-pass filter (LPF) and adjustable parameters are added to the HESO structure. By filtering out noise signals and adjusting a single gain parameter, operating efficiency is improved, response time is shortened, and the internal structure of the observer is reorganized to ensure the reliability and structural stability of the newly designed IHESO. The LPF (Local Power Filter) is incorporated into the observer's equation for calculating the error between the observed and actual values, filtering out some noise signals in the input signal and reducing the impact of noise on the system's dynamic performance. In terms of parameter tuning, IHESO introduces new controllable parameters. . It is set in the prediction equations for the total disturbance observations of IHESO, so that It becomes a separate, adjustable module, while reducing the value of the gain parameter, thus reducing the impact of disturbances and noise on IHESO. This is achieved through adjustment. This can alter the disturbance rejection performance and response speed of IHESO, significantly improving the flexibility of IHESO parameter tuning and the controllability of the gain parameters. It solves the problem that traditional bandwidth methods cannot independently adjust the gain parameters after determination, while also improving the dynamic performance of ADRC. (See figure.) This represents the motor's inertia. Represents the Laplace operator. Indicates the coefficient of friction. Indicates the filter time constant. Indicates the actual speed of the motor. Indicates noise. Indicates the estimated gain. This represents the proportionality coefficient. In the equation representing the electromagnetic torque of the motor coefficient, , Indicates the number of pole pairs of the motor. This indicates the magnetic flux linkage of the permanent magnet in the motor. Indicates electromagnetic torque. Indicates load torque. This represents the system input quantity; in this invention, it represents the setpoint value of the motor speed.

[0068] Furthermore, the actual total disturbance is defined. Error between observed and actual values The transfer function between them is the disturbance sensitivity function. When the total disturbance value is the same, The smaller the amplitude-frequency response, the smaller the error between the observed and actual values. This leads to the ESO perturbation sensitivity function:

[0069] ;

[0070] The perturbation sensitivity function of HESO is obtained as follows:

[0071] ;

[0072] in: This represents the observer gain parameter. Let the order be the observer. The calculation formula is:

[0073] ;

[0074] in: Indicates controller bandwidth. This represents the Laplace operator.

[0075] Furthermore, the actual total disturbance is defined. The transfer function between the estimated disturbance and the noise sensitivity function is defined as the noise sensitivity function. , The closer the amplitude-frequency response is to zero, the smaller the error between the observed and actual values, indicating that ADRC has a better suppression effect on high-frequency noise. Therefore, the noise sensitivity function of ESO is obtained:

[0076] ;

[0077] The noise sensitivity function of HESO is obtained as follows:

[0078] .

[0079] Furthermore, based on the state-space model of the improved high-order extended state observer, the disturbance sensitivity function and noise sensitivity function are defined as follows:

[0080] ;

[0081] .

[0082] Figure 3 , Figure 4 IHESO and HESO perturbation sensitivity functions, respectively. and noise sensitivity function Podtó, by Figure 3 We can analyze that, in the observation of low-to-mid-frequency disturbances, if the input signals of IHESO and HESO are the same, the error between the disturbance value estimated by IHESO and the actual disturbance value is smaller than that of HESO, indicating that IHESO's estimation accuracy is higher than HESO's. For high-frequency signals above 1000Hz, the gain amplitudes of IHESO and HESO are similar, indicating that under the same input signal conditions, the errors produced by IHESO and HESO in disturbance estimation are similar, and the estimation accuracy of IHESO is the same as that of HESO. Overall, IHESO's disturbance rejection performance is better than HESO's. The horizontal axis in the figure represents frequency, and the vertical axis represents magnitude.

[0083] Depend on Figure 4 Analysis reveals that, under the condition of constant total system disturbance, for low- and mid-frequency signals, the disturbance prediction gain amplitudes of both IHESO and HESO are close to 0 dB / dec, indicating high disturbance prediction accuracy. However, for high-frequency noisy signals, a significant difference emerges in the signal predictions of HESO and IHESO. The gain amplitude of IHESO becomes significantly smaller than that of HESO, and the slope of the gain amplitude change in IHESO is also less than that of HESO. This indicates that, under the same frequency and bandwidth conditions, IHESO's prediction for the noise signal at that frequency is smaller than HESO's. Furthermore, the proportion of high-frequency noise in the final total disturbance prediction output of IHESO is less than that of HESO, resulting in higher accuracy. Therefore, it can be concluded that IHESO has a better noise suppression capability than HESO.

[0084] Figure 5 , Figure 6The results of steady-state tests on motors using ADRC strategies based on HESO and IHESO are presented, respectively. The experimental load was 50% of the rated load of the motor, and white noise interference was applied to the motor. When the motor was controlled by IHESO, the maximum oscillation amplitude of the motor's iq waveform was 0.38A, while the maximum oscillation amplitude was 0.50A when controlled by HESO. This shows that IHESO reduces the impact of white noise on the current better than HESO, exhibiting superior noise suppression performance.

[0085] Figure 7 , Figure 8 The results of motor loading and unloading experiments based on the HESO-based ADRC strategy are as follows. Figure 9 , Figure 10 The results of the motor loading and unloading experiment based on the IHESO ADRC strategy are shown. The amplitude of the changing load is 50% of the rated load of the experimental motor, and white noise interference is applied to the motor. During the process from the sudden addition of 50% load to the motor stabilizing again, IHESO still has good disturbance rejection compared to HESO under the condition of high frequency noise interference. It can effectively suppress disturbances while reducing noise interference. The ADRC controller based on IHESO can still maintain good dynamic response performance.

[0086] Figure 11 , Figure 12 The test results are shown for motor acceleration / deceleration using an ADRC strategy based on HESO and an ADRC strategy based on IHESO, respectively. The motor was ramped from a given speed of 200 r / min to 400 r / min, and then ramped back down to 200 r / min after stabilization. When using the IHESO-based ADRC controller, the maximum amplitude of the motor speed oscillation was significantly lower than when using the HESO-based controller. This indicates the accuracy of the controller's disturbance estimation. IHESO has higher accuracy and more accurate disturbance estimation than HESO, and therefore exhibits better disturbance rejection capability.

[0087] The above description is only a preferred embodiment of the present invention and does not limit the scope of the present invention. All equivalent structural transformations made under the inventive concept of the present invention using the contents of the present invention specification and drawings, or direct / indirect applications in other related technical fields, are included within the protection scope of the present invention.

Claims

1. A method for automatic disturbance rejection control of the speed of a permanent magnet synchronous motor, characterized in that, Includes the following steps: S1. Establish the state-space model of the third-order observer and the higher-order extended observer; S2. Add a low-pass filter and introduce parameters to the state-space model of the higher-order extended observer of the third-order observer. This yields the state-space model of the improved high-order extended state observer; S3, By adjusting parameters By modifying and improving the disturbance rejection performance and response speed of the higher-order extended state observer, the dynamic performance of active disturbance rejection control can be altered. The state-space model of the improved high-order extended state observer is as follows: ； in: This indicates the set low-pass filter time parameter. Indicates the disturbance observation adjustment parameters. This represents the error value after filtering by the low-pass filter. Representing variables The differential, This represents the speed estimate. Represents intermediate state variables. This represents the estimated total disturbance. This represents the actual values ​​of the observation parameters of the third-order observer and the higher-order extended observer. Represents the variable The predicted gain; in: This represents the observer gain parameter. Let the order be the observer. Indicates controller bandwidth. The calculation formula is: ； S4. Define disturbance sensitivity function and noise sensitivity function based on the state space model of the improved high-order extended state observer. Quantify the disturbance rejection performance and noise suppression performance of the active disturbance rejection control through the disturbance sensitivity function and noise sensitivity function to ensure that the control accuracy and robustness of the active disturbance rejection control system under dynamic conditions reach the optimal performance index. Based on the state-space model of the improved high-order extended state observer, the disturbance sensitivity function and noise sensitivity function are defined as follows: ； 。 2. The speed active disturbance rejection control method for permanent magnet synchronous motors according to claim 1, characterized in that, The state-space model of the third-order observer and the higher-order extended observer is as follows: ； in: express Reference value of shaft current , Represents current. This indicates that the parameter is a reference value or a given value; This represents the error between the observed value and the actual value. and Represents the state variable gain parameter. express The differential value, express The differential value, express The differential value of .

3. The speed active disturbance rejection control method for permanent magnet synchronous motors according to claim 2, characterized in that, After S3, before defining the disturbance sensitivity function and noise sensitivity function based on the state-space model of the improved higher-order extended state observer, the actual total disturbance is defined. Error between observed and actual values The transfer function between them is the disturbance sensitivity function. The perturbation sensitivity function of ESO is obtained: ； The perturbation sensitivity function of HESO is obtained as follows: ； in: This represents the Laplace operator.

4. The speed active disturbance rejection control method for permanent magnet synchronous motors according to claim 3, characterized in that, After S3, before defining the disturbance sensitivity function and noise sensitivity function based on the state-space model of the improved higher-order extended state observer, the actual total disturbance is defined. The transfer function between the estimated disturbance and the noise sensitivity function is defined as the noise sensitivity function. The noise sensitivity function of ESO is obtained as follows: ； The noise sensitivity function of HESO is obtained as follows: 。 5. A readable storage medium, characterized in that, The readable storage medium stores a computer program that is adapted to be loaded by a processor and executed by the speed active disturbance rejection control method for permanent magnet synchronous motors according to any one of claims 1-4.

6. A computer device, characterized in that, The computer device includes a memory and a processor. The memory stores a computer program, which, when executed by the processor, runs the speed active disturbance rejection control method for permanent magnet synchronous motors according to any one of claims 1-4.

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