Continuous set multi-step model predictive control method for sliding mode active disturbance rejection permanent magnet synchronous motor

Abstract

The present invention relates to a continuous set multi-step model predictive control method for a sliding mode self-disturbance rejection permanent magnet synchronous motor. The method comprises the following steps: collecting the real-time value of the three-phase current and the real-time rotation speed of the motor through a sensor module, and obtaining the value of the current in a d-q rotating coordinate system through transformation; establishing a sliding mode speed controller based on an extended state observer, inputting the actual rotation speed and the q-axis current component into an extended state observer module, obtaining an estimated value of the total disturbance, and obtaining the desired q-axis current component through a sliding film speed controller module; establishing a continuous set multi-step model predictive current controller module, and using i d =0 control, and input the expected d-axis current component and the expected q-axis current component to obtain the expected value of the d-q-axis voltage component; the obtained expected value of the d-q-axis voltage component is transformed by inverse park to obtain the voltage component in the α-β stationary coordinate system, and the drive signal is obtained by modulation; while maintaining fast dynamic response, the speed tracking performance and strong robustness to interference are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of motors, and in particular to a continuous set multi-step model predictive control method for a sliding mode self-disturbance rejection permanent magnet synchronous motor. Background Art

[0002] Permanent magnet synchronous motor (PMSM) is widely used in aerospace, automobile, CNC machine tools, robotics and other fields due to its superior performance.

[0003] One of the most commonly used control schemes for permanent magnet synchronous motors (PMSMs) is a cascade structure called field-oriented control, in which both the inner and outer loop controllers are proportional-integral controllers. The inner loop controller regulates the current in the d–q rotating coordinate system, and the outer loop controller regulates the speed by providing the q-axis reference current to the inner loop. However, the permanent magnet synchronous motor is a nonlinear strongly coupled control system. System parameter mismatch and external interference are inevitable, which will reduce the performance of the control algorithm. It is difficult to quickly alleviate these interferences using traditional linear PI controllers, and there are problems such as slow dynamic response, easy overshoot, integral saturation, and coupling effects, which limits its current loop response capability.

[0004] Model predictive control (MPC), which is an optimization-based approach, obtains the applied current control by minimizing the difference between the predicted behavior of the system and its desired performance. This form of control behavior has long existed in process control and can usually use relatively large sampling times, so the quadratic programming (QP) problem that arises in the resulting algorithm can be solved online. There are two main types of predictive control applied in drive applications: deadbeat predictive control (MPC) and finite control set (FCS-MPC). FCS-MPC depends on determining the best voltage vector that minimizes a predefined cost index. This MPC approach produces good transient performance. However, this approach can produce high ripple in the torque and current waves. Continuous control set MPC (CCS-MPC), which combines the advantages of deadbeat MPC and FCS-MPC techniques, has been applied to permanent magnet synchronous motor (PMSM) control. CCS-MPC is based on voltage calculation and obtains the optimal reference voltage by minimizing the cost function of reference tracking. Summary of the invention

[0005] To solve the above problems, the present invention provides a sliding mode self-disturbance rejection permanent magnet synchronous motor continuous set multi-step model predictive control method, which enables the system to have fast dynamic response and excellent robustness, eliminates the influence of parameter mismatch and disturbance on the control system, and improves the dynamic response speed of the current loop.

[0006] The technical solution adopted by the present invention is: a sliding mode self-disturbance rejection permanent magnet synchronous motor continuous set multi-step model predictive control method, characterized in that it includes the following steps:

[0007] S1: The real-time value of the three-phase current of the motor is collected through the current sensor, and the value of the current in the dq rotating coordinate system is obtained through Clark and Park transformation;

[0008] S2: Get the rotor position and real-time speed of the motor through the photoelectric encoder;

[0009] S3: Establish a sliding mode speed controller SMSC based on an extended state observer, input the actual speed of the permanent magnet synchronous motor and the q-axis current component into the extended state observer, obtain an estimated value of the total disturbance, input the obtained total disturbance estimate and the desired speed and actual speed of the permanent magnet synchronous motor into the sliding mode speed controller, and obtain the desired q-axis current component;

[0010] S4: Establish a continuous set multi-step model predictive current controller using i d =0 control, and input the expected d-axis current component and the expected q-axis current component to obtain the expected values ​​of the dq-axis voltage components;

[0011] S5: The expected value of the dq axis voltage component obtained by the continuous set multi-step model predictive current controller is transformed into the voltage component in the α-β stationary coordinate system through inverse park transformation, and the driving pulse signal of the inverter is obtained through spatial voltage pulse width modulation.

[0012] Preferably, in step S3, the extended state observer is designed as follows to estimate the total disturbance f of the PMSM drive speed control loop online: td

[0013]

[0014] in: and They are ω e and f td The estimated value of β 01 and β 02 is the gain of the ESO, which converts the estimated disturbance The output is given to the sliding mode speed controller. The equation shows that the design of ESO only requires the nominal values ​​of PMSM parameters and is therefore robust to PMSM parameter variations;

[0015] The dynamic motion equation of the permanent magnet synchronous motor considering the changes in machine parameters and load torque is expressed as follows:

[0016]

[0017] in: The subscript "0" indicates the nominal parameter value, f id and f edThey represent the uncertain dynamics caused by the changes in machine parameters and external load torque, respectively, and are expressed as:

[0018] f ed =-(n p T L / J0), where: ΔJ=J-J0, ΔB=B-B0, Δψ f =ψ f -ψ f0

[0019] Let f td =f id +f ed is the total interference, x=[ω e , f td ] T The state vector u = [i a ,0] T is the control input vector; assuming f td It is constant in each sampling period, so the mathematical model can be rewritten in the following matrix form:

[0020]

[0021] in:

[0022] Preferably, in step S3, the control law of the sliding mode speed controller SMSC is designed as follows:

[0023]

[0024] Where: i qr is the q-axis current reference; sgn is the sign function; γ is a positive number that determines the decay rate of the rotor speed error; is the switching gain, which ensures stability and causes sliding motion on the sliding surface in a limited time;

[0025] The electromagnetic torque equation of the surface mounted permanent magnet synchronous motor is:

[0026]

[0027] Where T e is the electromagnetic torque i q represents the q-axis stator current, ψ f Represents the rotor flux; n p is the extreme logarithm;

[0028] The mechanical motion equation of the surface-mounted permanent magnet synchronous motor is:

[0029]

[0030] Where J is the moment of inertia; B is the viscous friction coefficient; ω m is the rotor mechanical angular velocity; T L is the load torque;

[0031] Define the rotor speed error e ω as follows:

[0032] e ω =ω e -ω er (7)

[0033] where ω er is the rotor speed reference;

[0034] Define the following sliding surface:

[0035] σ ω =e ω +c ω f ω (8)

[0036] If the bandwidth of the ESO is high enough compared to the time variation of the internal disturbance, then within each short sampling period, f td The change of is almost zero, that is, Define the total disturbance observation error

[0037] Define the following Lyapunov function:

[0038]

[0039] Where m is the compensation gain, designed as

[0040] Then, the derivative of V can be derived as follows:

[0041]

[0042] The asymptotic stability of the closed-loop speed control is thus proved, and finally, the proposed ESO-SMSC is obtained by combining them.

[0043] Preferably, in step S4, the specific steps of establishing the continuum multi-step model predictive current controller are:

[0044] The mathematical model of the permanent magnet synchronous motor dq axis is expressed as:

[0045]

[0046] where i d i q represents the dq axis stator current, u d u qrepresents the dq axis stator voltage, L d L q represents the stator inductance, R represents the stator resistance, ω e represents the rotor electrical angular velocity, ψ f represents the rotor flux;

[0047] The model is discretized and converted into state space equation form using the forward Euler method:

[0048]

[0049] in

[0050] Rewrite the model into incremental form:

[0051]

[0052] Among them, Δx(k)=x(k)-x(k-1), Δu(k)=u(k)-u(k-1), Δd(k)=d(k)-d(k-1).

[0053] Preferably, in step S4, a continuous set multi-step model predictive current controller is established, and its prediction equation is:

[0054] Define the p-step prediction output vector Y p (k+1|k) and m-step input vector ΔU(k):

[0055] The predicted output vector for the next P steps can be calculated using this equation:

[0056] Y p (k+1|k)=S x Δx(k)+Ty(k)+S d Δd(k)+S u ΔU(k) ​​(14)

[0057] in

[0058] The objective function is constructed by considering the system performance requirements and taking into account the output error and input action amplitude. The objective function is:

[0059]

[0060] Where T yj,i is the weight factor of the error of the jth output component at the prediction time i, T uj,i is the weight factor of the error of the jth control increment component at the prediction time i, r j(k+i) is the jth component of the given reference input, which is determined by the current reference value given by the speed loop;

[0061] The open-loop optimization problem can be described as:

[0062]

[0063] Solving this function yields:

[0064]

[0065] The final output voltage is:

[0066]

[0067] The beneficial effects achieved by the present invention are as follows: the real-time value of the three-phase current of the motor, the rotor position and the real-time speed of the motor are collected by sensors, and the value of the current in the dq rotating coordinate system is obtained by transformation; a sliding mode speed controller based on an extended state observer is established, the actual speed of the permanent magnet synchronous motor and the q-axis current component are input into the extended state observer, an estimated value of the total disturbance is obtained, and the desired q-axis current component is obtained through the sliding film speed controller; a continuous set multi-step model predictive current controller is established, and i d =0 control, and input the expected d-axis current component and the expected q-axis current component to obtain the expected value of the dq-axis voltage component; the obtained expected value of the dq-axis voltage component is transformed by inverse park to obtain the voltage component in the α-β stationary coordinate system, and the drive signal is obtained after modulation; while maintaining fast dynamic response, the speed tracking performance and strong robustness to interference are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 This is the block diagram of the permanent magnet synchronous motor control system;

[0069] Figure 2 It is the system flow chart;

[0070] Figure 3 It is the flow chart of speed loop;

[0071] Figure 4 This is the current loop flow chart. DETAILED DESCRIPTION

[0072] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0073] like Figure 1-4As shown, a sliding mode self-disturbance rejection permanent magnet synchronous motor continuous set multi-step model predictive control method of the present invention adopts an extended state observer module, a sliding mode speed controller module, a model predictive current controller module and a sensor module. The extended state observer module obtains an estimated value of the total disturbance by analyzing the actual speed and q-axis current component of the permanent magnet synchronous motor; the sliding film speed controller module obtains the expected q-axis current component by the total disturbance estimate and the expected speed and actual speed of the permanent magnet synchronous motor; the model predictive current controller module adopts i d =0 control, and input the expected d-axis current component and the expected q-axis current component to obtain the expected value of the dq-axis voltage component; the sensor module includes a current sensor, a photoelectric encoder, a temperature detection module, and a DC bus voltage detection module. The expected value of the dq-axis voltage component obtained by the continuous set multi-step model predictive current controller is obtained by inverse park transformation to obtain the voltage component in the α-β stationary coordinate system, and the driving pulse signal of the inverter is obtained by spatial voltage pulse width modulation.

[0074] The present invention collects the real-time value of the three-phase current of the motor, the rotor position and the real-time speed of the motor through a sensor module, and obtains the value of the current in the dq rotating coordinate system through transformation; establishes a sliding mode speed controller based on an extended state observer, inputs the actual speed and q-axis current component of the permanent magnet synchronous motor into the extended state observer module, obtains the estimated value of the total disturbance, and obtains the expected q-axis current component through a sliding film speed controller module; establishes a continuous set multi-step model prediction current controller module, adopts i d =0 control, and input the expected d-axis current component and the expected q-axis current component to obtain the expected value of the dq-axis voltage component; the obtained expected value of the dq-axis voltage component is transformed by inverse park to obtain the voltage component in the α-β stationary coordinate system, and the drive signal is obtained after modulation; while maintaining fast dynamic response, the speed tracking performance and strong robustness to interference are improved.

[0075] A sliding mode self-disturbance rejection permanent magnet synchronous motor continuous set multi-step model predictive control method of the present invention specifically comprises the following steps:

[0076] S1: The real-time value of the three-phase current of the motor is collected through the current sensor, and the value of the current in the dq rotating coordinate system is obtained through Clark and Park transformation;

[0077] S2: Get the rotor position and real-time speed of the motor through the photoelectric encoder;

[0078] S3: Establish a sliding mode speed controller SMSC based on an extended state observer, input the actual speed of the permanent magnet synchronous motor and the q-axis current component into the extended state observer, obtain an estimated value of the total disturbance, input the obtained total disturbance estimate and the desired speed and actual speed of the permanent magnet synchronous motor into the sliding mode speed controller, and obtain the desired q-axis current component;

[0079] The electromagnetic torque equation of the surface mounted permanent magnet synchronous motor is:

[0080]

[0081] Where T e is the electromagnetic torque, i q represents the q-axis stator current, ψ f Represents the rotor flux; n p is the extreme logarithm.

[0082] The mechanical motion equation of the surface-mounted permanent magnet synchronous motor can be written as

[0083]

[0084] Where J is the moment of inertia; B is the viscous friction coefficient; ω m is the rotor mechanical angular velocity; T L is the load torque

[0085] The FOC system of PMSM adopts id=0 control mode, and the following formula can be obtained

[0086]

[0087] where ω er is the rotor speed reference, c=(n p / J)

[0088] Define the rotor speed error e ω as follows:

[0089] e ω =ω e -ω er (4)

[0090] where ω e =n p ω m is the electron angular velocity

[0091] Define the following sliding surface:

[0092] σ ω =e ω +c ω ∫e ω (5)

[0093] In order to make σ ω To approach zero in a finite time, the following sliding mode conditions must be met:

[0094]

[0095] To meet the requirements, the control law of SMSC can be designed as follows:

[0096] i qr =-γσ ω -ηsgn(σ ω ) (7)

[0097] where i qr is the q-axis current reference; sgn is the sign function; γ is a positive number that determines the decay rate of the rotor speed error; η is the switching gain that ensures stability and causes sliding motion on the sliding surface in a finite time, and is defined as follows:

[0098]

[0099] in is the limit of the absolute value of the load torque, that is It can be proved that the sliding mode conditions are satisfied as follows:

[0100]

[0101] In order to design a suitable disturbance observer, the dynamic motion equation of the permanent magnet synchronous motor considering the changes in machine parameters and load torque is expressed as follows:

[0102]

[0103] in The subscript "0" indicates the nominal parameter value, f id and f ed They represent the uncertain dynamics caused by the changes in machine parameters and external load torque, respectively, and are expressed as:

[0104]

[0105] f ed =-(n p T L / J0)

[0106] Among them ΔJ=J-J0, ΔB=B-B0, Δψ f =ψ f -ψ f0

[0107] Let f td =f id +f ed is the total interference, x=[ωe ,f td ] T is the state vector is the control input vector; assuming f td is constant in each sampling period. Then, the mathematical model can be rewritten in the following matrix form:

[0108]

[0109] in

[0110] The extended state observer (ESO) is designed as follows to estimate the total disturbance f in the speed control loop of the PMSM drive online: td

[0111]

[0112] in and They are ω e and f td The estimated value of β 01 and β 02 is the gain of the ESO. The equation shows that the design of the ESO only requires the nominal values ​​of the PMSM parameters and is therefore robust to PMSM parameter variations.

[0113] Considering the estimated total disturbance, the control law of SMSC is designed as follows:

[0114]

[0115] where i qr is the q-axis current reference; sgn is the sign function; γ is a positive number that determines the decay rate of the rotor speed error; is the switching gain, which ensures stability and causes sliding motion on the sliding surface in a limited time;

[0116] If the bandwidth of the ESO is high enough compared to the time variation of the internal disturbance, then within each short sampling period, f td The change of is almost zero, that is, Define the total disturbance observation error

[0117] Define the following Lyapunov function:

[0118]

[0119] Where m is the compensation gain, designed as

[0120] Then, the derivative of V can be derived as follows:

[0121]

[0122] Thus, the asymptotic stability of the closed-loop speed control is proved, and finally, the proposed ESO-SMSC is obtained by combining;

[0123] S4: Establish a continuous set multi-step model predictive current controller using i d =0 control, and input the expected d-axis current component and the expected q-axis current component to obtain the expected values ​​of the dq-axis voltage components;

[0124] The mathematical model of the permanent magnet synchronous motor dq axis is expressed as:

[0125]

[0126] where i d i q represents the dq axis stator current, u d u q represents the dq axis stator voltage, L d L q represents the stator inductance, R represents the stator resistance, ω e represents the rotor electrical angular velocity, ψ f represents the rotor flux;

[0127] The model is discretized and converted into state space equation form using the forward Euler method:

[0128]

[0129] in

[0130] Taking the magnetic flux as the interference term, the state space equation model is rewritten into incremental form:

[0131]

[0132] Among them, Δx(k)=x(k)-x(k-1), Δu(k)=u(k)-u(k-1), Δd(k)=d(k)-d(k-1)

[0133] The p-step prediction output vector and the m-step input vector are defined as follows:

[0134]

[0135] The predicted output vector for the next P steps can be calculated using this equation:

[0136] Y p (k+1|k)=S x Δx(k)+Ty(k)+Sd Δd(k)+S u ΔU(k) ​​(19)

[0137] in

[0138] The objective function is constructed by considering the system performance requirements and taking into account the output error and input action amplitude. The objective function is:

[0139]

[0140] Where T yj,i is the weight factor of the jth output component error at the prediction time i, which is:

[0141] T y,i =diag(T y1,i T y2,i … T ync,i ) (twenty one)

[0142] nc is the number of output components

[0143] T uj,i is the weight factor of the jth control increment component error at the prediction time i, which is:

[0144] T u,i =diag(T u1,i T u2,i … T unu,i ) (twenty two)

[0145] nu is the number of input components

[0146] r j (k+i) is the jth lower component of the given reference input

[0147] The open-loop optimization problem can be described as:

[0148]

[0149] Solving this function yields:

[0150]

[0151] ΔN(k)=[I nu*nu 0 … 0] 1*m ΔU(k) ​​(25)

[0152] The final output voltage is:

[0153]

[0154] S5: The expected value of the dq axis voltage component obtained by the continuous set multi-step model predictive current controller is transformed into the voltage component in the α-β stationary coordinate system through inverse park transformation, and the driving pulse signal of the inverter is obtained through spatial voltage pulse width modulation.

[0155] It should be noted that the description of the above technical solutions is exemplary, and this specification can be embodied in different forms and should not be interpreted as being limited to the technical solutions set forth herein. On the contrary, providing these descriptions will make the disclosure of the present invention thorough and complete, and will fully convey the scope disclosed in this specification to those skilled in the art. In addition, the technical solutions of the present invention are limited only by the scope of the claims.

[0156] The shapes, sizes, ratios, angles, and numbers disclosed for describing various aspects of the present specification and claims are merely examples, and therefore, the present specification and claims are not limited to the details shown. In the following description, when the detailed description of the related known functions or configurations is determined to be unnecessarily obscuring the focus of the present specification and claims, the detailed description will be omitted.

[0157] In the case of using “including”, “having” and “comprising” described in the present specification, unless otherwise used, there may also be another part or other parts, and the terms used may generally be in the singular but may also represent the plural form.

[0158] It should be noted that although the terms "first", "second", "top", "bottom", "one side", "the other side", "one end", "the other end", etc. may appear and be used in this specification to describe various components, these components and parts should not be limited by these terms. These terms are only used to distinguish one component and part from another component and part. For example, without departing from the scope of this specification, the first component can be called the second component, and similarly, the second component can be called the first component. The components at the top and bottom can also be swapped or converted with each other under certain circumstances; the components at one end and the other end can have the same or different performances.

[0159] When describing a positional relationship, for example, when the positional sequence is described as "on ...", "above ...", "below ..." and "next", unless words or terms such as "just" or "directly" are used, situations where they are not in contact or in contact may also be included. If it is mentioned that a first element is "on" a second element, it does not mean that the first element must be above the second element in the figure. The upper and lower parts of the component will change according to the change of the angle and orientation of observation. Therefore, in the drawings or in the actual construction, if it is involved that the first element is "on" the second element, the situation where the first element is "below" the second element and the situation where the first element is "above" the second element may be included. When describing a temporal relationship, unless "just" or "directly" is used, when describing "after", "subsequently", "subsequently" and "before", situations where the steps are not continuous may be included. The features of various embodiments of the present invention may be partially or completely combined or spliced ​​with each other, and may be performed in various different configurations as can be fully understood by those skilled in the art. The embodiments of the present invention may be performed independently of each other, or may be performed together in a mutually dependent relationship.

[0160] Finally, it should be pointed out that the above embodiments are only representative examples of the present invention. Obviously, the present invention is not limited to the above embodiments, and there are many variations. Any simple modification, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention should be considered to belong to the protection scope of the present invention.

Claims

1. A sliding mode self-disturbance rejection permanent magnet synchronous motor continuous set multi-step model predictive control method, characterized by: The following steps are involved: S1: The real-time value of the three-phase current of the motor is collected through the current sensor, and the value of the current in the dq rotating coordinate system is obtained through Clark and Park transformation; S2: Get the rotor position and real-time speed of the motor through the photoelectric encoder; S3: Establish a sliding mode speed controller SMSC based on an extended state observer, input the actual speed of the permanent magnet synchronous motor and the q-axis current component into the extended state observer, obtain an estimated value of the total disturbance, input the obtained total disturbance estimate and the desired speed and actual speed of the permanent magnet synchronous motor into the sliding mode speed controller, and obtain the desired q-axis current component; S4: Establish a continuous set multi-step model predictive current controller using i d =0 control, and input the expected d-axis current component and the expected q-axis current component to obtain the expected values ​​of the dq-axis voltage components; S5: The expected value of the dq axis voltage component obtained by the continuous set multi-step model predictive current controller is transformed by inverse Park to obtain the voltage component in the α-β stationary coordinate system, and the driving pulse signal of the inverter is obtained by spatial voltage pulse width modulation; In step S3, the extended state observer is designed as follows to estimate the total disturbance f of the PMSM drive speed control loop online: td in: and They are ω e and f td The estimated value of β 01 and β 02 is the gain of the ESO, which converts the estimated disturbance The output is given to the sliding mode speed controller. The equation shows that the design of ESO only requires the nominal values ​​of PMSM parameters and is therefore robust to PMSM parameter variations; The dynamic motion equation of the permanent magnet synchronous motor considering the changes in machine parameters and load torque is expressed as follows: in: The subscript "0" indicates the nominal parameter value, f id and f ed They represent the uncertain dynamics caused by the changes in machine parameters and external load torque, respectively, and are expressed as: f ed =-(n p T L / J0), where: ΔJ=J-J0, ΔB=B-B0, Δψ f =ψ f -ψ f0 Let f td =f id +f ed is the total interference, x=[ω e , f td ] T The state vector u = [i q ,0] T is the control input vector; assuming f td It is constant in each sampling period, so the mathematical model can be rewritten in the following matrix form: in: In step S3, the sliding mode speed controller SMSC control law is designed as follows: Where: i qr is the q-axis current reference; sgn is the sign function; γ is a positive number that determines the decay rate of the rotor speed error; is the switching gain, which ensures stability and causes sliding motion on the sliding surface in a limited time; The electromagnetic torque equation of the surface mounted permanent magnet synchronous motor is: Where T e is the electromagnetic torque i q represents the q-axis stator current, ψ f Represents the rotor flux; n p is the extreme logarithm; The mechanical motion equation of the surface-mounted permanent magnet synchronous motor is: Where J is the moment of inertia; B is the viscous friction coefficient; ω m is the rotor mechanical angular velocity; T L is the load torque; Define the rotor speed error e ω as follows: e ω =ω e -oh er (7) where ω er is the rotor speed reference; Define the following sliding surface: s ω =e ω +c ω ∫e ω (8) If the bandwidth of the ESO is high enough compared to the time variation of the internal disturbance, then within each short sampling period, f td The change of is almost zero, that is, Define the total disturbance observation error Define the following Lyapunov function: Where m is the compensation gain, designed as Then, the derivative of V can be derived as follows: Thus, the asymptotic stability of the closed-loop speed control is proved, and finally, the proposed ESO-SMSC is obtained by combining; In step S4, the specific steps of establishing the continuum multi-step model predictive current controller are: The mathematical model of the permanent magnet synchronous motor dq axis is expressed as: where i d i q represents the dq axis stator current, u d u q represents the dq axis stator voltage, L d L q represents the stator inductance, R represents the stator resistance, ω e represents the rotor electrical angular velocity, ψ f represents the rotor flux; The model is discretized and converted into state space equation form using the forward Euler method: in Rewrite the model into incremental form: Among them, Δx(k)=x(k)-x(k-1), Δu(k)=u(k)-u(k-1), Δd(k)=d(k)-d(k-1).

2. The sliding mode auto-disturbance rejection permanent magnet synchronous motor continuous set multi-step model predictive control method according to claim 1, characterized in that: In step S4, a continuous set multi-step model predictive current controller is established, and its prediction equation is: Define the p-step prediction output vector Y p (k+1|k) and m-step input vector ΔU(k): The predicted output vector for the next P steps can be calculated using this equation: Y p (k+1|k)=S x Δx(k)+Ty(k)+S d Δd(k)+S u ΔU(k) ​​(14) in The objective function is constructed by considering the system performance requirements and taking into account the output error and input action amplitude. The objective function is: Where T yj，i is the weight factor of the error of the jth output component at the prediction time i, T uj，i is the weight factor of the error of the jth control increment component at the prediction time i, r j (k+i) is the jth component of the given reference input, which is determined by the current reference value given by the speed loop; The open-loop optimization problem can be described as: Solving this function yields: The final output voltage is:

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