Composite active-disturbance-rejection control method of grid-connected inverter system based on duplex-winding induction motor

Abstract

The invention discloses a composite active-disturbance-rejection control method of a grid-connected inverter system based on a duplex-winding induction motor, and belongs to the technical field of motor control. Aiming at the control problems of multivariate, strong coupling and complex disturbance of the duplex-winding induction motor, the method comprises the following steps: firstly, listing a state equation of the duplex-winding induction motor; furthermore, a composite extended state observer is designed, a proportional element and a quasi-resonance controller are introduced into the observer on the basis of a traditional structure, and aperiodic disturbance and periodic disturbance with specific frequency can be estimated at the same time with high precision. According to the invention, the inhibition capability of the system on various disturbances is effectively improved, and the dynamic response speed and the steady-state control precision of the double-winding induction motor driving system are obviously improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of motor control, and relates to a composite active disturbance rejection control method of a grid-connected inverter system based on a double-winding induction motor. BACKGROUND

[0002] With the popularization of renewable energy grid-connected systems, the power grid is facing increasingly prominent problems such as wideband oscillation, inertia reduction and strength weakening. As an effective grid interface device, the double-winding induction motor (DWIM) can alleviate the above problems. However, the DWIM is a nonlinear, multivariable and strongly coupled system, and its high-performance control faces challenges.

[0003] The self-disturbance rejection control (ADRC) is first proposed in the paper entitled From PID to active disturbance rejection control (J. Han, From PID to active disturbance rejection control, in IEEE Transactions on Industrial Electronics, vol. 56, no. 3, pp. 900-906, Mar. 2009) (From PID to active disturbance rejection control) (Jingqing Han, From PID to active disturbance rejection control, IEEE Industrial Electronics, vol. 56, no. 3, pp. 900-906, March 2009), which estimates and compensates disturbances in real time. The core of the ADRC framework is the extended state observer (ESO), which regards internal uncertainty and external disturbance as a generalized total disturbance.

[0004] The ESO bandwidth of the traditional ADRC is limited, and too high noise is introduced, and too low leads to insufficient low-frequency disturbance suppression capability, and the suppression effect of periodic harmonic disturbance is not good. Some scholars have proposed to improve the anti-non-periodic disturbance ability of the ESO, for example: Robust speed control of electrical drives with reduced ripple using adaptive switching high-order extended state observer, in IEEE Transactions on Power Electronics, vol. 37, no. 2, pp. 2009-2020, Feb. 2022) adopts two groups of high-order ESOs and switches them online according to the motor operating state, which requires a large amount of experimental data to provide the basis for discrimination, and the discrimination basis also needs to be changed after the working condition is changed.

[0005] Some scholars have proposed to improve the anti-periodic disturbance ability of ESO, for example: Guo, S. Bacha, M. Alamir, A. Hably, and C. Boudinet, Generalized integrator-extended state observer with applications to grid-connected converters in the presence of disturbances, in IEEE Transactions on Control Systems Technology, vol. 29, no. 2, pp. 744-755, Mar. 2021) introduces a generalized integrator aiming to suppress harmonic frequencies, at the cost of amplifying disturbances around the harmonic frequencies.

[0006] In summary, the prior art has the following problems: (1) It is complex in structure or parameter tuning, different parameters are needed for different working conditions, the calculation amount is large, and experimental data are needed for parameter tuning.

[0007] (2) There is a contradiction between noise suppression and disturbance suppression, and it is difficult to achieve a good balance between dynamic response and steady-state accuracy.

[0008] (3) When ADRC is applied to DWIM, a MIMO system, the coupling problem increases the difficulty of controller design. SUMMARY

[0009] The purpose of the present application is to overcome the shortcomings of the prior art and provide a composite active disturbance rejection control method based on double-winding induction motor grid connection. This method significantly improves the suppression ability of periodic and non-periodic disturbances through system decoupling and observer structure optimization, while ensuring the dynamic response speed and steady-state accuracy of the system.

[0010] To achieve the above object, the application adopts the following technical solutions: A composite active disturbance rejection control method of a grid-connected inverter system based on a double-winding induction motor, the grid-connected inverter system comprising a DC side power supply, an inverter, a double-winding asynchronous motor and an excitation capacitor; the steps are as follows: Step 1, sampling the following parameters of the double-winding asynchronous motor: three-phase stator voltage and three-phase current of the control winding, three-phase stator voltage and three-phase current of the grid-connected winding; then obtaining the actual values of the dq-axis stator voltage of the control winding , , the actual values of the dq-axis current of the control winding , , the actual values of the dq-axis stator voltage of the grid-connected winding , , the actual values of the dq-axis current of the grid-connected winding , ; Step 2, establishing a mathematical model of the double-winding induction motor, including a voltage equation and a flux linkage equation in a synchronous rotating coordinate system; Step 3, obtaining a standard state equation of the double-winding induction motor according to the mathematical model of Step 2, and obtaining a control quantity gain matrix ; Step 4, introducing a quasi-resonant controller, introducing the control quantity gain matrix , and constructing a composite active disturbance rejection control extended state observer; Step 5, generating a control signal to drive the double-winding induction motor based on the output of the composite active disturbance rejection control extended state observer.

[0011] Preferably, the expression of the voltage equation in Step 2 is: ; The expression of the flux linkage equation is: ; In the formula, , is the dq-axis current of the rotor, , is the dq-axis voltage of the rotor, and the double-winding induction motor is a squirrel-cage asynchronous motor, =0, =0; is a stator resistance, is a rotor resistance, , is the dq-axis flux linkage of the control winding, , is the dq-axis flux linkage of the grid-connected winding, , is the dq-axis flux linkage of the rotor, e is the synchronous angular frequency, is the rotor angular frequency, is the differential operator, is the stator winding leakage inductance, is the rotor winding leakage inductance, is the mutual leakage inductance between the two stator windings, is the mutual inductance between the stator winding and the rotor winding.

[0012] Preferably, the expression of the standard state equation of the double-winding induction motor of step 3 is: ; wherein, is the state variable gain matrix, is the differential operator; the expression of the control variable gain matrix is: ; wherein, d is the first control variable gain, e is the second control variable gain 。

[0013] Preferably, the expression of the transfer function of the quasi-resonant controller of step 4 is: ; wherein, is the resonant gain of the quasi-resonant controller, is the resonant frequency of the quasi-resonant controller, is the bandwidth of the quasi-resonant controller, is the Laplace operator; the expression of the extended state observer of the composite active disturbance rejection control comprises a dynamic equation 1 for controlling the d-axis winding current and a dynamic equation 2 for controlling the q-axis winding current; the expression of the dynamic equation 1 is: ; the expression of the dynamic equation 2 is: ; wherein, is the estimated value of the d-axis winding current, is the estimated value of the d-axis winding current disturbance, is the estimated value of the q-axis winding current, is the estimated value of the q-axis winding current disturbance, is the actual value of the d-axis winding current​ and the difference between the control winding d-axis current actual value and the control winding d-axis current estimated value and the difference between the control winding q-axis current actual value and the control winding q-axis current estimated value are respectively a first gain and a second gain of the extended state observer of the active disturbance rejection control, is a Laplace operator, is a first row of the control quantity gain matrix is a second row of the control quantity gain matrix = [d 0 e 0], = [0 d 0 e], d is a control quantity first gain, e is 。

[0014] Preferably, the control quantity first gain d e is calculated as follows: wherein, is a stator winding leakage inductance, is a rotor winding leakage inductance, is a mutual leakage inductance between two stator windings, is a mutual inductance between the stator winding and the rotor winding.

[0015] Preferably, the state quantity gain matrix is expressed as follows: wherein, a, b, c are respectively a state quantity first gain, a state quantity second gain, a state quantity third gain, and are calculated as follows: wherein, is a stator winding leakage inductance, is a rotor winding leakage inductance.​​​​​​​​​​​​​​​​​​​ is mutual leakage inductance between two stator windings, is mutual inductance between stator winding and rotor winding, e is synchronous angular frequency, is stator resistance, is rotor resistance.

[0016] Compared with the prior art, the present application has the beneficial effects that: 1. The present application embeds a quasi-resonant controller (QR) in a traditional extended state observer (ESO) to obtain a composite extended state observer (CESO) of active disturbance rejection control, which has a steeper amplitude-frequency characteristic in the low-frequency band and reduces disturbance estimation error. The embedded quasi-resonant controller (QR) provides high gain at a specific harmonic frequency, achieving accurate estimation and compensation of periodic disturbances. 2. The effective decoupling of the DWIM system is realized through the control quantity gain matrix, simplifying the complex MIMO control problem into a SISO problem. The proposed CESO structure enhances the estimation ability of total disturbance, especially improving the observation accuracy of low-frequency non-periodic disturbance and specific frequency periodic disturbance. Compared with the traditional ADRC method, the present application shows better dynamic response performance and steady-state accuracy under grid voltage drop and harmonic disturbance conditions, while maintaining strong robustness. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 is the overall control structure block diagram of the double-winding induction motor grid-connected inverter system of the embodiment of the present application.

[0018] Figure 2 is the structure block diagram of the composite extended state observer (CESO) of active disturbance rejection control of the present application.

[0019] Figure 3 is the bandwidth of different resonant controllers Bode diagram of disturbance estimation error transfer function of the CESO and the traditional ESO.

[0020] Figure 4 is the gain of different resonant controllers Bode diagram analysis of disturbance estimation error transfer function of the CESO and the traditional ESO.

[0021] Figure 5 is the resonant frequency of different resonant controllers Bode diagram of disturbance estimation error transfer function of the CESO and the traditional ESO.

[0022] Figure 6is the dynamic response graph of the d-axis and q-axis currents of the traditional ESO control of the double-winding induction motor grid-connected inverter system in the simulation verification of the application.

[0023] Figure 7 is the dynamic response graph of the d-axis and q-axis currents of the CESCO control in the simulation verification of the application.

[0024] Figure 8 is the d-axis current harmonic analysis (FFT) graph of the traditional ESO control of the double-winding induction motor grid-connected inverter system in the simulation verification of the application.

[0025] Figure 9 is the d-axis current harmonic analysis (FFT) graph of the CESCO control of the double-winding induction motor grid-connected inverter system in the simulation verification of the application. DETAILED DESCRIPTION

[0026] The technical solutions of the application will be described in detail below with reference to the drawings and embodiments.

[0027] Figure 1 is the overall control structure block diagram of the grid-connected inverter system of the embodiment of the application, which gives the overall state of the control method of the application, wherein, and are the given current values of the control winding dq axes, is the control rate coefficient, and are the given voltage values of the control winding dq axes, is the control quantity gain matrix, is the inverse of the control quantity gain matrix, the CESCO module is a composite active disturbance rejection control module, is a coordinate transformation matrix for converting the dq-axis coordinates into axes, and are the given voltage values of the control winding axes, and the SVPWM is a modulation mode. Figure 1 It can be seen that the grid-connected inverter system comprises a DC side power supply, an inverter, a double-winding asynchronous motor and an excitation capacitor. The steps of the composite active disturbance rejection control method of the grid-connected inverter system based on the double-winding induction motor of the application are as follows: Step 1: sample the following parameters of the double-winding asynchronous motor: the three-phase stator voltage and three-phase current of the control winding, and the three-phase stator voltage and three-phase current of the grid-connected winding; then obtain the actual values of the control winding dq-axis stator voltage , and the actual values of the control winding dq-axis current , Actual value of dq-axis stator voltage of grid-connected winding , Actual value of dq-axis current of grid-connected winding , .

[0028] Step 2: Establish a mathematical model of the dual-winding induction motor, including the voltage equation and flux linkage equation in the synchronous rotating coordinate system.

[0029] In this embodiment, the expression for the voltage equation is: ; The expression for the magnetic flux linkage equation is: ; In the formula, , The dq-axis current of the rotor is... , Given the dq-axis voltage of the rotor, the dual-winding induction motor is designed to be a squirrel-cage asynchronous motor. =0, =0; For stator resistance, For rotor resistance, , To control the dq axis flux linkage of the winding, , For the dq axis flux linkage of the grid-connected winding, , For the dq axis flux linkage of the rotor, e The synchronization angular frequency, The rotor angular frequency, For differential operators, For stator winding leakage inductance, For rotor winding leakage inductance, The leakage inductance between the two stator windings This refers to the mutual inductance between the stator winding and the rotor winding.

[0030] Step 3: Based on the mathematical model in Step 2, obtain the standard state equation of the dual-winding induction motor and the control gain matrix. .

[0031] In this embodiment, the standard state equation of the dual-winding induction motor is expressed as follows: ; in, Here is the state variable gain matrix. It is a differential operator; The control gain matrix The expression is: ; In the formula, d To control the first gain, e is Second gain of control quantity 。

[0032] In this embodiment, the first gain of the control quantity d Second gain of control quantity e The calculation formulas are as follows: ; In the formula, For stator winding leakage inductance, For rotor winding leakage inductance, The leakage inductance between the two stator windings This refers to the mutual inductance between the stator winding and the rotor winding.

[0033] In this embodiment, the state quantity gain matrix The expression is as follows: ; in, a, b, c These are the first gain, second gain, and third gain of the state variable, respectively, and their calculation formulas are as follows: ; ; ; In the formula, For stator winding leakage inductance, For rotor winding leakage inductance, The leakage inductance between the two stator windings For the mutual inductance between the stator winding and the rotor winding, e The synchronization angular frequency, For stator resistance, This represents the rotor resistance.

[0034] Step 4: Introduce a quasi-resonant controller and introduce a control gain matrix. A composite active disturbance rejection control extended state observer was constructed.

[0035] Figure 2 This is a structural block diagram of the Composite Active Disturbance Rejection Control Extended State Observer (CESO) of the present invention.

[0036] In this embodiment, the transfer function of the quasi-resonant controller The expression is: ; in, a resonance gain for the quasi-resonant controller, a resonance frequency for the quasi-resonant controller, a bandwidth for the quasi-resonant controller, a Laplacian operator.

[0037] The expression of the composite active disturbance rejection control extended state observer includes dynamic equation 1 and dynamic equation 2, wherein dynamic equation 1 is used to control the winding d-axis current, and dynamic equation 2 is used to control the winding q-axis current.

[0038] The expression of the dynamic equation 1 is: ; The expression of the dynamic equation 2 is: ; wherein, is an estimated value of the control winding d-axis current, is an estimated value of the disturbance of the control winding d-axis current, is an estimated value of the control winding q-axis current, is an estimated value of the disturbance of the control winding q-axis current, is a difference between an actual value of the control winding d-axis current and the estimated value of the control winding d-axis current , is a difference between an actual value of the control winding q-axis current and the estimated value of the control winding q-axis current , , , , are derivatives of , , , , and are a first gain and a second gain of the composite active disturbance rejection control extended state observer, is a Laplacian operator, is a first row of a control quantity gain matrix , is a second row of the control quantity gain matrix , = [d 0 e 0], = [0 d 0 e], d is the control quantity first gain, e is the control quantity second gain 。

[0039] Step 5, based on the output of the composite active disturbance rejection control extended state observer, generate a control signal to drive the double-winding induction motor.

[0040] In order to verify the beneficial effects of the present application, tests and simulations were carried out.

[0041] Figure 3 is the Bode plot of the disturbance estimation error transfer function of the CESCO and the conventional ESO for different resonant controller bandwidth From the figure, it can be seen that compared with the conventional ESO, the CESCO of the present application shows a steeper slope and a significantly lower amplitude at low frequencies, thereby reducing the disturbance estimation error. This enhanced low-frequency performance enables the CESCO to estimate non-periodic disturbances. As the resonant controller bandwidth increases, the opening of the Bode plot at the resonant frequency of the resonant controller becomes larger, and the range of the suppression frequency becomes larger.

[0042] Figure 4 is the Bode plot of the disturbance estimation error transfer function of the CESCO and the conventional ESO for different resonant controller gain From the figure, it can be seen that as the resonant controller gain increases, the amplitude of the Bode plot at the resonant frequency of the resonant controller becomes larger, and the degree of suppression of the resonant frequency becomes larger.

[0043] Figure 5 is the Bode plot of the disturbance estimation error transfer function of the CESCO and the conventional ESO for different resonant controller resonant frequency From the figure, it can be seen that as the resonant controller resonant frequency increases, the frequency of the Bode plot at the resonant frequency of the resonant controller becomes larger, and the resonant frequency of the suppression becomes larger.

[0044] Figure 6is a dynamic response graph of d-axis and q-axis currents of the control winding of the double-winding induction motor grid-connected inverter system of the traditional ESO control in the simulation verification of the application. The upper half of the figure is the d-axis current of the control winding of the double-winding induction motor grid-connected inverter system, the vertical coordinate is 0.2A / div, the lower half is the q-axis current of the control winding of the double-winding induction motor grid-connected inverter system, the vertical coordinate is 0.5A / div, and the horizontal coordinate of the figure is 0.001s / div. Simulation is carried out on a 10kW double-winding induction motor grid-connected inverter system, and the d-axis current command is set to 5A and the q-axis current command is set to 10A. At time t=2s, the grid voltage is simulated to drop from 310V to 155V, generating aperiodic disturbance. The dynamic recovery time of the d-axis current and the q-axis current of the control winding of the double-winding induction motor grid-connected inverter system is 0.0025s, the dynamic overshoot of the d-axis current of the control winding of the double-winding induction motor grid-connected inverter system is 0.2A, and the dynamic overshoot of the q-axis current of the control winding of the double-winding induction motor grid-connected inverter system is 1A.

[0045] Figure 7 is a dynamic response graph of d-axis and q-axis currents of the CESCO control in the simulation verification of the application. The upper half of the figure is the d-axis current of the control winding of the double-winding induction motor grid-connected inverter system, the vertical coordinate is 0.05A / div, the lower half is the q-axis current of the control winding of the double-winding induction motor grid-connected inverter system, the vertical coordinate is 0.2A / div, and the horizontal coordinate of the figure is 0.001s / div. Simulation is carried out on a 10kW double-winding induction motor grid-connected inverter system, and the d-axis current command is set to 5A and the q-axis current command is set to 10A. At time t=2s, the grid voltage is simulated to drop from 310V to 155V, generating aperiodic disturbance. The dynamic recovery time of the d-axis current of the control winding of the double-winding induction motor grid-connected inverter system is 0.001s, and the dynamic recovery time of the q-axis current is 0.0015s, both of which are less than the dynamic recovery time under the traditional ESO control. The dynamic overshoot of the d-axis current of the control winding of the double-winding induction motor grid-connected inverter system is 0.1A, and the dynamic overshoot of the q-axis current of the control winding of the double-winding induction motor grid-connected inverter system is 0.6A, both of which are less than the dynamic overshoot under the traditional ESO control.

[0046] Figure 8is the d-axis current harmonic analysis (FFT) graph of the double-winding induction motor grid-connected inverter system controlled by the traditional ESO control in the steady state in the simulation verification of the application. The horizontal coordinate is the harmonic number, DC is the direct current component amplitude, and the vertical coordinate is the harmonic amplitude percentage of the direct current component DC. The simulation is carried out on the 10kW double-winding induction motor grid-connected inverter system, and the d-axis current command is set to 5A and the q-axis current command is set to 10A. After the steady state, the double-winding induction motor grid-connected inverter system is subjected to 6th harmonic periodic disturbance. The six harmonic amplitude of the d-axis current controlled by the traditional ESO control is 1.96% of the direct current component amplitude.

[0047] Figure 9 is the d-axis current harmonic analysis (FFT) graph of the double-winding induction motor grid-connected inverter system controlled by the traditional ESO control in the steady state in the simulation verification of the application. The horizontal coordinate is the harmonic number, DC is the direct current component amplitude, and the vertical coordinate is the harmonic amplitude percentage of the direct current component DC. The simulation is carried out on the 10kW double-winding induction motor grid-connected inverter system, and the d-axis current command is set to 5A and the q-axis current command is set to 10A. After the steady state, the double-winding induction motor grid-connected inverter system is subjected to 6th harmonic periodic disturbance. The six harmonic amplitude of the d-axis current controlled by the traditional ESO control is 1.96% of the direct current component amplitude.

[0047] Figure 9 is the d-axis current harmonic analysis (FFT) graph of the double-winding induction motor grid-connected inverter system controlled by the traditional ESO control in the steady state in the simulation verification of the application. The horizontal coordinate is the harmonic number, DC is the direct current component amplitude, and the vertical coordinate is the harmonic amplitude percentage of the direct current component DC. The simulation is carried out on the 10kW double-winding induction motor grid-connected inverter system, and the d-axis current command is set to 5A and the q-axis current command is set to 10A. After the steady state, the double-winding induction motor grid-connected inverter system is subjected to 6th harmonic periodic disturbance. The six harmonic amplitude of the d-axis current controlled by the traditional ESO control is 1.96% of the direct current component amplitude.

Claims

1. A composite active disturbance rejection control method for a grid-connected inverter system based on a dual-winding induction motor, wherein the grid-connected inverter system includes a DC-side power supply, an inverter, a dual-winding asynchronous motor, and an excitation capacitor; characterized in that, The steps are as follows: Step 1: Sample the following parameters of the dual-winding asynchronous motor: three-phase stator voltage and three-phase current of the control winding, and three-phase stator voltage and three-phase current of the grid-connected winding; then obtain the actual values ​​of the dq-axis stator voltage of the control winding through coordinate transformation. , Actual value of dq axis current of control winding , Actual value of dq-axis stator voltage of grid-connected winding , Actual value of grid-connected winding dq axis current , ; Step 2: Establish a mathematical model of the dual-winding induction motor, including the voltage equation and flux linkage equation in the synchronous rotating coordinate system; Step 3: Based on the mathematical model in Step 2, obtain the standard state equation of the dual-winding induction motor and the control gain matrix. ; Step 4: Introduce a quasi-resonant controller and introduce a control gain matrix. A composite active disturbance rejection control extended state observer is constructed. Step 5: Based on the output of the composite active disturbance rejection control extended state observer, generate a control signal to drive the dual-winding induction motor.

2. The composite active disturbance rejection control method for a grid-connected inverter system based on a dual-winding induction motor according to claim 1, characterized in that, The expression for the voltage equation in step 2 is: The expression for the magnetic flux linkage equation is: In the formula, , Let dq be the rotor's d-axis current. , Given the dq-axis voltage of the rotor, the dual-winding induction motor is designed to be a squirrel-cage asynchronous motor. =0, =0; For stator resistance, For rotor resistance, , To control the dq axis flux linkage of the winding, , For the dq axis flux linkage of the grid-connected winding, , For the dq axis flux linkage of the rotor, e The synchronization angular frequency, The rotor angular frequency, For differential operators, For stator winding leakage inductance, For rotor winding leakage inductance, The leakage inductance between the two stator windings This refers to the mutual inductance between the stator winding and the rotor winding.

3. The composite active disturbance rejection control method for a grid-connected inverter system based on a dual-winding induction motor according to claim 1, characterized in that, The standard state equation of the dual-winding induction motor described in step 3 is expressed as follows: in, Here is the state variable gain matrix. It is a differential operator; The control gain matrix The expression is: In the formula, d To control the first gain, e The second gain is for control.

4. The composite active disturbance rejection control method for a grid-connected inverter system based on a dual-winding induction motor according to claim 1, characterized in that, The transfer function of the quasi-resonant controller described in step 4 The expression is: in, The resonant gain of the quasi-resonant controller, The resonant frequency of the quasi-resonant controller. For the bandwidth of the quasi-resonant controller, For the Laplace operator; The expression of the composite active disturbance rejection control extended state observer includes dynamic equation 1 and dynamic equation 2, wherein dynamic equation 1 is used to control the d-axis current of the winding and dynamic equation 2 is used to control the q-axis current of the winding. The expression for dynamic equation 1 is as follows: The expression for dynamic equation 2 is as follows: in, To control the estimated value of the d-axis current of the winding, To control the estimated value of the d-axis current disturbance of the winding, To control the estimated value of the winding q-axis current, To control the estimated value of the q-axis current disturbance of the winding. To control the actual value of the d-axis current of the winding and the estimated value of the d-axis current of the control winding The difference, To control the actual value of the winding q-axis current and the estimated value of the q-axis current of the control winding The difference, , , , They are respectively , , , The derivative of and These are the first and second gains of the composite active disturbance rejection control extended state observer, respectively. For the Laplace operator, For the control gain matrix The first line, For the control gain matrix The second line, =[d 0 e 0], =[0 d 0 e], d To control the first gain, e is The second gain of the control quantity.

5. The composite active disturbance rejection control method for a grid-connected inverter system based on a dual-winding induction motor according to claim 3 or 4, characterized in that, The first gain of the control quantity d Second gain of control quantity e The calculation formulas are as follows: In the formula, For stator winding leakage inductance, For rotor winding leakage inductance, The leakage inductance between the two stator windings This refers to the mutual inductance between the stator winding and the rotor winding.

6. The composite active disturbance rejection control method for a grid-connected inverter system based on a dual-winding induction motor according to claim 3, characterized in that, The state quantity gain matrix The expression is as follows: in, a,b,c These are the first gain, second gain, and third gain of the state variable, respectively, and their calculation formulas are as follows: In the formula, For stator winding leakage inductance, For rotor winding leakage inductance, The leakage inductance between the two stator windings For the mutual inductance between the stator winding and the rotor winding, e The synchronization angular frequency, For stator resistance, This represents the rotor resistance.

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