A Method for Predictive Current Control Without Deadbeat and a Motor System for a Permanent Magnet Synchronous Motor

Abstract

The present invention relates to the field of motor control technology, specifically providing a permanent magnet synchronous motor deadbeat predictive current control method and motor system. A discrete mathematical model of the permanent magnet synchronous motor is constructed under the d-q axis of a synchronous rotating coordinate system, taking into account control system delay. Furthermore, parameter mismatch is considered, the disturbance introduced by the model is modeled, and an improved generalized extended state observer is constructed to obtain the observed value of the d-q axis disturbance. Real-time and accurate identification of inductance parameter changes is achieved through an inductance parameter identification method based on a model reference adaptive system. The inductance parameters in the controller and observer are dynamically corrected based on the lumped disturbance and inductance parameter identification results, thereby forming a robust deadbeat predictive current control method for the motor. The present invention effectively reduces current harmonics and greatly improves system robustness and control performance.

Description

Technical Field

[0001] The present invention belongs to the technical field of motor control, and in particular relates to a deadbeat predictive current control method for a permanent magnet synchronous motor and a motor system. Background Art

[0002] Permanent magnet synchronous motors (PMSMs) are widely used in servo drives due to their attractive advantages, including high power factor, high operating efficiency, and high power density. Among the numerous PMSM control strategies, deadbeat predictive current control (DPCC) has gained widespread adoption due to its advantages such as simple programming, low current harmonics, and fast dynamic response. However, achieving high transient and steady-state performance with DPCC depends on the accuracy of the model parameters. In practical systems, motor parameters can change due to temperature fluctuations and saturation effects, resulting in steady-state current errors and even system instability.

[0003] Therefore, there is an urgent need for a deadbeat predictive current control method that can ensure high dynamic performance of the system while enhancing its robustness. Summary of the Invention

[0004] In view of this, the present invention aims to provide a beat-free predictive current control method and motor system for a permanent magnet synchronous motor. In the current prediction process, the disturbance problem introduced by parameter changes is taken into account, an improved generalized extended state observer (Improved Generalized Extended State Observer) is designed, and a model reference adaptive system is used to perform online identification of inductance parameters, thereby realizing real-time updating of the controller and the improved generalized extended state observer, effectively suppressing the problem of current harmonic increase in the case of parameter mismatch, and having excellent robustness and control performance.

[0005] To achieve the above object, the technical solution created by the present invention is implemented as follows:

[0006] The present invention provides a method for controlling a deadbeat predictive current of a permanent magnet synchronous motor, comprising:

[0007] S1: Construct a discrete mathematical model of the permanent magnet synchronous motor considering the control system delay as follows:

[0008] ;

[0009] in, represents the dq axis current at time k+1, , represents the sampling period, , represents the stator resistance, Indicates the d-axis or q-axis inductance, , represents the electrical angular velocity of the motor at time k, , represents the d-axis stator current at time k, represents the q-axis stator current at time k, , represents the dq axis reference voltage at time k-1, , represents the permanent magnet flux at time k;

[0010] S2: The disturbances caused by the changes in the d- and q-axis parameters are modeled as lumped disturbances. An improved generalized extended state observer is designed and used to observe the lumped disturbances of the motor system. The improved generalized extended state observer is:

[0011] ;

[0012] in, represents the predicted dq axis current at time k, represents the predicted dq axis current at time k+1, , Indicates the inductance identification value, Indicates the nominal value of resistance, , , represents the d-axis voltage at time k-1, represents the q-axis voltage at time k-1, represents the back electromotive force at time k, represents the lumped perturbation observation value of the dq axis caused by parameter changes at time k, , , represents the cutoff frequency, 、 、 and are gain coefficients, Represents the second extended state variable The observed value of , Indicates the third extended state variable The observed value of ;

[0013] S3: Online identification of motor inductance using a model reference adaptive system;

[0014] S4: The aggregate disturbance observation value observed by S2 As the feedforward compensation, the inductance identification value obtained by S3 identification is used to dynamically modify the inductance of the improved generalized extended state observer and the motor system controller, generating the deadbeat predictive current control law as follows:

[0015] ;

[0016] represents the dq axis reference voltage at time k, Indicates the given current of dq axis at time k

[0017] Preferably, in S1, the process of establishing the discrete mathematical model of the permanent magnet synchronous motor considering the control system delay is:

[0018] The stator current equation of the permanent magnet synchronous motor is established as:

[0019] ;

[0020] Where t represents time, represents the d-axis stator current, represents the q-axis stator current, represents the d-axis stator voltage, represents the q-axis stator voltage, represents the d-axis inductance, represents the q-axis inductance, , represents the rotor electrical angular velocity, represents the permanent magnet flux;

[0021] The stator current equation of the permanent magnet synchronous motor is discretized as:

[0022] ;

[0023] And the dq axis stator current at time k+2 Track the reference current at time k , a discrete mathematical model of the permanent magnet synchronous motor considering the control system delay is constructed.

[0024] Preferably, the parameter changes include: resistance changes, inductance changes and flux changes.

[0025] Preferably, the model reference adaptive system designs the inductance adaptive law based on Popov stability theorem.

[0026] Preferably, the inductance adaptive law is a proportional-integral structure.

[0027] Preferably, the inductance adaptive law is:

[0028] ;

[0029] in, Indicates the d-axis adjustable current, Indicates the q-axis adjustable current, represents the proportional gain of the PI controller, Represents the integral gain of the PI controller.

[0030] Preferably, in S3, the process of identifying the motor inductance using the model reference adaptive system includes:

[0031] Constructing an adjustable model:

[0032] ;

[0033] in, , , is the state matrix, is the inductance identification value;

[0034] The stator current equation of the permanent magnet synchronous motor is used as a reference model, and the reference model is subtracted from the adjustable model to obtain an error equation; the state equation of the motor's feedback system is constructed based on the error equation, and the inductance adaptive law is designed based on the state equation of the feedback system.

[0035] Preferably, in S3, , , , ,in, represents the bandwidth of the improved generalized extended state observer.

[0036] Another aspect of the present invention provides a deadbeat predictive current control method using a permanent magnet synchronous motor.

[0037] Compared with the prior art, the present invention can achieve the following beneficial effects:

[0038] This invention significantly improves the system's dynamic response through delayed predictive compensation control and an improved generalized extended state observer (IGESO). Parameter mismatch is considered during the IGESO construction process. IGESO employs multi-order disturbance observation, resulting in superior interference and noise immunity, effectively mitigating the impact of changes in resistance, inductance, flux linkage, and other parameters on system performance. Furthermore, a model-referenced adaptive system is used for online identification of inductor parameters, enabling real-time updates of the inductor parameters of the controller and improved generalized extended state observer. This significantly suppresses current harmonics even when the inductor parameters change suddenly.

[0039] The improved generalized extended state observer of the present invention shows significant advantages in both interference suppression and noise suppression. It has stronger interference estimation capability in the low-frequency band and can compensate for system disturbances more accurately. The noise suppression capability in the high-frequency band is also significantly enhanced, effectively avoiding the observer's sensitivity to high-frequency noise. Compared with the traditional generalized extended state observer, it can still maintain excellent observation performance under complex working conditions, laying a solid foundation for improving system robustness and control accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings, which constitute part of the present invention, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0041] Figure 1 1 is a block diagram of a motor system structure based on a deadbeat predictive current control method for a permanent magnet synchronous motor provided by an embodiment of the present invention;

[0042] Figure 2 is a flow chart of a deadbeat predictive current control method for a permanent magnet synchronous motor provided by an embodiment of the present invention;

[0043] Figure 3 This is a schematic diagram of a system control timing principle according to an embodiment of the present invention;

[0044] Figure 4 is a logarithmic amplitude-frequency characteristic curve diagram of the interference suppression transfer function provided by an embodiment of the present invention;

[0045] Figure 5 is a logarithmic amplitude-frequency characteristic curve diagram of a noise suppression transfer function provided by an embodiment of the present invention;

[0046] Figure 6 2. FIG is a diagram of an inductance identification result based on a model reference adaptive system provided in an embodiment of the present invention;

[0047] Figure 7 is a comparative simulation result diagram of different control algorithms under resistance mismatch provided by an embodiment of the present invention;

[0048] Figure 8 2 is a diagram showing comparative simulation results of different control algorithms under flux mismatch according to an embodiment of the present invention;

[0049] Figure 9 This is the simulation result of inductor mismatch under the deadbeat predictive current control strategy of the extended state observer;

[0050] Figure 10 This is the simulation result of inductor mismatch under the deadbeat predictive current control strategy based on the generalized extended state observer;

[0051] Figure 11 This is the simulation result of inductance mismatch under the permanent magnet synchronous motor zero-beat predictive current control strategy. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not constitute a limitation to the present invention. Similar elements in different embodiments use associated similar element numbers. In the following embodiments, many detailed descriptions are intended to enable the present invention to be better understood. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, or methods. In some cases, some operations related to the present invention are not shown or described in the specification. This is to avoid the core part of the present invention being overwhelmed by too much description. For those skilled in the art, it is not necessary to describe these related operations in detail. They can fully understand the related operations based on the description in the specification and the general technical knowledge in the art.

[0053] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other to form various implementation methods. At the same time, the steps or actions in the method description can also be interchanged or adjusted in a manner that is obvious to those skilled in the art. Therefore, the various orders in the description and the drawings are only for the purpose of clearly describing a certain embodiment and are not intended to be a required order, unless otherwise specified that a certain order must be followed.

[0054] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, features defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0055] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to internal connections between two components. Those skilled in the art can understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0056] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments.

[0057] In one embodiment of the present invention, a deadbeat predictive current control method for a permanent magnet synchronous motor (Proposed RDPCC, RDPCC) is provided, which is specifically applied to the following: Figure 1 In the motor system shown in the figure, PI is a proportional-integral controller, SVPWM is a space vector pulse width modulation, PMSM is a permanent magnet synchronous motor, and Position and Speed detection is a position and speed detection module.

[0058] The specific current control process is as follows:

[0059] S1: First, establish the stator current equation of the permanent magnet synchronous motor in the synchronous rotating coordinate system (dq axis). The equation expression is:

[0060] (1)

[0061] Where t represents time, represents the d-axis stator current, represents the q-axis stator current, represents the d-axis stator voltage, represents the q-axis stator voltage, represents the d-axis inductance, It represents the q-axis inductance, which exists for surface-mounted permanent magnet synchronous motors: , represents the rotor electrical angular velocity, represents the permanent magnet flux, represents the stator resistance, represents the motor electrical angular velocity, Indicates the motor mechanical angular velocity.

[0062] Due to the sampling period It is small enough, so the forward Euler method is used to discretize the stator current equation of the permanent magnet synchronous motor expressed in formula (1), and the discretized mathematical model of the permanent magnet synchronous motor without considering the control system delay is obtained:

[0063] (2)

[0064] in, ,Right now , represents the dq axis current at time k in the discrete mathematical model of the permanent magnet synchronous motor without considering the control system delay, represents the d-axis stator current at time k, represents the q-axis stator current at time k, , , , , ,Right now , represents the d-axis stator voltage, represents the q-axis stator voltage, represents the dq axis reference voltage at time k, , represents the permanent magnet flux at time k.

[0065] like Figure 3As shown in the figure, in digital control systems, digital signal processors (DSPs) undertake important tasks such as control decision-making, signal processing, and pulse-width modulation (PWM) signal generation. In the figure, "Current sampling" represents current sampling, "PWM duty update" represents duty cycle update, "Voltage calculation" represents voltage calculation, and "Voltage reference update" represents voltage reference update. Because A / D conversion and control algorithm calculations consume the majority of the time, PWM duty cycle updates can only be completed within the next control cycle. This results in a one-step delay in the execution of deadbeat predictive current control. This time delay in the control signal slows the system's response to current changes and makes it unable to quickly keep up with changes in the given current, thus affecting the system's dynamic response performance. Furthermore, under conditions such as rapidly changing loads, this delay can cause system instability and lead to current oscillations.

[0066] Since the control period is extremely small, it is usually considered that there is , so let the current at time k+2 be Track the given current at time k , so we can deduce that:

[0067] (3)

[0068] On this basis, the discrete mathematical model of the permanent magnet synchronous motor represented by Equation (2) can be rewritten as follows considering the system time delay:

[0069] (4)

[0070] in, and Represents the dq axis current in the motor model obtained by rewriting formula (2), is the dq axis reference voltage at time k-1. The discrete mathematical model of the permanent magnet synchronous motor considering the control system delay expressed by formula (4) is used as the motor model for subsequent control, that is, the dq axis currents designed subsequently are all in formula (4). .

[0071] For the traditional deadbeat predictive current control strategy, the predicted current control rate is usually constructed as:

[0072] (5)

[0073] in, represents the dq axis reference voltage at time k, Indicates the given current of dq axis at time k.

[0074] In summary, if the control voltage generated at time k is applied to the PMSM, the actual current will track the set current after two cycles, provided the model parameters are accurate. However, in actual control systems, motor parameters vary with temperature, causing a deviation between the actual motor current and the set current.

[0075] S2: Traditional observers have deficiencies in interference suppression and noise suppression and cannot meet the high-precision observation requirements under complex working conditions. Therefore, in order to accurately observe the disturbances caused by parameter perturbations and other factors, improve the system's ability to suppress disturbances and enhance noise resistance, it is necessary to design and construct an improved generalized extended state observer (IGESO) to observe the disturbances caused by parameter perturbations.

[0076] The total perturbation of the d-axis and q-axis is defined as: ;in, represents the d-axis perturbation, Represents the q-axis disturbance. Based on the discrete mathematical model of the permanent magnet synchronous motor considering the system time delay (4), three additional state variables are considered and the disturbance caused by the change of the d- and q-axis parameters is modeled as a lumped disturbance. The discrete mathematical model of the permanent magnet synchronous motor considering the control system delay can be rewritten as:

[0077] (6)

[0078] in, , , , and for and The parameters are matrices of nominal parameters. is the second extended state variable, is the third extended state variable, for The difference.

[0079] According to formula (6), the improved generalized extended state observer is designed as follows:

[0080] (7)

[0081] in, It represents the predicted current of dq axis at time k, which realizes the motor delay compensation. represents the predicted dq axis current at time k+1, , Indicates the inductance identification value, Indicates the nominal value of resistance, , , represents the d-axis voltage at time k-1, represents the q-axis voltage at time k-1, represents the back electromotive force at time k, It represents the lumped disturbance observation value of the dq axis caused by the parameter change at time k, that is, the first extended state variable, Represents the second extended state variable The observed value of Indicates the third extended state variable The observed value of , represents the cutoff frequency, 、 、 and are all gain coefficients. In order to improve the noise resistance of the observer, the above gain coefficients are preferably: 、 、 and , represents the bandwidth of the designed improved generalized extended state observer, , , .

[0082] S3: To address the model mismatch problem caused by changes in inductance parameters due to temperature, magnetic saturation, etc. in permanent magnet synchronous motor control, an embodiment of the present invention proposes an online identification method based on a model reference adaptive system (Inductance Identification Based on MRAS). By dynamically adjusting adjustable model parameters, the motor inductance is identified online, significantly reducing the system's dependence on inductance changes.

[0083] definition For the dq axis adjustable current, the adjustable model designed based on the model reference adaptive system (AdaptiveModel) is:

[0084] (8)

[0085] in, , , , is the state matrix, is the inductance identification value.

[0086] Taking the stator current equation (1) of the permanent magnet synchronous motor as the reference model, the reference model equation (1) is subtracted from the adjustable model equation (8) to obtain the error equation:

[0087] (9)

[0088] in, for The derivative of , , and They represent the differences between the actual parameters and the identified parameters respectively.

[0089] definition , then formula (9) can be rewritten as:

[0090] (10)

[0091] The state equation of the motor feedback system constructed by the error equation (9) is:

[0092] (11)

[0093] in, represents the output variable, is a constant matrix. To make the linear steady-state model strictly positive real, take , is the identity matrix.

[0094] For a strictly positive definite matrix , s is a complex variable in the frequency domain. According to the stability theorem of the Popov Adaptation Algorithm, in order to keep the feedback system stable, the following conditions must be met:

[0095] (12)

[0096] in, is a finite positive real number that does not depend on t; represents the output of the nonlinear feedback system; represents the input of the linear time-invariant system.

[0097] Expanding the stability condition (12) yields:

[0098] (13)

[0099] in, express The transpose of .

[0100] Furthermore, we define three finite positive real numbers 、 、 , then we can process Equation (13) into blocks and get:

[0101] (14)

[0102] in, 、 and Represent three arbitrary discrete times.

[0103] Since the adaptive law is usually designed as a proportional-integral structure, the inductor adaptive law can be designed based on equation (14):

[0104] (15)

[0105] in, Indicates the d-axis adjustable current, Indicates the q-axis adjustable current, represents the proportional gain of the PI controller, It represents the integral gain of the PI controller, which determines the convergence speed and steady-state accuracy.

[0106] The above parameter identification method achieves high-precision dynamic tracking of the inductor by converting the parameter identification problem into a stability problem, significantly improving the control performance of the system under parameter mismatch.

[0107] S4: After obtaining the aggregated disturbance observation value and inductance identification value Then, the lumped disturbance observation value observed in step S2 is As the feedforward compensation, the inductance identification value obtained in step S3 is used. Dynamically correct the inductance of the improved generalized extended state observer and motor system controller, that is, use the inductance identification value By replacing the inductance parameters in the improved generalized extended state observer and the motor system controller, the final deadbeat predictive current control law is:

[0108] (16)

[0109] In order to verify the effectiveness of the improved generalized extended state observer provided by the embodiment of the present invention in interference suppression and noise suppression, the following Figure 4 and Figure 5The logarithmic amplitude-frequency characteristics of the extended state observer (ESO), generalized extended state observer (GESO), and improved generalized extended state observer (IGESO) for interference and noise suppression are shown, respectively. The abscissa represents frequency (rad / s), and the ordinate represents resonant amplitude (magnitude) (dB). As can be seen from the figure, compared with the traditional ESO, the ESO improves its interference estimation capability in the low-frequency band, but its noise suppression capability is weakened, which to some extent limits its application in practical systems. In contrast, the improved GESO designed and provided by the embodiments of the present invention demonstrates significant advantages in both interference and noise suppression. On the one hand, it has stronger interference estimation capability in the low-frequency band, enabling more accurate compensation for system disturbances; on the other hand, its noise suppression capability is significantly enhanced in the high-frequency band, effectively avoiding the observer's sensitivity to high-frequency noise. The improved GESO can maintain excellent observation performance even under complex operating conditions, laying a solid foundation for improving system robustness and control accuracy.

[0110] To verify the effectiveness and advancement of the solution proposed in the embodiment of the present invention, a simulation comparison was conducted on MATLAB / Simulink for the robust deadbeat predictive current control method proposed in the embodiment of the present invention, the deadbeat predictive current control method based on the extended state observer, and the deadbeat predictive current control method based on the generalized extended state observer. The comparison results are as follows:

[0111] like Figure 6 Figure 2 shows the deadbeat predictive current control method of the present invention. The dashed line, Indutance reference, represents the inductance reference value, and the solid line, Indutance identification, represents the inductance identification value. The horizontal axis represents time (in seconds), and the vertical axis represents the inductance identification value (in millihenries (mH). The inductance identification results are shown at a speed of 400 rpm, with a 4 N·m load added at 0.14 s. As can be seen from the figure, the IGESO estimate quickly converges to the true value in less than 0.02 s, with an inductance identification accuracy of approximately 0.38%. Furthermore, the sudden addition of a load at 0.14 s does not significantly affect the identification performance, demonstrating the rapid response and robustness of the model reference adaptive system in parameter estimation applications.

[0112] like Figure 7 As shown in the figure, the deadbeat predictive current control method based on extended state observer (DPCC-ESO) is 30% Mismatch and 80% Simulation results under mismatch conditions. Figure 8 As shown in the figure, the deadbeat predictive current control method based on the improved generalized extended state observer (DPCC-IGESO) is 30% Mismatch and 80% Simulation results under mismatch conditions. The results show that the impact of resistance mismatch on system performance is minimal and almost negligible. However, when using a deadbeat predictive current control strategy based on an extended state observer, flux mismatch can produce significant steady-state errors in the q-axis current. In contrast, the proposed DPCC-IGESO has stronger interference estimation capabilities, effectively mitigating error fluctuations caused by flux mismatch and keeping the steady-state error of the q-axis current within a small range.

[0113] Figure 9 、 Figure 10 as well as Figure 11 Comparative simulation results for three control strategies (deadbeat predictive current control based on an extended state observer, a deadbeat predictive current control based on a generalized extended state observer, and a robust deadbeat predictive current control strategy) are presented at 400 rpm under rated load conditions, with the inductance decreasing from 100% to 60% of the rated value in 0.4 s. The results show that while the deadbeat predictive current control strategy based on the extended state observer mitigates the impact of inductor mismatch to some extent, it produces significant current ripple, with a total harmonic distortion (THD) reaching 12.14%. In contrast, the deadbeat predictive current control strategy based on the improved generalized extended state observer exhibits improved noise immunity and effectively reduces current ripple. With matched inductors, the THD is 2.24%, while with a 60% inductor mismatch, the THD is reduced to 9.23%. Notably, the proposed DPCC-IGESO achieves superior performance through real-time inductance estimation and compensation, significantly suppressing current fluctuations caused by inductor mismatch. Under the condition of 60% inductor mismatch, the robust deadbeat predictive current control strategy can reduce the total harmonic distortion to 2.36%, which is almost equivalent to the performance under ideal inductor conditions.

[0114] In short, the above description is only a preferred embodiment of this specification and is not intended to limit the scope of protection of this specification. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this specification shall be included in the scope of protection of this specification.

[0115] The systems, devices, modules, or units described in one or more of the above embodiments may be implemented by a computer chip or entity, or by a product having a certain function. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0116] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0117] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

[0118] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A deadbeat predictive current control method for a permanent magnet synchronous motor, characterized in that: include: S1: Construct a discrete mathematical model of the permanent magnet synchronous motor considering the control system delay as follows: ； in, represents the dq axis current at time k+1, , represents the sampling period, , represents the stator resistance, Indicates the d-axis or q-axis inductance, , represents the electrical angular velocity of the motor at time k, , represents the d-axis stator current at time k, represents the q-axis stator current at time k, , represents the dq axis reference voltage at time k-1, , represents the permanent magnet flux at time k; S2: Model the disturbance caused by the change of the d-axis and q-axis parameters as a lumped disturbance, design an improved generalized extended state observer, and use the improved generalized extended state observer to observe the lumped disturbance of the motor system; wherein the improved generalized extended state observer is: ； in, represents the predicted dq axis current at time k, represents the predicted dq axis current at time k+1, , Indicates the inductance identification value, Indicates the nominal value of resistance, , , represents the d-axis voltage at time k-1, represents the q-axis voltage at time k-1, represents the back electromotive force at time k, represents the lumped perturbation observation value of the dq axis caused by parameter changes at time k, , , represents the cutoff frequency, 、 、 and are gain coefficients, The second extended state variable Observed values , Indicates the third extended state variable The observed value of ; S3: Online identification of motor inductance using a model reference adaptive system; S4: The aggregate disturbance observation value observed by S2 As a feedforward compensation, the inductance identification value obtained by the S3 identification is used to dynamically correct the inductance of the improved generalized extended state observer and the motor system controller, and the deadbeat predictive current control law is generated as follows: ； represents the reference voltage of the dq axis at time k, Indicates the given current of dq axis at time k.

2. The deadbeat predictive current control method for a permanent magnet synchronous motor according to claim 1, characterized in that: In S1, the process of establishing the discrete mathematical model of the permanent magnet synchronous motor considering the control system delay is as follows: The stator current equation of the permanent magnet synchronous motor is established as: ； Where t represents time, represents the d-axis stator current, represents the q-axis stator current, represents the d-axis stator voltage, represents the q-axis stator voltage, represents the d-axis inductance, represents the q-axis inductance, , represents the rotor electrical angular velocity, represents the permanent magnet flux; The stator current equation of the permanent magnet synchronous motor is discretized as: ； And the dq axis stator current at time k+2 Track the reference current at time k , construct and obtain the discrete mathematical model of the permanent magnet synchronous motor considering the control system delay.

3. The deadbeat predictive current control method for a permanent magnet synchronous motor according to claim 1, wherein: The parameter changes include resistance changes, inductance changes and flux changes.

4. The deadbeat predictive current control method for a permanent magnet synchronous motor according to claim 2, characterized in that: The model reference adaptive system designs the inductance adaptive law based on Popov stability theorem.

5. The deadbeat predictive current control method for a permanent magnet synchronous motor according to claim 4, characterized in that: The inductance adaptive law is a proportional-integral structure.

6. The method for controlling the deadbeat predictive current of a permanent magnet synchronous motor according to claim 5, wherein: The inductance adaptive law is: ； in, Indicates the d-axis adjustable current, Indicates the q-axis adjustable current, represents the proportional gain of the PI controller, Represents the integral gain of the PI controller.

7. The method for controlling the deadbeat predictive current of a permanent magnet synchronous motor according to claim 6, wherein: In S3, the process of identifying the motor inductance using the model reference adaptive system includes: Constructing an adjustable model: ； in, , , represents the state matrix, Indicates the inductance identification value; The stator current equation of the permanent magnet synchronous motor is used as a reference model, and the reference model is subtracted from the adjustable model to obtain an error equation; the state equation of the motor's feedback system is constructed based on the error equation, and the inductance adaptive law is designed based on the state equation of the feedback system.

8. The deadbeat predictive current control method for a permanent magnet synchronous motor according to claim 1, wherein: In the S3, , , , ,in, represents the bandwidth of the improved generalized extended state observer.

9. A motor system, characterized in that: A deadbeat predictive current control method for a permanent magnet synchronous motor as described in any one of claims 1 to 8 is adopted.

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