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CN114614713B - Model predictive speed control method for permanent magnet synchronous motor based on additive state decomposition - Google Patents

Model predictive speed control method for permanent magnet synchronous motor based on additive state decomposition Download PDF

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CN114614713B
CN114614713B CN202210337390.6A CN202210337390A CN114614713B CN 114614713 B CN114614713 B CN 114614713B CN 202210337390 A CN202210337390 A CN 202210337390A CN 114614713 B CN114614713 B CN 114614713B
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speed
control
permanent magnet
main system
state
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CN114614713A (en
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程善美
姜福喜
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Huazhong University of Science and Technology
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/13—Observer control, e.g. using Luenberger observers or Kalman filters
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P21/00—Arrangements or methods for the control of electric machines by vector control, e.g. by control of field orientation
    • H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
    • H02P21/18—Estimation of position or speed
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P25/00—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details
    • H02P25/02—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details characterised by the kind of motor
    • H02P25/022—Synchronous motors
    • H02P25/024—Synchronous motors controlled by supply frequency

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Control Of Electric Motors In General (AREA)
  • Control Of Ac Motors In General (AREA)

Abstract

本发明公开了一种基于加性状态分解的永磁同步电机模型预测速度控制方法，包括建立dq同步旋转坐标系下表贴式永磁同步电机的数学模型；利用加性状态分解技术，将速度子系统等效分解为标称主系统和包含不确定性的辅系统；针对主系统，设计指数收敛型模型预测控制器，使得主系统输出对给定参考转速的跟踪误差以指数形式渐近收敛至0附近；针对辅系统，设计广义比例积分观测器在线估计速度子系统的总扰动，在此基础上，设计基于扰动主动补偿的状态反馈控制律，抑制扰动对辅系统输出的影响；对主系统和辅系统的控制输入进行融合，得到速度环复合控制律。本发明控制方法结构简单，易于实现，灵活性和控制精度高。

The present invention discloses a permanent magnet synchronous motor model prediction speed control method based on additive state decomposition, including establishing a mathematical model of a surface-mounted permanent magnet synchronous motor in a dq synchronous rotating coordinate system; using additive state decomposition technology, the speed subsystem is equivalently decomposed into a nominal main system and an auxiliary system containing uncertainty; for the main system, an exponential convergence model prediction controller is designed so that the tracking error of the main system output to a given reference speed converges asymptotically to near 0 in an exponential form; for the auxiliary system, a generalized proportional integral observer is designed to estimate the total disturbance of the speed subsystem online, and on this basis, a state feedback control law based on active disturbance compensation is designed to suppress the influence of the disturbance on the auxiliary system output; the control inputs of the main system and the auxiliary system are fused to obtain a speed loop composite control law. The control method of the present invention has a simple structure, is easy to implement, and has high flexibility and control accuracy.

Description

Permanent magnet synchronous motor model prediction speed control method based on additive state decomposition
Technical Field
The invention belongs to the field of motor control, and in particular relates to a permanent magnet synchronous motor model predictive speed control method based on additive state decomposition.
Background
The permanent magnet synchronous motor (PERMANENT MAGNET synchronous motor, PMSM) has the characteristics of simple structure, high power density, reliable operation and the like, and is widely applied to the fields of aerospace, electric automobiles, numerical control machine tools, robot control and the like. The PMSM speed regulation system in practical application is inevitably influenced by uncertain factors such as unmodeled dynamics, parameter perturbation, external load disturbance and the like, and satisfactory control precision is difficult to achieve by adopting conventional PID control. Therefore, the research designs an advanced control method to effectively inhibit the internal and external interference in the PMSM speed regulation system, and the realization of high-precision control of the advanced control method has important scientific significance and application value.
With the continuous development of control theory, various novel nonlinear control technologies are sequentially proposed and applied to a PMSM speed regulation system, such as sliding mode control, self-adaptive control, H ∞ robust control and the like. However, the above methods have certain disadvantages, for example, the suppression of disturbance and external disturbance of system parameters by the conventional sliding mode control is at the cost of generating high-frequency buffeting, which may excite the unmodeled characteristics of the system, so that the performance of the PMSM system is greatly compromised. The method reduces the sensitivity of disturbance in the output channel of the system by improving the robustness of the controller, and has the problems of compromise between nominal performance and robustness, tracking control and disturbance suppression performance.
Model predictive control (Model predictive control, MPC) was born in the 70 s of the last century as an optimization control theory, when the MPC is applied to a PMSM speed regulation system, the MPC directly takes the rotating speed as a control target to be added into a cost function, predicts the rotating speed at the next moment according to a mechanical motion equation of a motor, and obtains the optimal control quantity by minimizing the cost function. MPC has faster dynamic performance, but this approach cannot directly cope with external load disturbances and is more sensitive to model uncertainty. In addition, the MPC calculation amount increases exponentially with the increase of the prediction step, and the application of the MPC calculation amount in a PMSM speed regulation system is limited by the excessive calculation amount.
Disclosure of Invention
Aiming at the defects or improvement demands of the prior art, the invention provides a permanent magnet synchronous motor model prediction speed control method based on an additive state decomposition (ADDITIVE STATE d) technology, which is used for decomposing the speed tracking problem of a disturbed PMSM into the tracking control problem of a nominal main system and the disturbance suppression problem of an uncertain auxiliary system. And respectively designing a model prediction controller and a state feedback controller based on disturbance estimation and compensation aiming at a main system and an auxiliary system with independent control tasks, and fusing the controllers to obtain a final speed loop composite control law, so that the PMSM still has higher rotating speed tracking precision under the conditions of parameter perturbation, unmodeled dynamic and external load interference.
In order to achieve the above object, according to one aspect of the present invention, there is provided a permanent magnet synchronous motor model predictive speed control method based on additive state decomposition, including:
S1, establishing a mathematical model of a surface-mounted PMSM under a dq synchronous rotation coordinate system;
S2, equivalently decomposing the speed subsystem into a nominal main system and an auxiliary system containing uncertainty by using an additive state decomposition technology;
s3, designing an exponential convergence type model prediction controller aiming at the main system, so that the tracking error of the main system output to the given reference rotating speed gradually converges to be near 0 in an exponential form;
S4, aiming at an auxiliary system, designing a generalized proportional integral observer (Generalized proportional integral observer, GPIO) to estimate the total disturbance of the speed subsystem on line, and on the basis, designing a state feedback control law based on disturbance active compensation to inhibit the influence of disturbance on the output of the auxiliary system;
s5, fusing control inputs of the main system and the auxiliary system to obtain a speed loop composite control law.
The surface-mounted PMSM mathematical model in step S1 is built as follows:
Wherein R and L are stator resistance and stator inductance, p is the pole pair number of the motor, J is the rotor moment of inertia, B is the viscous damping coefficient, ψ f is the rotor permanent magnet flux linkage, i d and i q are the d and q axis currents, u d and u q are the d and q axis voltages, ω is the rotor angular velocity, ω e =pω is the rotor electrical angular velocity, and T L is the load torque.
The decomposition of the speed subsystem in step S2 comprises the sub-steps of:
S201, dividing a speed subsystem into a main system and an auxiliary system according to an additive state decomposition idea, so as to simplify the control problem; the main system (nominal system) is noted as:
Wherein ω p is the main system state and i qp is the main system control input; the main system control targets are: designing i qp such that when time t→infinity, ω p-ωr →0, where ω r is a given reference input speed;
s202, defining:
Wherein i qr is a speed loop composite control law, omega s and i qs are respectively used as the state and control input of an auxiliary system, and an auxiliary system state equation is established:
Order the The above auxiliary system is further noted as:
the control targets of the auxiliary system are as follows: i qs is designed such that when time t→infinity, ω s →0.
Preferably, the design of the exponential convergence model predictive controller of the host system in step S3 comprises the sub-steps of:
s301, setting a speed ring discrete period as T s, and discretizing a main system by using a forward Euler method to obtain the following steps:
ωp(k+1)＝ωp(k)+Tsbiqp(k)；
Defining a main system speed tracking error:
the first order derivative is obtained and then discretized by a forward Euler method to obtain:
assume that e p converges exponentially to 0, i.e
Wherein the method comprises the steps ofFor the exponential convergence factor, the above formula is discretized by forward euler method:
s302, selecting the following cost function:
In the middle of Is a weight coefficient;
S303, order
Recording deviceAnd (3) obtaining:
Through the calculation, the method has the advantages that, Thus, whenIn this case, the cost function in step S302 takes a minimum value.
Preferably, the controller design of the secondary system in step S4 comprises the following sub-steps:
s401 is provided with Taking f s and its i-th derivative f s (i) (i=1, 2,., n) as the expansion state variables, building an n+2-th order augmentation system state space model corresponding to the auxiliary system:
Wherein the state variables Control input u=i qs, output y=ω s, coefficient matrix:
S402, the GPIO pair ω s、fs and its i-th derivative f s (i) (i=1, 2, online estimation n):
Wherein the method comprises the steps of Representing an estimate of the state x, M is the observer gain matrix to be designed, which can be found by pole configuration. Discretizing the GPIO by using a forward Euler method to obtain the product:
Wherein I (n+2) represents an (n+2) x (n+2) th order identity matrix;
s403, obtaining a total disturbance estimated value based on the discrete form GPIO in the step S402 The following auxiliary system control laws are designed:
wherein K x is the state feedback gain, which can be obtained by the pole allocation method, The gain is compensated for the disturbance.
Preferably, the speed ring composite controller in step S5 is designed as follows:
In general, the above technical solutions conceived by the present invention have mainly the following advantages compared with the prior art:
(1) The invention utilizes the additive state decomposition technology to decompose the problems of rotation speed tracking and disturbance suppression of the permanent magnet synchronous motor into independent control problems of two subsystems, so that the controller design has higher degree of freedom and flexibility;
(2) The model predictive controller of the main system can be designed and operated offline, and the real-time calculation amount and the calculation complexity of the digital controller can be effectively reduced during practical application;
(3) The auxiliary system is used for solving the problem of speed loop disturbance suppression, and the GPIO is used for estimating the total disturbance of the system on line, so that the GPIO has stronger time-varying disturbance estimation performance compared with a conventional linear extended state observer;
(4) The method provided by the invention does not depend on an accurate model, when the system has parameter perturbation and unmodeled dynamic, the parameter perturbation and unmodeled dynamic can be used as a part of total disturbance to be estimated and compensated, and the system has strong robustness and is suitable for complex environments and severe working conditions;
(5) The method provided by the invention is applied to a PMSM speed regulation control system, has excellent system dynamic and steady state performance, can realize high-precision tracking of a constant value and a time-varying reference rotating speed, and meets the application requirements of the PMSM speed regulation control system in the field of high-performance servo.
Drawings
FIG. 1 is a schematic diagram of a PMSM control system according to the method of the present invention disclosed in an embodiment of the present invention;
FIG. 2 is a schematic flow chart of the method of the present invention;
FIG. 3 is an equivalent exploded schematic view of the speed ring subsystem;
FIG. 4 is a schematic diagram of a speed controller according to the present invention;
Fig. 5 is a waveform diagram of motor output signals when the reference rotational speed ω r =1000 rpm is set;
FIG. 6 is a graph of tracking error versus the present method and conventional MPC method when the reference speed ω r =1000 rpm is set;
fig. 7 is a waveform diagram of motor output signals when the reference rotational speed ω r =500 sin (20pi t) rpm is set;
Fig. 8 is a graph of tracking error versus the present method and conventional MPC method when the reference rotational speed ω r =500 sin (20pi t) rpm is set.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
Fig. 1 is a block diagram of a PMSM control system employing the method of the present invention. The speed loop adopts the model predictive controller based on the additive state decomposition, and the given reference rotating speed is omega r. The speed loop control signal i qr is used as a reference value of q-axis current, the reference value of d-axis current is i dr =0, the current loop control period is T c, and the tracking of d-axis current and q-axis current on the reference current is realized by adopting a conventional PID control strategy.
Fig. 2 is a flow chart of a method for controlling a model prediction speed of a permanent magnet synchronous motor based on additive state decomposition according to an embodiment of the present invention, where the method shown in fig. 2 includes the following steps:
S1, under the dq synchronous rotation coordinate system, establishing a mathematical model of the surface-mounted PMSM as follows:
Wherein R and L are stator resistance and stator inductance, p is the pole pair number of the motor, J is the rotor moment of inertia, B is the viscous damping coefficient, ψ f is the rotor permanent magnet flux linkage, i d and i q are the d and q axis currents, u d and u q are the d and q axis voltages, ω is the rotor angular velocity, ω e =pω is the rotor electrical angular velocity, and T L is the load torque.
S2, FIG. 3 is an equivalent system decomposition schematic diagram, and the speed subsystem is divided into a main system and an auxiliary system according to an additive state decomposition idea, so that the control problem is simplified. The main system (nominal system) is noted as:
Where ω p is the main system state and i qp is the main system control input. The main system control targets are: i qp is designed such that when time t→infinity, ω p-ωr →0.
Definition:
Wherein i qr is a speed loop composite control law, omega s and i qs are respectively used as the state and control input of an auxiliary system, and an auxiliary system state equation is established:
Order the The above auxiliary system is further noted as:
the control targets of the auxiliary system are as follows: i qs is designed such that when time t→infinity, ω s →0.
S3, setting a speed ring discrete period as T s, and discretizing a main system by using a forward Euler method to obtain the product:
ωp(k+1)＝ωp(k)+Tsbiqp(k).
Defining a main system speed tracking error:
the first order derivative is obtained and then discretized by a forward Euler method to obtain:
assume that e p converges exponentially to 0, i.e
Wherein the method comprises the steps ofThe index convergence coefficient is obtained by discretizing the above formula by using a forward Euler method:
selecting the following cost function:
In the middle of Is a weight coefficient.
Order the
Recording deviceAnd (3) obtaining:
Through the calculation, the method has the advantages that, Thus, whenAnd when the cost function is the minimum value.
S4, designing a state feedback control law based on disturbance estimation and compensation, and inhibiting influence of disturbance on output of an auxiliary system. Is provided with Taking f s and its i-th derivative f s (i) (i=1, 2,., n) as the expansion state variables, building an n+2-th order augmentation system state space model corresponding to the auxiliary system:
Wherein the state variables Control input u=i qs, output y=ω s, coefficient matrix:
The following GPIO was designed to make an online estimate of ω s、fs and its i-derivative f s (i) (i=1, 2,., n):
Wherein the method comprises the steps of Representing an estimate of the state x, M is the observer gain matrix to be designed, which can be found by pole configuration. Discretizing the GPIO by using a forward Euler method to obtain the product:
Wherein I (n+2) represents an (n+2) × (n+2) th order identity matrix.
Total disturbance estimated value based on the above discrete form GPIOThe following auxiliary system control laws are designed:
wherein K x is the state feedback gain, which can be obtained by the pole allocation method, The gain is compensated for the disturbance.
S5, the structure of the permanent magnet synchronous motor model prediction speed control system based on the additive state decomposition is shown in fig. 4. And (3) performing controller fusion on control inputs of the main system and the auxiliary system of the speed loop, and designing the following speed loop composite control law:
In order to test the control performance of the permanent magnet synchronous motor model predictive speed control method based on the additive state decomposition, the method is applied to a PMSM speed regulation system, and motor parameters are given in table 1. The set load torque is:
TABLE 1
Fig. 5 (a) - (d) are respectively a reference input and output rotational speed waveform, a q-axis current reference value i qr waveform, an a-phase current i a waveform, and an electromagnetic torque T e waveform when the reference rotational speed ω r =1000 rpm is set. Fig. 6 is a comparison of motor speed tracking error for the method provided by the present invention and a conventional MPC method. As can be seen from fig. 5 and fig. 6, the method provided by the invention can effectively estimate and compensate the total disturbance in the speed regulating system of the permanent magnet synchronous motor, inhibit the influence of load mutation, time-varying load and the like on the motor rotation speed, realize high-precision tracking of the motor output rotation speed on a given reference rotation speed, and has stronger robustness compared with the conventional MPC speed controller.
In fig. 7, (a) - (e) are the reference input and output rotational speed waveforms, the rotational speed tracking error waveform, the q-axis current reference value i qr waveform, the a-phase current i a waveform, and the electromagnetic torque T e waveform, respectively, when the reference rotational speed ω r =500 sin (20pi T) rpm is set. Fig. 8 is a comparison of motor speed tracking error for the method provided by the present invention and a conventional MPC method. As can be seen from fig. 8, the method provided by the invention has strong robustness to load abrupt change, time-varying load and the like, and has higher tracking precision to time-varying reference signals.
It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the invention and is not intended to limit the invention, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.

Claims (6)

1.基于加性状态分解的永磁同步电机模型预测速度控制方法，其特征在于，包括以下步骤：1. A permanent magnet synchronous motor model prediction speed control method based on additive state decomposition, characterized in that it comprises the following steps: S1、建立dq同步旋转坐标系下表贴式永磁同步电机的数学模型；S1. Establish a mathematical model of a surface-mounted permanent magnet synchronous motor in a dq synchronous rotating coordinate system; S2、利用加性状态分解技术，将速度子系统等效分解为标称主系统和包含不确定性的辅系统；S2. Using the additive state decomposition technique, the speed subsystem is equivalently decomposed into a nominal main system and an auxiliary system containing uncertainties; S3、针对主系统，设计指数收敛型模型预测控制器，使得主系统输出对给定参考转速的跟踪误差以指数形式渐近收敛至0附近；S3. For the main system, an exponential convergence model predictive controller is designed so that the tracking error of the main system output to a given reference speed converges asymptotically to near 0 in an exponential form; S4、针对辅系统，设计广义比例积分观测器在线估计速度子系统的总扰动，在此基础上，设计基于扰动主动补偿的状态反馈控制律，抑制扰动对辅系统输出的影响；S4. For the auxiliary system, a generalized proportional-integral observer is designed to estimate the total disturbance of the speed subsystem online. On this basis, a state feedback control law based on active disturbance compensation is designed to suppress the influence of disturbance on the output of the auxiliary system. S5、对主系统和辅系统的控制输入进行融合，得到速度环复合控制律。S5. The control inputs of the main system and the auxiliary system are integrated to obtain the speed loop composite control law. 2.根据权利要求1所述的基于加性状态分解的永磁同步电机模型预测速度控制方法，其特征在于，所述步骤S1中的表贴式永磁同步电机数学模型建立为：2. The method for predicting speed control of a permanent magnet synchronous motor model based on additive state decomposition according to claim 1 is characterized in that the mathematical model of the surface mounted permanent magnet synchronous motor in step S1 is established as follows: 其中R和L分别为定子电阻和定子电感，p为电机极对数，J为转子转动惯量，B为粘滞阻尼系数，ψf为转子永磁体磁链，id和iq分别为d、q轴电流，ud和uq分别为d、q轴电压，ω为转子角速度，ωe＝pω为转子电角速度，TL为负载转矩。Where R and L are the stator resistance and stator inductance respectively, p is the number of motor pole pairs, J is the rotor moment of inertia, B is the viscous damping coefficient, ψf is the magnetic flux of the rotor permanent magnet, id and iq are the d-axis and q-axis currents respectively, ud and uq are the d-axis and q-axis voltages respectively, ω is the rotor angular velocity, ωe = pω is the rotor electrical angular velocity, and TL is the load torque. 3.根据权利要求1所述的基于加性状态分解的永磁同步电机模型预测速度控制方法，其特征在于，所述步骤S2中速度子系统的分解包括以下子步骤：3. The method for predicting speed control of a permanent magnet synchronous motor model based on additive state decomposition according to claim 1, characterized in that the decomposition of the speed subsystem in step S2 comprises the following sub-steps: S201、依据加性状态分解思想，将速度子系统划分为主系统和辅系统，简化控制问题；将主系统记为：S201. Based on the additive state decomposition concept, the speed subsystem is divided into a main system and an auxiliary system to simplify the control problem; the main system is recorded as: 其中ωp为主系统状态，uqp为主系统控制输入；主系统的控制目标为：设计uqp使得当时间t→∞时，ωp-ωr→0，其中ωr为给定的参考输入转速；Where ω p is the state of the main system, u qp is the control input of the main system; the control objective of the main system is: design u qp so that when time t→∞, ω p -ω r →0, where ω r is the given reference input speed; S202、定义：S202. Definition: 其中iqr为速度环复合控制律，将ωs和iqs分别作为辅系统的状态和控制输入，建立辅系统状态方程：Where iqr is the speed loop composite control law, ωs and iqs are used as the state and control input of the auxiliary system respectively, and the state equation of the auxiliary system is established: 令将上述辅系统进一步记为：make The above auxiliary system is further recorded as: 辅系统的控制目标为：设计iqs使得当时间t→∞时，ωs→0。The control objective of the auxiliary system is to design i qs so that when time t→∞, ω s →0. 4.根据权利要求1所述的基于加性状态分解的永磁同步电机模型预测速度控制方法，其特征在于，所述步骤S3中主系统的指数收敛型模型预测控制器的设计包括以下子步骤：4. The permanent magnet synchronous motor model predictive speed control method based on additive state decomposition according to claim 1 is characterized in that the design of the exponential convergence model predictive controller of the main system in step S3 comprises the following sub-steps: S301、设速度环离散周期为Ts，则主系统的离散化形式为：S301. Assume that the discrete period of the speed loop is T s , then the discretization form of the main system is: ωp(k+1)＝ωp(k)+Tsbiqp(k)；ω p (k+1)=ω p (k)+T s bi qp (k); 定义主系统速度跟踪误差：Define the main system speed tracking error: 对上式求一阶导数并进行离散化：Find the first-order derivative of the above formula and discretize it: 假设ep以指数形式收敛至0，即Assume that ep converges to 0 exponentially, that is 其中为指数收敛系数，对上式进行离散化：in is the exponential convergence coefficient, discretize the above formula: S302、选取如下代价函数：S302, select the following cost function: 式中为权重系数；In the formula is the weight coefficient; S303、步骤S302中的代价函数取得最小值时对应的主系统控制律为：S303. When the cost function in step S302 reaches the minimum value, the corresponding main system control law is: 其中 in 5.根据权利要求1所述的基于加性状态分解的永磁同步电机模型预测速度控制方法，其特征在于，所述步骤S4中辅系统的控制器设计包括以下子步骤：5. The method for predicting speed control of a permanent magnet synchronous motor model based on additive state decomposition according to claim 1, characterized in that the controller design of the auxiliary system in step S4 comprises the following sub-steps: S401、设将fs及其i阶导数作为扩张状态变量，建立辅系统对应的n+2阶增广系统状态空间模型：S401, set f s and its i-th order derivative As the extended state variable, the n+2-order augmented system state space model corresponding to the auxiliary system is established: 其中状态变量控制输入u＝uqs，输出y＝ωs，系数矩阵：The state variables Control input u = u qs , output y = ω s , coefficient matrix: S402、设计如下GPIO对ωs、fs及其i阶导数进行在线估计：S402, design the following GPIO pair ω s , f s and its i-th order derivative To get an online estimate: 其中表示对状态x的估计，M为待设计的观测器增益矩阵，可由极点配置法求取；对上述GPIO进行离散化：in Represents the estimation of state x, M is the observer gain matrix to be designed, which can be obtained by pole placement method; discretize the above GPIO: 其中I(n+2)表示(n+2)×(n+2)阶单位矩阵；Where I (n+2) represents the (n+2)×(n+2)-order identity matrix; S403、基于上述步骤S402中离散形式GPIO得到的总扰动估计值设计如下辅系统控制律：S403: The total disturbance estimation value obtained based on the discrete GPIO in step S402 Design the following auxiliary system control law: 其中Kx为状态反馈增益，可由极点配置法求得，为扰动补偿增益。Where K x is the state feedback gain, which can be obtained by the pole placement method. is the disturbance compensation gain. 6.根据权利要求1所述的基于加性状态分解的永磁同步电机模型预测速度控制方法，其特征在于，所述步骤S5中速度环复合控制器设计如下：6. The method for predicting speed control of a permanent magnet synchronous motor model based on additive state decomposition according to claim 1, characterized in that the speed loop composite controller in step S5 is designed as follows:
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