CN116566270A - Permanent magnet synchronous motor finite time control method and system based on super local model - Google Patents
Permanent magnet synchronous motor finite time control method and system based on super local model Download PDFInfo
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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
- H02P21/14—Estimation or adaptation of machine parameters, e.g. flux, current or voltage
- H02P21/18—Estimation of position or speed
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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
- H02P21/0003—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
- H02P21/0017—Model reference adaptation, e.g. MRAS or MRAC, useful for control or parameter estimation
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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
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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
- 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
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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- H02P2207/00—Indexing scheme relating to controlling arrangements characterised by the type of motor
- H02P2207/05—Synchronous machines, e.g. with permanent magnets or DC excitation
- H02P2207/055—Surface mounted magnet motors
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Abstract
The invention provides a permanent magnet synchronous motor finite time control method and a permanent magnet synchronous motor finite time control system based on a super local model, wherein the method comprises the following steps: constructing a super local model of a speed regulation system of the permanent magnet synchronous motor; designing a finite time observer, and estimating unknown dynamics of the super local model by using the finite time observer to obtain an estimation error of the unknown dynamics, which is stable in finite time and converges to zero; designing a finite time stability controller based on the superlocal model and the estimation error of the finite time observer; and controlling the speed regulating system of the permanent magnet synchronous motor based on the finite time stable controller. The method of the invention estimates the unknown dynamic of the system on line through a limited time observer under the condition that the unknown dynamic exists; by adjusting the parameters of the controller, the given rotating speed of the permanent magnet synchronous motor can be tracked quickly and stably.
Description
Technical Field
The invention belongs to the technical field of permanent magnet synchronous motor control, and particularly relates to a permanent magnet synchronous motor limited time control method and system based on a super local model.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Permanent magnet synchronous motors (permanent magnet synchronous machine, PMSM) have the advantages of wide speed regulation range, high efficiency and high power density, and are currently indispensable motor equipment in the field of production and activity. Typically, the electromagnetic torque of the PMSM is generated by the interaction of the rotor field and the magnetic field generated by the stator current, the performance index function is designed using the deviation between the current reference value and the feedback value, and the controller is constructed, the reference value of the current being given by the PI controller of the outer ring of the rotational speed.
In order to meet the requirements of economic and social development on the high-precision speed regulation performance of the PMSM, domestic and foreign scholars put forward control strategies such as sliding mode control, fuzzy control, predictive control, neural network control and the like. In order to obtain a faster response speed, engineers have proposed model predictive torque control, which introduces the torque and rotational speed of the PMSM into the predictive model, discarding the inner and outer ring cascade structure of current and rotational speed.
However, the prediction accuracy of the existing method depends on the accuracy of a PMSM mechanism model, in practical application, unknown disturbance such as disturbance voltage of an inverter, cross coupling and saturation effect of ferromagnetic materials, influence of temperature on flux linkage and resistance and the like can affect the accuracy of the PMSM model, and parameters of a motor are difficult to accurately obtain, so that parameter mismatch of a controller is caused, and control performance is deteriorated.
In order to improve the robustness of the PMSM speed regulation control strategy, an adaptive parameter identification method for on-line observation of the stator resistance, the rotor flux linkage and the inductance of the PMSM is generally adopted. However, when the motor is operating in steady state, due to the underrank problem, the observer cannot recognize all parameters, in particular inductance and flux linkage, from being observed independently.
In order to overcome the dependence of the traditional control method on parameters, researchers have proposed parametric-model-free predictive control. And directly establishing a lookup table between the current variation and the voltage vector, and updating the current variation intersecting the voltage vector in the lookup table in real time. However, when the voltage vector does not change, the lookup table stops updating, which increases the parameter estimation error and deteriorates the anti-interference capability of the system. In addition, in order to improve the estimation accuracy of unknown parameters or disturbances, the unknown part of the PMSM model is expanded to an expanded state and estimated by using an expanded state observer, but the expanded observer itself has the problems of a large number of tuning parameters and difficulty in adjustment.
Disclosure of Invention
Aiming at the speed control problem of the permanent magnet synchronous motor, the invention provides a permanent magnet synchronous motor finite time control method and system based on a super local model, which are used for overcoming the defects of difficult establishment of an accurate mathematical model, poor unknown disturbance estimation precision and the rotating speed tracking precision of the prior control technology in the prior method, do not need to predict PMSM parameters, and can obtain a model-free control strategy with good static and dynamic rotating speed tracking performance.
To achieve the above object, one or more embodiments of the present invention provide the following technical solutions:
the first aspect of the invention provides a permanent magnet synchronous motor finite time control method based on a super local model, which comprises the following steps:
constructing a super local model of a speed regulation system of the permanent magnet synchronous motor;
designing a finite time observer, and estimating unknown dynamics of the super local model by using the finite time observer to obtain an estimated value and an estimated error of the unknown dynamics;
designing a finite time stability controller based on the super local model, the estimated value of the finite time observer and the estimated error;
and controlling the speed regulating system of the permanent magnet synchronous motor based on the finite time stable controller.
The second aspect of the invention provides a permanent magnet synchronous motor finite time control system based on a super local model, which comprises:
a super local model building module configured to: constructing a super local model of a speed regulation system of the permanent magnet synchronous motor;
a finite time observer design module configured to: designing a finite time observer, and estimating unknown dynamics of the super local model by using the finite time observer to obtain an estimated value and an estimated error of the unknown dynamics;
a finite time stabilization controller design module configured to: designing a finite time stability controller based on the super local model, the estimated value of the finite time observer and the estimated error;
a permanent magnet synchronous motor control module configured to: and controlling the speed regulating system of the permanent magnet synchronous motor based on the finite time stable controller.
The one or more of the above technical solutions have the following beneficial effects:
(1) The whole design process of the invention mainly considers the simplicity and stability of the permanent magnet synchronous motor speed controller design and the rapid accuracy of speed tracking. The method overcomes the defects of the existing method that the accurate mathematical model is difficult to build, the unknown disturbance estimation precision is poor, and the existing control technology has the rotating speed tracking precision.
(2) The invention utilizes the finite-time observer to estimate the unknown dynamic of the super local model, and the controller is only related to the input and output data of the control system in the design process without PMSM mathematical model parameter information, and the designed finite-time stable controller has stronger load disturbance resistance and higher track tracking precision.
(3) The invention has the following specific advantages: firstly, under the condition that unknown dynamic exists, the method estimates the unknown dynamic of the system on line through a limited time observer; secondly, the given rotating speed of the permanent magnet synchronous motor can be tracked rapidly and stably by adjusting the parameters of the controller; thirdly, a new finite time stability control strategy stability analysis method based on the super local model is provided; fourth, the designed controller is only related to the online measurement data of the control system, and an accurate mathematical model of the permanent magnet synchronous motor is not needed.
Additional aspects of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
Fig. 1 is a flow chart of a method of a first embodiment.
Fig. 2 is a speed response curve of the first embodiment at the time of a step of the desired speed.
Fig. 3 is a graph of the speed tracking error at the time of the step desired speed of the first embodiment.
Fig. 4 is a graph of the control input current response at a step desired speed for the first embodiment.
Fig. 5 is a graph showing the speed response of the first embodiment when the jump step is to a desired speed.
Fig. 6 is a graph of the velocity tracking error at the time of the jump step of the first embodiment for the desired velocity.
Fig. 7 is a graph of the control input current response at a jump step desired speed for the first embodiment.
Detailed Description
Example 1
The embodiment discloses that includes:
step one: the dynamic model of the surface-mounted PMSM under synchronous rotation coordinates is described as:
wherein J is moment of inertia, Ω is rotor angular velocity, B is viscous friction coefficient, T L For loading torque, T e As electromagnetic torque, it can be expressed as:
wherein ,id Is the stator current of the d-axis, i q Is the stator current of q-axis, p n The number of pole pairs is represented,represents rotor magnetic flux, L d and Lq The d-axis and q-axis stator inductances, respectively. Satisfy L for surface-mounted PMSM d ＝L q Electromagnetic torque T e Can be rewritten as
Then, equation (1) can be rewritten as
The discrete time form of formula (3) can be obtained by a first-order Euler discrete method as follows
wherein ,Ts Representing the sampling time.
Definition y (k) =Ω (k),
u(k)＝i q (k)，
F＝-(T s BΩ(k)/J)+T s T L (k)/J+Ω(k)。
equation (4) is expressed as a discrete time super local model as follows:
y(k+1)＝αu(k)+F(k) (5)
where y (k+1) is the output angular velocity of the PMSM at time k+1, y (k) is the output angular velocity of the PMSM at time k, and u (k) is the control input of the PMSM at time k (i.e., stator current i q ) F (k) represents unknown dynamics, including external disturbances, unmodeled dynamicsAnd parameter variation.
Step two: estimating unknown dynamics F (k)
The first order differential equation for the unknown dynamic F (k) is expressed as:
ΔF(k)＝F(k+1)-F(k) (6)
defining an unknown dynamic estimation error e F(k) and eΔF (k) The method comprises the following steps:
wherein Is an estimate of F (k),>is an estimate of Δf (k).
Consider a finite time stable observer as follows:
wherein ,
C. mu is an adjustable parameter and needs to be set manually;
the observer (9) causes e F (k) And eΔf (k) converge to a neighborhood of zero in a finite time.
Thus, formula (5) can be expressed as:
if e F (k)＝0 (10)
Step three: finite time stable tracking controller design
This step proposes a finite time stability tracking control (FSTC-ULM) strategy based on a super local model.
The output error of the super local model of the speed regulating system is defined as follows:
e y (k)＝y(k)-y d (k) (11)
wherein yd (k) Representing the expected output trajectory of the super local model at time k.
To facilitate controller design and convergence analysis, the following quotients are given.
Lemma 1: consider the output of a discrete time dynamic system asIf the Liapunov function V (k) of z (k) is decreasing and positive, let δ (k) be a positive function of V (k), meaning that δ (k) satisfies the following condition:
δ(k)＝δ(V(k))≥τ 1-β (12)
wherein τ >0, β ε [0,1].
If V (k) satisfies the following inequality:
V(k+1)-V(k)≤-δ(k)(V(k)) β (13)
the discrete-time dynamic system is stable, i.e. z (k) converges to 0 when k > M, M representing a finite number of steps.
And (4) lemma 2: considering the superlocal model (10), the following control law is adopted:
the tracking error (11) satisfies:
e y (k+1)+e F (k)＝0 (15)
e if the finite time stable observer defined by equation (9) is employed y (k+1) converges to a neighborhood of 0 in a finite number of steps.
Theorem 1: for a PMSM speed regulation system described by a superlocal model (10), its finite time stable tracking controller is designed to:
wherein eta is >0 and r is [1,2].
Then under the action of the control law (16), the super local model (5) of the PMSM speed regulation system with unknown dynamic F (k) meets the following error dynamic:
e y (k+1)+e F (k)＝γ(e y (k))e y (k) (18)
that is to say,obtained from formula (9), then e y (k+1) converges to a bounded neighborhood of 0 for a finite time.
The controller outputs stator current i q The input is the error of the desired rotational speed and the actual rotational speed. The controller generates stator current i according to the rotation speed error q The stator current i q As the reference current of the PMSM current loop, the reference current is compared with the actually collected stator current, and the current inner loop controller ensures that the actual stator current tracking controller of the motor outputs the stator current i q Thereby ensuring that the whole PMSM speed regulation system can track a given speed.
Step four: stability analysis
This step mainly completes the demonstration of theorem 1 in step three.
And (3) proving: 1) If e F (k) =0, then, from (10), e y (k+1) satisfies
In this case, the unknown dynamics F (k) are perfectly estimated by the finite time stable observer. And e y (k) Stable and converge to zero for a finite time, if e y (k) Satisfy the following requirements
e y (k+1)＝γ(e y (k))e y (k) (20)
wherein γ(ey (k) Defined in formula (17). Definition e y (k) The Liapunov function of (C) is as follows
V(k)＝(e y (k)) T e y (k) (21)
Taking into account the differential form of V (k), one can obtain
V(k+1)-V(k)＝-ξ(k)(V(k)) 1/r (22)
Where ζ (k) = (1- (γ (e) y (k))) 2 )(V(k)) 1-1/r And γ (e (k)). Epsilon. -1, 0. Thus, ζ (k) is a positive definite function. Substituting equation (21) into equation (17), the function ζ (k) is further expressed as
Obtainable from the formula (23)
Where k > M, M represents a finite number of steps. Therefore, the action of ζ (k) is the same as δ (k) in the argument 1, and the condition (12) is satisfied. Using the relationships (11) and (20), it is possible to obtain
y(k+1)＝γ(e y (k))e y (k)+y d (k+1) (25)
According to the quotation 2,it can be concluded that formula (25) results in e y (k+1) is stable and converges to zero for a finite time.
2) If e F (k) Bounded around zero, i.e. e F (k) Not equal to 0, can be deduced from equation (18)
y(k+1)＝y d (k+1)-e F (k)+γ(e y (k))e y (k) (26)
Consider the unknown dynamic estimation error e F (k) Satisfy the following requirements
||e F (k)||≤D，k>M (27)
Wherein D >0. Then, the difference of V (k) is expressed as follows:
V(k+1)-V(k)＝(e y (k+1)+e y (k)) T (e y (k+1)-e y (k))
＝((γ(e y (k))) 2 -1)(e y (k)) T e y (k)-2γ(e y (k))(e F (k)) T e y (k)+(e F (k)) T e F (k) (28)
from formulas (27) and (28), the upper bounds of V (k-1) -V (k) are obtained as follows:
V(k+1)-V(k)≤-Λ(e y (k))||e y (k)|| 2 -2|γ(e y (k))|D||e y (k)||+D 2 (29)
wherein Λ(ey (k))＝1-(γ(e y (k))) 2 . When e y (k) When the initial value of I is sufficiently large, V (k-1) -V (k) is negative, as can be seen from formula (29)
Λ(e y (k))||e y (k)|| 2 +2|γ(e y (k))|D||e y (k)||-D 2 >0 (30)
Obviously, formula (30) is a term for E y (k) The quadratic inequality of I, while the coefficient of equation (30) depends on e y (k) Solving inequality (30) to obtain
||e y (k) The true positive solution of I guarantees V (k+1) -V (k)<0 can be implemented, therefore, when e y (k) When i is sufficiently large, V (k) is monotonically decreasing to satisfy expression (31).
Step five: simulation experiment verification
The effectiveness of the proposed control scheme is verified through simulation experiments. The rated value of the permanent magnet synchronous motor is 0.75KW, 380V and 3000r/min. Physical parameter p n ＝4，L d ＝L q ＝8.5mH，J＝0.0008Kg·m 2 ，R=2.875Ω. Sampling time T s Taken at 0.01s.
It is noted here that the mathematical model parameters given are used only for generating input-output data in the simulation, independent of the controller design process. A traditional PI controller and an intelligent PI (i-PI) controller are subjected to simulation comparison experiments with the FSTC-ULM method provided by the invention, so that the superiority of the provided control scheme is verified. Wherein the i-PI controller is configured as
wherein yd E is the tracking error, k p and ki Proportional gain and integral gain, respectively.
The desired rotational speed of the PMSM is set to be both a step signal and a jump step signal.
1) The desired rotational speed is set as a constant value step signal: the step change value was 1000rpm, the load torque (10 N.m) was suddenly applied at 0.1s, and the load was released at 0.25 s. Among the three comparison controllers, the gain of the PI controller is selected to be k p＝0.7 and ki Gain of the i-PI controller (32) is selected to be k p ＝200，k i Parameters of the fstc-ULM controller (16) are selected to be α=0.06, r=1.5, η=0.05, c=1.5 and μ=0.5, =0.1 and α=50. Notably, in the gain tuning options of the three comparison controllers, it is necessary to track the essence at the control systemA compromise is made between the degree and the load-resisting performance, so that optimum performance is achieved. The simulation results are shown in fig. 2-4.
2) The desired rotational speed is set to a jump step signal: the initial rotational speed was set at 600rpm, the load torque (10 N.m) was suddenly increased at 0.1s, unloaded at 0.15s, the rotational speed signal was increased to 1200rpm at 0.25s, and the rotational speed signal was decreased to 800rpm at 0.3 s. In the simulation process, the controller parameter settings of the three comparison methods are the same as the parameter settings when the expected speed is a step signal. The simulation results are shown in fig. 4-6.
It is clear from fig. 2 that the control performance of the i-PI method is slightly better than that of the PI method, and the FSTC-ULM scheme achieves track following accuracy and load resistance superior to those of the PI and i-PI methods, among the three comparative methods. Meanwhile, when load is unloaded, the FSTC-ULM scheme still has better output response. Tracking error and control input current i of three control schemes q As shown in fig. 3 and 4.
As can be seen from fig. 5, the FSTC-ULM method is better able to track the changing speed step signal when the desired speed is a jump step signal, and the output response is barely overshot when the step signal amplitude changes. Meanwhile, compared with PI and i-PI methods, the FSTC-ULM method has stronger load disturbance resistance and higher track tracking precision. Figures 6 and 7 show the tracking error and the control input current i, respectively, for three control schemes q . As can be seen from fig. 6, the FSTC-ULM method has minimal tracking error. As can be seen from fig. 6, the PI and i-PI methods control a greater overshoot of the input current and a longer actuator saturation time when the desired speed trajectory changes abruptly, as compared to the FSTC-ULM method. And the i-PI method generates larger current ripple from the load surge to the unloading stage, resulting in larger steady state error.
Example two
The embodiment discloses a permanent magnet synchronous motor finite time control system based on super local model, including:
a super local model building module configured to: constructing a super local model of a speed regulation system of the permanent magnet synchronous motor;
a finite time observer design module configured to: designing a finite time observer, and estimating unknown dynamics of the super local model by using the finite time observer to obtain an estimated value and an estimated error of the unknown dynamics;
a finite time stabilization controller design module configured to: designing a finite time stability controller based on the super local model, the estimated value of the finite time observer and the estimated error;
a permanent magnet synchronous motor control module configured to: and controlling the speed regulating system of the permanent magnet synchronous motor based on the finite time stable controller.
Further, a super local model of a speed regulation system of the permanent magnet synchronous motor is constructed, comprising: constructing a dynamic model of a speed regulation system of the permanent magnet synchronous motor;
a first-order Euler discrete method is utilized to discrete a dynamic model of a speed regulation system of the permanent magnet synchronous motor;
and obtaining a super local model of the permanent magnet synchronous motor speed regulation system based on a discrete time form of a dynamic model of the permanent magnet synchronous motor speed regulation system.
Further, the finite time stable tracking controller is designed to:
wherein eta is >0 and r is [1,2].
It will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented by general-purpose computer means, alternatively they may be implemented by program code executable by computing means, whereby they may be stored in storage means for execution by computing means, or they may be made into individual integrated circuit modules separately, or a plurality of modules or steps in them may be made into a single integrated circuit module. The present invention is not limited to any specific combination of hardware and software.
While the foregoing description of the embodiments of the present invention has been presented in conjunction with the drawings, it should be understood that it is not intended to limit the scope of the invention, but rather, it is intended to cover all modifications or variations within the scope of the invention as defined by the claims of the present invention.
Claims (10)
1. The finite time control method of the permanent magnet synchronous motor based on the super local model is characterized by comprising the following steps of:
constructing a super local model of a speed regulation system of the permanent magnet synchronous motor;
designing a finite time observer, and estimating unknown dynamics of the super local model by using the finite time observer to obtain an estimated value and an estimated error of the unknown dynamics;
designing a finite time stability controller based on the super local model, the estimated value of the finite time observer and the estimated error;
and controlling the speed regulating system of the permanent magnet synchronous motor based on the finite time stable controller.
2. The method for controlling the finite time of the permanent magnet synchronous motor based on the super-local model as claimed in claim 1, wherein the constructing the super-local model of the speed regulation system of the permanent magnet synchronous motor comprises the following steps: constructing a dynamic model of a speed regulation system of the permanent magnet synchronous motor;
a first-order Euler discrete method is utilized to discrete a dynamic model of a speed regulation system of the permanent magnet synchronous motor;
and obtaining a super local model of the permanent magnet synchronous motor speed regulation system based on a discrete time form of a dynamic model of the permanent magnet synchronous motor speed regulation system.
3. The method for controlling the finite time of the permanent magnet synchronous motor based on the super-local model as claimed in claim 2, wherein the super-local model of the speed regulation system of the permanent magnet synchronous motor is as follows:
y(k+1)＝αu(k)+F(k)
wherein y (k+1) is the output angular velocity of the permanent magnet synchronous motor at the moment k+1, u (k) is the control input current of the permanent magnet synchronous motor at the moment k, and F (k) represents unknown dynamics, including external interference, unmodeled dynamics and parameter variation;T s represents the sampling time, p n Represents the pole pair number>And represents rotor magnetic flux, and J is moment of inertia.
4. A method for finite time control of a permanent magnet synchronous motor based on a super local model as claimed in claim 3, wherein the finite time observer design process comprises:
a first order differential equation defining the unknown dynamics F (k) of the super local model:
ΔF(k)＝F(k+1)-F(k)
defining an estimation error e of the unknown dynamics F (k) and the unknown dynamics DeltaF (k) after differentiation F(k) and eΔF (k)：
wherein ,is an estimate of the unknown dynamic F (k), -, for example>Is an estimate of the unknown dynamic Δf (k) after differencing;
the finite time stabilization observer is designed to:
wherein ,
wherein, C and mu are adjustable parameters.
5. The method of finite time control of permanent magnet synchronous motor based on super local model as claimed in claim 4, wherein the estimated error is assumed to be stable in finite time and converged to zero based on the estimated value observed by the finite time stable observerThe super local model is restated as:
6. the method for controlling the finite time of the permanent magnet synchronous motor based on the super local model as claimed in claim 5, wherein the output error of the super local model is defined as follows:
e y (k)＝y(k)-y d (k)
wherein ,yd (k) Representing the expected output trajectory of the super-local model at time k, y (k) is the output of the super-local model at time k.
7. The method for controlling the finite time of the permanent magnet synchronous motor based on the super local model as claimed in claim 6, wherein the finite time stable tracking controller is designed to:
wherein eta is >0 and r is [1,2].
8. A permanent magnet synchronous motor finite time control system based on a super local model, comprising:
a super local model building module configured to: constructing a super local model of a speed regulation system of the permanent magnet synchronous motor;
a finite time observer design module configured to: designing a finite time observer, and estimating unknown dynamics of the super local model by using the finite time observer to obtain an estimated value and an estimated error of the unknown dynamics;
a finite time stabilization controller design module configured to: designing a finite time stability controller based on the super local model, the estimated value of the finite time observer and the estimated error;
a permanent magnet synchronous motor control module configured to: and controlling the speed regulating system of the permanent magnet synchronous motor based on the finite time stable controller.
9. The finite time control system of the permanent magnet synchronous motor based on the super local model as set forth in claim 8, wherein the constructing the super local model of the speed regulation system of the permanent magnet synchronous motor comprises: constructing a dynamic model of a speed regulation system of the permanent magnet synchronous motor;
a first-order Euler discrete method is utilized to discrete a dynamic model of a speed regulation system of the permanent magnet synchronous motor;
and obtaining a super local model of the permanent magnet synchronous motor speed regulation system based on a discrete time form of a dynamic model of the permanent magnet synchronous motor speed regulation system.
10. The ultra-local model-based permanent magnet synchronous motor finite time control system according to claim 8, wherein the finite time stable tracking controller is designed to:
wherein eta is >0 and r is [1,2].
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